diff --git a/Fa_sample_funcs.R b/Fa_sample_funcs.R new file mode 100644 index 0000000..f422121 --- /dev/null +++ b/Fa_sample_funcs.R @@ -0,0 +1,68 @@ +####################### +#---#DETERMINE WHAT ALLELES FALL IN WHAT CATEGORIES---# +####################### + +get.allele.cat<-function(UK_genpop, region_makeup, N_REGIONS, n_ind_p_pop, n_drop=2,glob_only=F){ + + n_pops<-length(n_ind_p_pop) + #--Set up categories for GLOBAL ALLELES + allele_freqs<-colSums(UK_genpop@tab)/(sum(n_ind_p_pop)*2) + min_freq<-(n_drop/(2*sum(n_ind_p_pop))) + glob<-as.vector(which(allele_freqs>min_freq)) + glob_v_com<-as.vector(which(allele_freqs>0.10)) + glob_com<-as.vector(which(allele_freqs>0.05)) + glob_lowfr<-as.vector(which(allele_freqs<0.10&allele_freqs>0.01)) + glob_rare<-as.vector(which((allele_freqs<0.01)&(allele_freqs>min_freq))) + + if (!(glob_only)) { + + #--REGIONAL ALLELES--# #NOT USED IN WHITE ASH MANUSCRIPT- USED IN OTHER PROJECTS + reg_com<-vector(length=length(allele_freqs)); reg_rare<-vector(length=length(allele_freqs)) + reg_com_int<-NULL #These are the interesting ones- common in one region, rare in others + allele_freq_by_reg<-matrix(nrow=N_REGIONS,ncol=length(allele_freqs)) + + #this will go region by region and determine allele frequencies in that region + #then it determines for which regions the allele frequency is >0.20 + #then it gives each allele a "+1" when it is at >0.20 in a region + #alleles for which this count==1 at the end, are only present at >0.20 for one region + for (nr in 1:N_REGIONS){ + #get the number of individuals in the region (sum across populations in the region) + n_ind_this_region<- sum(n_ind_p_pop[region_makeup[nr][[1]]]) #note that the "1" just gets us the list item, its ok + #divide allele counts by number of individuals (times 2 because diploid) + allele_freq_by_reg[nr,]<-colSums(UK_genpop[region_makeup[[nr]],]@tab)/(n_ind_this_region*2) + #record if above threshold for common + reg_com<- as.numeric(reg_com) + as.numeric(allele_freq_by_reg[nr,]>=0.20) + #check: print(as.vector(which((allele_freq_by_reg[nr,]>=thresh_freq_H)))) + #record if below threshold for rare + reg_rare<- as.numeric(reg_rare) + as.numeric(allele_freq_by_reg[nr,]<0.10) + } + #this is the number of alleles that are regionally common + #check: which(reg_com==1); which(reg_rare==N_REGIONS) + #check: ((reg_com==1)|(reg_com==2)|(reg_com==3))&((reg_rare==5)|(reg_rare==4)) + reg_com_int<-which((reg_com==1)&(reg_rare>=(N_REGIONS-3))) + #check: allele_freq_by_reg[,reg_com_int] + + + #--LOCAL ALLELES--# + #get the populations having alleles which occur at frequency greater than a given frequency in focal pop'n + #and not more than another frequency in more than two other populations + local_freqs<-UK_genpop@tab/as.vector(n_ind_p_pop*2) + #identify columns (alleles) for which at least one population exceeds min threshold + loc_com_d1<-as.vector(which((colMax(as.data.frame((local_freqs)))>=0.20)&(apply(local_freqs,2,sort)[(n_pops*.95),]<0.10),arr.ind=F)) + loc_com_d2<-as.vector(which((colMax(as.data.frame((local_freqs)))>=0.15)&(apply(local_freqs,2,sort)[(n_pops*.90),]<0.05),arr.ind=F)) + loc_rare<-as.vector(which((colMax(as.data.frame((local_freqs)))<0.10)&(colMax(as.data.frame((local_freqs)))>min_freq))) + } else reg_com_int<-NA; loc_com_d1<-NA; loc_com_d2<-NA; loc_rare<-NA + list(glob, glob_v_com, glob_com, glob_lowfr, glob_rare, reg_com_int, loc_com_d1, loc_com_d2, loc_rare) +} + + +##################### +#--GENERAL SAMPLING FUNCTION--# +##################### + +#we pass it a vector of populations and a vector of sample sizes, as well as the genind object +sample.pop<-function(genind_obj,vect_pop_ID,vect_samp_sizes){ + for (p in 1:length(vect_pop_ID)) + alleles[p,]<-colSums(genind_obj[[vect_pop_ID[p]]]@tab[sample(1:nrow(genind_obj[[vect_pop_ID[p]]]@tab), vect_samp_sizes[p]),]) + alleles +} diff --git a/Mypramidata/mp_total.gen b/Mypramidata/mp_total.gen new file mode 100644 index 0000000..1082a07 --- /dev/null +++ b/Mypramidata/mp_total.gen @@ -0,0 +1,171 @@ +"Magnolia pyramidata, wild and then garden" +mpy85 +mpy93 +mpy83 +mpy78(2) +mpy81(2) +mpy15 +mpy17 +mpy96b +mpy72(2) +M6D3 +M8D8 +POP +IMLS071 , 178188 120120 197201 167169 183189 103111 212224 178192 203207 119129 202202 +IMLS072 , 157178 118118 197201 167169 181189 092103 218224 178180 207216 123129 204204 +IMLS073 , 162178 117117 197197 169169 181189 103103 218224 178178 202206 127131 000000 +IMLS074 , 184186 117120 197201 167167 181189 090103 218222 176176 205205 123133 178190 +IMLS075 , 180184 117120 197201 167167 181191 090106 222224 190192 205214 125133 190190 +IMLS076 , 166184 119120 197201 167167 191195 090106 218224 184186 204214 119125 190208 +IMLS077 , 164170 117119 197201 165165 181189 090090 216226 178180 201204 119125 190210 +IMLS078 , 170176 118118 197197 167169 000000 103108 208230 178188 206216 121125 178196 +IMLS079 , 164166 118119 197201 167167 187189 106106 226226 178192 205216 119125 182190 +IMLS080 , 164184 120120 197201 167169 189195 103111 222224 184186 206216 113123 192192 +IMLS081 , 174182 120120 197197 169169 181195 106111 210218 178186 205216 125131 186208 +IMLS082 , 162164 118118 197201 167167 187195 085092 218218 168174 203203 125131 184210 +IMLS083 , 162172 118120 197197 167169 189195 092106 206218 164168 205205 125125 184200 +IMLS084 , 162164 118120 197201 167169 187189 085092 218218 164174 202205 125156 184206 +IMLS085 , 164172 118118 197197 169169 189195 092114 218218 168174 203206 125156 184206 +IMLS086 , 180194 117119 197201 167167 179189 094106 210218 174178 205205 125131 192200 +IMLS087 , 164186 121121 197201 167169 175181 106106 218226 168192 205207 121138 196204 +IMLS088 , 164166 117117 197201 167167 191191 106111 216218 170174 206206 123131 198198 +IMLS089 , 162164 120120 197197 167167 189191 090106 222222 184192 205207 127127 178192 +IMLS090 , 170178 119119 000000 169169 189193 106118 220224 164182 204216 117117 178212 +IMLS091 , 166174 118118 197197 167169 185193 090100 214214 178194 202204 151154 172188 +IMLS443 , 160174 118118 197197 167169 173173 106118 218220 180182 206206 125136 176180 +POP +IMLS092 , 168170 117118 197197 167177 173187 109109 220222 174174 202216 125142 178186 +IMLS093 , 164170 117117 197197 171175 173197 109111 196220 170180 203203 119123 168186 +IMLS094 , 164182 117117 197197 167171 175183 103106 220220 168174 198203 121125 168186 +IMLS095 , 168168 118118 197197 169177 175183 103106 206216 170170 198216 127127 176186 +IMLS096 , 164168 117117 197197 169175 173175 109111 196220 174188 203203 123123 176186 +IMLS097 , 170170 117117 197197 171171 183200 106109 206206 170174 203203 125127 168186 +IMLS098 , 164164 121121 197197 167167 189189 109109 220220 174186 203203 121125 168186 +IMLS099 , 164164 121121 197197 167167 183189 106109 220220 186186 198203 121125 168186 +IMLS100 , 166166 118121 197197 167171 183183 109109 198222 174174 198203 127142 176188 +IMLS101 , 138138 000000 000000 000000 163163 000000 202208 000000 000000 123129 164164 +IMLS102 , 138138 000000 000000 000000 163163 000000 204204 000000 000000 000000 178200 +IMLS103 , 166176 117121 197201 167175 187191 103106 206206 170180 201215 121125 188192 +IMLS104 , 166180 117119 197201 167167 173187 090100 214214 170190 205205 115133 000000 +IMLS105 , 166172 117117 197201 167167 173189 090108 216222 170172 203207 113115 204204 +IMLS106 , 164168 117118 197201 167167 191191 083090 210214 170174 207207 121133 196204 +IMLS107 , 164170 117117 197201 167167 191195 109114 224224 170174 203207 111115 194202 +IMLS108 , 172176 117117 197201 167167 195195 090109 206224 156170 203203 115127 186202 +IMLS109 , 164172 117117 197201 167167 187191 083100 208210 170174 205205 117121 192202 +IMLS110 , 172174 119119 197201 167167 173195 083083 202210 170192 205205 125129 192192 +IMLS111 , 166176 117118 197201 167167 189195 083111 204222 170170 202202 111111 202202 +IMLS112 , 168172 118118 197201 167167 193195 111111 210216 170178 207216 111111 202202 +IMLS113 , 172172 118118 197201 167167 193195 083109 220222 178178 207207 111138 202202 +IMLS114 , 168178 117117 197197 167167 187195 108111 210222 174186 201216 131138 184196 +IMLS115 , 164164 117117 197201 167167 193195 083103 204210 178206 201204 125131 188202 +IMLS116 , 166168 117119 197201 167167 193195 090103 204220 200206 207207 111129 192202 +IMLS117 , 172176 117117 197201 167167 191197 109111 000000 182188 201216 117119 166192 +IMLS118 , 164168 117119 197201 167167 173195 083090 210220 170206 201207 111125 196202 +IMLS119 , 164166 117117 197201 167167 173191 083111 210224 170180 207207 129138 198202 +IMLS120 , 168176 117117 197201 167167 173173 108109 204222 170180 207207 113127 190200 +IMLS121 , 168174 117119 197201 167167 173193 108111 204222 170180 203207 127129 186190 +IMLS122 , 164176 119199 197201 167167 173177 106108 206222 170170 207207 125129 190204 +IMLS123 , 164166 117119 197201 167167 179191 106109 206222 170170 207216 125129 190190 +IMLS124 , 164164 117118 197201 167167 173193 109111 218222 170170 207207 125129 190204 +IMLS125 , 168176 117118 197201 167167 177191 106108 218222 174176 203207 113125 190204 +IMLS126 , 164164 117118 197201 167167 179191 090094 204210 176176 207207 113125 188188 +IMLS127 , 164164 117117 197201 167167 189191 090111 204222 170176 207207 129131 192202 +IMLS128 , 164168 117119 197201 167167 173191 109109 210222 170170 201203 125129 188188 +IMLS129 , 168176 119119 197201 167167 173193 109111 204222 170180 207207 129129 190204 +IMLS130 , 162164 117118 197201 167167 191191 094108 210222 170176 201207 125129 188192 +IMLS390 , 162168 117118 197201 167167 173195 108111 204214 176190 207207 129133 198206 +IMLS391 , 164174 117117 197201 167167 173191 106106 204218 156200 201201 129138 190190 +IMLS392 , 176184 117117 197201 167167 173185 111111 214222 170170 207207 125133 198204 +IMLS393 , 168168 117117 197201 167169 187204 090111 216216 174176 203207 115129 190190 +IMLS394 , 164168 117118 197197 167167 187187 090090 216222 174176 203207 111127 200206 +IMLS395 , 164168 117117 197201 167169 187204 090111 224224 176198 207207 125129 190206 +IMLS396 , 170178 117117 197201 167169 191204 083111 216216 170170 207207 115131 190190 +IMLS397 , 174176 118118 197197 167167 187195 090111 204230 176176 201207 123158 200200 +IMLS398 , 166174 117119 197201 167171 187208 090100 206224 170174 207207 111133 202202 +IMLS399 , 164178 117119 197201 167167 187195 090111 204210 156176 203216 000000 200200 +IMLS400 , 174181 117117 197201 167167 175187 090100 216226 170176 201207 000000 204204 +IMLS401 , 162170 117118 195199 165165 187211 088090 210210 170176 201207 129138 202202 +IMLS402 , 174174 117119 197201 167167 187189 090109 204226 170190 207216 111158 186192 +IMLS403 , 164166 119119 197201 169169 189197 083090 204204 170186 207216 123144 202204 +IMLS404 , 174174 117117 197201 167167 173187 090111 204218 156180 207207 111125 190204 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197201 167167 177193 106108 216220 180186 203203 121131 188188 +IMLS416 , 164168 119119 197201 167167 185185 085090 210220 182186 203217 119123 170188 +IMLS417 , 168168 119119 197201 167167 191193 085090 216220 180182 204207 125131 184188 +IMLS418 , 168184 117119 197201 167167 191193 094100 216220 180180 203203 123125 184188 +IMLS419 , 184188 119119 197197 167167 173173 090090 210220 180180 203206 121133 184194 +IMLS420 , 168180 119119 197197 167169 173177 090108 210216 182186 203217 121127 188194 +POP +IMLS421 , 170170 117118 197201 169169 177185 103108 222224 176176 217217 119125 178178 +IMLS422 , 170170 118118 197201 169169 185185 103108 224224 186194 217217 125125 178178 +IMLS423 , 170170 118118 197201 169169 185185 116116 218224 176176 217217 119119 178178 +IMLS424 , 170170 117118 197201 169169 185185 108108 220224 176176 217217 121127 178178 +IMLS425 , 170170 117117 197201 169169 185185 108108 220224 176176 217217 000000 178178 +IMLS426 , 170170 117117 197201 169169 185185 108116 224224 176176 217217 119119 178178 +IMLS427 , 170170 117117 197201 169169 177177 116116 224224 176176 203217 121125 178178 +IMLS428 , 170170 117117 197201 169169 177185 108116 218224 176176 203217 121127 178178 +IMLS429 , 172174 117118 197201 167169 185185 103108 220220 176188 217217 121121 178178 +IMLS430 , 170172 117118 197201 167169 185185 103108 218220 176182 217217 121127 178178 +IMLS431 , 170174 117119 197201 167167 185185 103109 218220 186194 203216 121121 178178 +IMLS432 , 160170 117118 197201 167167 185189 103108 218220 176196 217217 127133 178178 +IMLS433 , 160174 117118 197201 167167 177189 106106 218220 176176 217217 121144 178178 +IMLS434 , 174186 117118 197201 167167 185189 108116 218220 176196 203217 121121 178198 +IMLS435 , 170170 117117 197201 167169 185185 108108 218220 186196 203203 121142 178178 +IMLS436 , 170170 117117 197197 167169 185185 116116 218220 176176 217217 133133 178198 +IMLS437 , 170186 117118 197201 167169 177183 106108 218220 186186 203217 121121 178178 +IMLS438 , 160170 117118 197201 167169 177177 106108 218220 176176 203217 121121 178178 +IMLS439 , 170174 117119 197201 167169 177185 103108 220224 186192 203203 127133 178178 +IMLS440 , 160170 117117 197197 169169 185189 106106 216220 176176 203217 121136 178178 +IMLS441 , 160170 118118 197201 167169 185185 108108 218220 176196 217217 121142 178178 +POP +IMLS445 , 170170 118118 197201 169169 185185 106106 220224 176196 217217 127133 178198 +IMLS446 , 170174 117118 197197 167169 177185 116116 220220 176176 217217 133133 178178 +IMLS447 , 166170 119119 197201 167167 175197 103108 216218 174184 202202 111119 196202 +IMLS449 , 168168 120120 197197 167167 183191 103103 206212 154180 201201 133133 198202 +IMLS453 , 170170 117118 197201 167169 185185 116116 216218 176196 203217 121121 178178 +IMLS454 , 170170 117117 197201 169169 185185 108116 218220 176176 217217 125127 178178 +IMLS456 , 164168 119119 197201 167167 191195 083111 210216 170178 201216 111125 196202 +IMLS457 , 168174 117119 197197 167167 191191 108109 210212 180182 205217 136136 170170 +IMLS458 , 168170 120120 197197 167169 191200 114114 210232 162168 203212 121146 184198 +IMLS459 , 168178 120120 197197 169169 191191 106114 200216 162168 212212 121146 180180 +IMLS460 , 174178 120120 197201 165165 185191 106116 210220 154176 212217 121127 178198 +IMLS461 , 164164 119119 197201 167169 185197 100116 212220 176190 201217 133142 178186 +IMLS462 , 164178 118118 197201 167171 189211 090111 204206 176178 203207 127131 196204 +IMLS463 , 162162 121121 197197 167167 193195 114114 220220 158174 198203 125125 182182 +IMLS464 , 170170 118118 197201 169169 185185 108108 216218 174176 203217 127142 178178 +IMLS465 , 174174 118118 197197 000000 189189 108109 210210 176176 203214 115115 186192 +IMLS466 , 162162 115121 197197 167167 193193 114114 220220 158158 204204 125156 182206 +IMLS467 , 162164 119121 197201 167167 173195 108114 218220 170174 203216 125127 192206 +IMLS468 , 164170 117118 197201 167169 185189 090116 204220 176196 207217 121133 166198 +IMLS469 , 170170 000000 197197 167167 175191 116116 206224 154194 201205 119142 180196 +IMLS470 , 164170 118118 197201 167167 187187 090108 218220 170170 207216 125125 192192 +IMLS471 , 170170 117119 197201 169169 193193 106111 218218 182182 215215 151151 000000 +IMLS472 , 164170 117117 197201 167167 191193 083109 220222 170170 207207 127127 196196 +IMLS473 , 000000 119119 197201 167167 177206 109116 222226 192192 212216 119121 184190 +IMLS474 , 164170 117117 197201 167167 191191 083109 216218 170170 207207 121127 192192 +IMLS475 , 164170 117117 197201 167167 193193 083109 218222 170170 207207 000000 192196 +IMLS476 , 164164 117117 197201 000000 191193 109109 218222 170170 207207 127127 192196 +IMLS477 , 164170 117117 197201 167167 191193 083109 218218 170170 207207 127127 192192 +IMLS478 , 170170 117119 197201 169169 193193 106111 218218 182182 215215 151151 000000 +IMLS479 , 168170 119122 197201 169169 193193 106108 214218 172188 212212 117125 200200 +IMLS480 , 164168 119122 197201 169169 173193 109111 214218 186188 216216 117125 188188 +IMLS481 , 168170 119122 197201 169169 173193 106111 214218 182188 212215 117125 200200 +IMLS482 , 164192 117122 197201 169169 173193 106111 218226 172182 212215 125151 200200 +IMLS483 , 164168 117119 197201 169169 193193 106109 216218 174188 216216 113117 198198 +IMLS484 , 164164 117119 197201 169169 173173 106106 218218 188188 212215 113117 000000 +IMLS203 , 170174 117118 197197 169169 177185 116116 220220 176176 217217 133133 178198 +IMLS205 , 170170 117118 197201 169169 177185 116116 218220 176180 217217 125127 178178 +IMLS206 , 166168 117118 197197 167169 193193 090114 206208 154186 205207 123131 180180 +IMLS207 , 164174 118118 197201 171171 177189 109109 210222 176176 214214 115119 192192 +IMLS208 , 164168 117117 197201 167167 183183 090108 216218 156182 207207 111111 190196 \ No newline at end of file diff --git a/Mypramidata/mp_wild.gen b/Mypramidata/mp_wild.gen new file mode 100644 index 0000000..55e99e0 --- /dev/null +++ b/Mypramidata/mp_wild.gen @@ -0,0 +1,130 @@ +"Magnolia pyramidata, wild- AL, FL, MS, TX- had to rearrange last two samples moved them to FL and AL" +mpy85 +mpy93 +mpy83 +mpy78(2) +mpy81(2) +mpy15 +mpy17 +mpy96b +mpy72(2) +M6D3 +M8D8 +POP +IMLS071 , 178188 120120 197201 167169 183189 103111 212224 178192 203207 119129 202202 +IMLS072 , 157178 118118 197201 167169 181189 092103 218224 178180 207216 123129 204204 +IMLS073 , 162178 117117 197197 169169 181189 103103 218224 178178 202206 127131 000000 +IMLS074 , 184186 117120 197201 167167 181189 090103 218222 176176 205205 123133 178190 +IMLS075 , 180184 117120 197201 167167 181191 090106 222224 190192 205214 125133 190190 +IMLS076 , 166184 119120 197201 167167 191195 090106 218224 184186 204214 119125 190208 +IMLS077 , 164170 117119 197201 165165 181189 090090 216226 178180 201204 119125 190210 +IMLS078 , 170176 118118 197197 167169 000000 103108 208230 178188 206216 121125 178196 +IMLS079 , 164166 118119 197201 167167 187189 106106 226226 178192 205216 119125 182190 +IMLS080 , 164184 120120 197201 167169 189195 103111 222224 184186 206216 113123 192192 +IMLS081 , 174182 120120 197197 169169 181195 106111 210218 178186 205216 125131 186208 +IMLS082 , 162164 118118 197201 167167 187195 085092 218218 168174 203203 125131 184210 +IMLS083 , 162172 118120 197197 167169 189195 092106 206218 164168 205205 125125 184200 +IMLS084 , 162164 118120 197201 167169 187189 085092 218218 164174 202205 125156 184206 +IMLS085 , 164172 118118 197197 169169 189195 092114 218218 168174 203206 125156 184206 +IMLS086 , 180194 117119 197201 167167 179189 094106 210218 174178 205205 125131 192200 +IMLS087 , 164186 121121 197201 167169 175181 106106 218226 168192 205207 121138 196204 +IMLS088 , 164166 117117 197201 167167 191191 106111 216218 170174 206206 123131 198198 +IMLS089 , 162164 120120 197197 167167 189191 090106 222222 184192 205207 127127 178192 +IMLS090 , 170178 119119 000000 169169 189193 106118 220224 164182 204216 117117 178212 +IMLS091 , 166174 118118 197197 167169 185193 090100 214214 178194 202204 151154 172188 +IMLS443 , 160174 118118 197197 167169 173173 106118 218220 180182 206206 125136 176180 +POP +IMLS092 , 168170 117118 197197 167177 173187 109109 220222 174174 202216 125142 178186 +IMLS093 , 164170 117117 197197 171175 173197 109111 196220 170180 203203 119123 168186 +IMLS094 , 164182 117117 197197 167171 175183 103106 220220 168174 198203 121125 168186 +IMLS095 , 168168 118118 197197 169177 175183 103106 206216 170170 198216 127127 176186 +IMLS096 , 164168 117117 197197 169175 173175 109111 196220 174188 203203 123123 176186 +IMLS097 , 170170 117117 197197 171171 183200 106109 206206 170174 203203 125127 168186 +IMLS098 , 164164 121121 197197 167167 189189 109109 220220 174186 203203 121125 168186 +IMLS099 , 164164 121121 197197 167167 183189 106109 220220 186186 198203 121125 168186 +IMLS100 , 166166 118121 197197 167171 183183 109109 198222 174174 198203 127142 176188 +IMLS101 , 138138 000000 000000 000000 163163 000000 202208 000000 000000 123129 164164 +IMLS102 , 138138 000000 000000 000000 163163 000000 204204 000000 000000 000000 178200 +IMLS103 , 166176 117121 197201 167175 187191 103106 206206 170180 201215 121125 188192 +IMLS104 , 166180 117119 197201 167167 173187 090100 214214 170190 205205 115133 000000 +IMLS105 , 166172 117117 197201 167167 173189 090108 216222 170172 203207 113115 204204 +IMLS106 , 164168 117118 197201 167167 191191 083090 210214 170174 207207 121133 196204 +IMLS107 , 164170 117117 197201 167167 191195 109114 224224 170174 203207 111115 194202 +IMLS108 , 172176 117117 197201 167167 195195 090109 206224 156170 203203 115127 186202 +IMLS109 , 164172 117117 197201 167167 187191 083100 208210 170174 205205 117121 192202 +IMLS110 , 172174 119119 197201 167167 173195 083083 202210 170192 205205 125129 192192 +IMLS111 , 166176 117118 197201 167167 189195 083111 204222 170170 202202 111111 202202 +IMLS112 , 168172 118118 197201 167167 193195 111111 210216 170178 207216 111111 202202 +IMLS113 , 172172 118118 197201 167167 193195 083109 220222 178178 207207 111138 202202 +IMLS114 , 168178 117117 197197 167167 187195 108111 210222 174186 201216 131138 184196 +IMLS115 , 164164 117117 197201 167167 193195 083103 204210 178206 201204 125131 188202 +IMLS116 , 166168 117119 197201 167167 193195 090103 204220 200206 207207 111129 192202 +IMLS117 , 172176 117117 197201 167167 191197 109111 000000 182188 201216 117119 166192 +IMLS118 , 164168 117119 197201 167167 173195 083090 210220 170206 201207 111125 196202 +IMLS119 , 164166 117117 197201 167167 173191 083111 210224 170180 207207 129138 198202 +IMLS120 , 168176 117117 197201 167167 173173 108109 204222 170180 207207 113127 190200 +IMLS121 , 168174 117119 197201 167167 173193 108111 204222 170180 203207 127129 186190 +IMLS122 , 164176 119199 197201 167167 173177 106108 206222 170170 207207 125129 190204 +IMLS123 , 164166 117119 197201 167167 179191 106109 206222 170170 207216 125129 190190 +IMLS124 , 164164 117118 197201 167167 173193 109111 218222 170170 207207 125129 190204 +IMLS125 , 168176 117118 197201 167167 177191 106108 218222 174176 203207 113125 190204 +IMLS126 , 164164 117118 197201 167167 179191 090094 204210 176176 207207 113125 188188 +IMLS127 , 164164 117117 197201 167167 189191 090111 204222 170176 207207 129131 192202 +IMLS128 , 164168 117119 197201 167167 173191 109109 210222 170170 201203 125129 188188 +IMLS129 , 168176 119119 197201 167167 173193 109111 204222 170180 207207 129129 190204 +IMLS130 , 162164 117118 197201 167167 191191 094108 210222 170176 201207 125129 188192 +IMLS390 , 162168 117118 197201 167167 173195 108111 204214 176190 207207 129133 198206 +IMLS391 , 164174 117117 197201 167167 173191 106106 204218 156200 201201 129138 190190 +IMLS392 , 176184 117117 197201 167167 173185 111111 214222 170170 207207 125133 198204 +IMLS393 , 168168 117117 197201 167169 187204 090111 216216 174176 203207 115129 190190 +IMLS394 , 164168 117118 197197 167167 187187 090090 216222 174176 203207 111127 200206 +IMLS395 , 164168 117117 197201 167169 187204 090111 224224 176198 207207 125129 190206 +IMLS396 , 170178 117117 197201 167169 191204 083111 216216 170170 207207 115131 190190 +IMLS397 , 174176 118118 197197 167167 187195 090111 204230 176176 201207 123158 200200 +IMLS398 , 166174 117119 197201 167171 187208 090100 206224 170174 207207 111133 202202 +IMLS399 , 164178 117119 197201 167167 187195 090111 204210 156176 203216 000000 200200 +IMLS400 , 174181 117117 197201 167167 175187 090100 216226 170176 201207 000000 204204 +IMLS401 , 162170 117118 195199 165165 187211 088090 210210 170176 201207 129138 202202 +IMLS402 , 174174 117119 197201 167167 187189 090109 204226 170190 207216 111158 186192 +IMLS403 , 164166 119119 197201 169169 189197 083090 204204 170186 207216 123144 202204 +IMLS404 , 174174 117117 197201 167167 173187 090111 204218 156180 207207 111125 190204 +IMLS405 , 164172 117118 197201 167167 179197 090100 218218 186188 202207 123129 168190 +IMLS406 , 164164 117117 197201 167167 177193 090100 218229 188194 203207 119133 186202 +IMLS407 , 164164 119119 197201 167167 197197 090106 216222 190190 198207 119119 190202 +IMLS408 , 166174 119119 197201 169169 189197 106109 210222 170178 207207 119129 168198 +IMLS409 , 166174 119119 197201 167167 187197 106111 220222 170170 207207 111123 198202 +IMLS410 , 164166 117118 197201 167167 197197 090109 216222 170188 198207 119119 190202 +IMLS442 , 162164 117119 197201 167167 187187 108116 214222 172194 202215 133140 190202 +POP +IMLS411 , 168168 117117 197197 167167 189191 090100 196222 176180 203205 123123 188196 +IMLS412 , 172172 118120 197197 167167 181191 103106 196222 189192 203212 119123 178198 +IMLS413 , 166172 117120 197197 167167 191200 106106 220222 174176 204204 119123 188198 +IMLS414 , 166172 121121 197197 169169 181189 106106 222229 176189 203212 119119 188188 +IMLS415 , 168184 118120 197201 167167 177193 106108 216220 180186 203203 121131 188188 +IMLS416 , 164168 119119 197201 167167 185185 085090 210220 182186 203217 119123 170188 +IMLS417 , 168168 119119 197201 167167 191193 085090 216220 180182 204207 125131 184188 +IMLS418 , 168184 117119 197201 167167 191193 094100 216220 180180 203203 123125 184188 +IMLS419 , 184188 119119 197197 167167 173173 090090 210220 180180 203206 121133 184194 +IMLS420 , 168180 119119 197197 167169 173177 090108 210216 182186 203217 121127 188194 +POP +IMLS421 , 170170 117118 197201 169169 177185 103108 222224 176176 217217 119125 178178 +IMLS422 , 170170 118118 197201 169169 185185 103108 224224 186194 217217 125125 178178 +IMLS423 , 170170 118118 197201 169169 185185 116116 218224 176176 217217 119119 178178 +IMLS424 , 170170 117118 197201 169169 185185 108108 220224 176176 217217 121127 178178 +IMLS425 , 170170 117117 197201 169169 185185 108108 220224 176176 217217 000000 178178 +IMLS426 , 170170 117117 197201 169169 185185 108116 224224 176176 217217 119119 178178 +IMLS427 , 170170 117117 197201 169169 177177 116116 224224 176176 203217 121125 178178 +IMLS428 , 170170 117117 197201 169169 177185 108116 218224 176176 203217 121127 178178 +IMLS429 , 172174 117118 197201 167169 185185 103108 220220 176188 217217 121121 178178 +IMLS430 , 170172 117118 197201 167169 185185 103108 218220 176182 217217 121127 178178 +IMLS431 , 170174 117119 197201 167167 185185 103109 218220 186194 203216 121121 178178 +IMLS432 , 160170 117118 197201 167167 185189 103108 218220 176196 217217 127133 178178 +IMLS433 , 160174 117118 197201 167167 177189 106106 218220 176176 217217 121144 178178 +IMLS434 , 174186 117118 197201 167167 185189 108116 218220 176196 203217 121121 178198 +IMLS435 , 170170 117117 197201 167169 185185 108108 218220 186196 203203 121142 178178 +IMLS436 , 170170 117117 197197 167169 185185 116116 218220 176176 217217 133133 178198 +IMLS437 , 170186 117118 197201 167169 177183 106108 218220 186186 203217 121121 178178 +IMLS438 , 160170 117118 197201 167169 177177 106108 218220 176176 203217 121121 178178 +IMLS439 , 170174 117119 197201 167169 177185 103108 220224 186192 203203 127133 178178 +IMLS440 , 160170 117117 197197 169169 185189 106106 216220 176176 203217 121136 178178 +IMLS441 , 160170 118118 197201 167169 185185 108108 218220 176196 217217 121142 178178 \ No newline at end of file diff --git a/Pekmanii/Pe_total.gen b/Pekmanii/Pe_total.gen new file mode 100644 index 0000000..2d05f08 --- /dev/null +++ b/Pekmanii/Pe_total.gen @@ -0,0 +1,311 @@ +"Pseudopheonix ekmanii full dataset, with ex situ lumped as last POP" +pse2_1 +pse3_11 +pse3_33b +pse3_34b +pse3_6 +pse5_2 +pse5_4 +pse5_5 +pse5_6 +pse7_26b +POP +Psek1in_001 , 464464 458458 264264 218218 210221 455455 348348 246246 364364 293293 +Psek1in_002 , 462462 458458 264264 218218 214217 448475 348348 246246 364364 290290 +Psek1in_003 , 464464 458458 264264 218218 179217 455455 348348 246246 364370 290293 +Psek1in_004 , 464464 458458 264264 218218 212212 455455 348348 248248 364370 290290 +Psek1in_005 , 452452 458458 264264 218218 214217 455455 348348 246246 370370 290293 +Psek1in_006 , 462466 458458 264264 218218 210221 455473 348348 246246 364364 000000 +Psek1in_007 , 464464 458458 264264 218218 212212 455455 348348 246246 364364 290293 +Psek1in_008 , 452464 458458 264264 218218 215215 455455 348348 246246 364368 293307 +Psek1in_009 , 452464 458458 264264 218218 210214 456456 348348 246246 364368 293293 +Psek1in_010 , 464464 458458 264264 218218 179217 456475 348348 248248 370370 290293 +Psek1in_011 , 464464 458458 264264 218218 192215 456475 348348 246246 364364 293293 +Psek1in_012 , 464464 458458 264264 218218 217217 456456 348348 246246 364370 290293 +Psek1in_013 , 452464 458458 264264 218218 217217 475475 348348 243248 364370 293293 +Psek1in_014 , 462466 458458 264264 218218 214217 450475 348348 246246 370370 293307 +Psek1in_015 , 452464 458458 264264 218218 210214 451475 348348 243246 368370 290307 +Psek1in_016 , 452466 458458 264264 218218 192221 457475 348348 246246 364364 290290 +Psek1in_017 , 000000 458458 264264 000000 179217 000000 000000 241246 000000 000000 +Psek1in_018 , 462464 458458 264264 218218 210221 456456 348348 248248 370370 293307 +Psek1in_019 , 462462 458458 264264 218218 212212 450475 348348 246246 364370 293293 +Psek1in_020 , 462462 458458 264264 218218 219223 450450 348348 246246 364368 290293 +Psek1in_021 , 000000 000000 264264 000000 000000 000000 000000 000000 000000 000000 +Psek1in_022 , 452452 458458 264264 218218 179212 450475 348348 241246 000000 293293 +Psek1in_023 , 452464 458458 264264 218218 217221 456477 348348 248248 364370 293293 +Psek1in_024 , 452464 458458 264264 218218 214217 475475 348348 248248 368368 293293 +Psek1in_025 , 464466 458458 264264 218218 217221 448452 348348 236246 370370 293293 +Psek1in_026 , 462462 458458 264264 218218 217221 448448 348348 248248 370370 293307 +Psek1in_027 , 000000 000000 000000 000000 000000 000000 000000 000000 000000 000000 +Psek1in_028 , 452466 458458 264264 218218 214217 458475 348348 248248 364370 293293 +Psek1in_029 , 464464 458458 264264 218218 217217 456456 348348 248248 364370 290307 +Psek1in_030 , 452466 458458 264264 218218 179210 448456 348348 241246 370370 290293 +Psek1in_031 , 452464 458458 264264 000000 179179 000000 000000 246246 000000 000000 +Psek1in_032 , 452452 458458 264264 218218 179215 450456 348348 246246 364370 293293 +Psek1in_033 , 462466 452452 264264 218218 210215 456456 348348 241246 370370 290293 +Psek1in_034 , 462464 458458 264264 218218 214217 448456 348348 243252 000000 290293 +Psek1in_035 , 464466 458458 264264 218218 217217 456475 348348 250250 364368 290293 +Psek1in_036 , 452464 458458 264264 218218 179192 456456 348348 250250 368370 290290 +Psek1in_037 , 462464 458458 264264 218218 210214 456473 348348 248248 364368 290293 +Psek1in_038 , 466466 458458 264264 218218 210215 448456 348348 246246 370370 293293 +Psek1in_039 , 452464 458458 264264 218218 214217 448456 348348 241246 364370 290293 +Psek1in_040 , 452464 458458 264264 218218 212212 456475 348348 248248 364370 290290 +Psek1in_041 , 466466 458458 264264 218218 212212 450450 348348 246246 364368 290293 +Psek1in_042 , 462466 458458 264264 218218 208221 448456 348348 246246 370370 290290 +Psek1in_043 , 464466 458458 264264 218218 215215 475475 348348 246246 364364 000000 +Psek1in_044 , 464464 458458 264264 218218 217221 456475 348348 248248 000000 290307 +Psek1in_045 , 464466 458458 264264 218218 192215 448456 348348 246246 364364 293307 +Psek1in_046 , 464464 458458 264264 218218 179221 456475 348348 246246 368370 290290 +Psek1in_047 , 452464 458458 264264 218218 214217 448456 348348 241246 370370 307307 +Psek1in_048 , 462464 458458 264264 218218 212212 450475 348348 241241 364368 290293 +Psek1in_049 , 466466 458458 264264 218218 215215 456456 348348 241243 368370 293307 +Psek1in_050 , 452464 458458 264264 218218 214217 452475 348348 246246 368370 293307 +Psek1in_051 , 464464 458458 264264 218218 212212 450475 348348 246246 364368 000000 +Psek1in_052 , 452452 458458 264264 218218 217221 456456 348348 248248 364370 290290 +Psek1in_053 , 464464 458458 264264 218218 214217 452452 348348 246246 364370 290293 +Psek1in_054 , 452462 458458 264264 218218 219223 450456 348348 248248 364364 290307 +Psek1in_055 , 460466 458458 264264 218218 214217 456463 348348 248248 370370 290290 +Psek1in_056 , 462464 458458 264264 218218 192212 456456 348348 246246 368370 290290 +Psek1in_057 , 452466 458458 264264 000000 179215 456456 348348 246246 368368 290293 +Psek1in_058 , 462462 458458 264264 218218 210210 456456 348348 246246 364370 290290 +Psek1in_059 , 452464 458458 264264 218218 217217 451451 348348 241246 364368 293293 +Psek1in_060 , 464466 458458 264264 218218 214217 449475 348348 241246 364368 000000 +Psek1in_061 , 466466 458458 264264 218218 192212 456477 348348 241246 368370 290290 +Psek1in_062 , 462464 458458 264264 218218 210217 456475 348348 246246 364364 290290 +Psek1in_06 , 464464 458458 264264 218218 179212 456456 348348 241254 368368 290293 +Psek1in_064 , 452464 458458 264264 218218 192215 456475 348348 246246 364370 293307 +Psek1in_065 , 452462 458458 264264 218218 179212 463475 348348 246246 364370 290293 +Psek1in_066 , 464466 458458 264264 218218 210215 450456 348348 248248 368370 290290 +Psek1in_067 , 464466 458458 264264 218218 210215 452456 348348 246246 364368 290293 +Psek1in_068 , 464466 458458 264264 218218 214217 452475 348348 241241 364368 290290 +Psek1in_069 , 452466 458458 264264 218218 208221 456475 348348 241248 364368 290290 +Psek1in_070 , 000000 000000 000000 000000 000000 000000 000000 000000 000000 000000 +Psek1in_071 , 464466 458458 264264 218218 214217 456456 348348 241246 364364 293293 +Psek1in_072 , 452464 458458 264264 218218 192212 452475 348348 248248 370370 293307 +Psek1in_073 , 452464 458458 264264 218218 221221 456456 348348 246246 370370 290293 +Psek1in_074 , 460464 458458 264264 218218 217221 452456 348348 248248 370370 293293 +Psek1in_075 , 464464 458458 264264 218218 212221 449456 348348 246246 368370 307307 +Psek1in_076 , 452464 458458 264264 218218 216216 456456 348348 248248 364370 293293 +Psek1in_077 , 462464 458458 264266 218218 212221 452458 348348 246246 370370 293293 +Psek1in_078 , 452466 458458 264264 218218 217221 456475 348348 241248 368368 290290 +Psek1in_079 , 464464 458458 264264 218218 214217 449456 348348 248248 364370 290293 +Psek1in_080 , 462464 458458 264264 218218 215215 449456 348348 246246 364368 290293 +Psek1in_081 , 452464 458458 264264 218218 217221 456475 348348 241246 368370 290293 +Psek1in_082 , 452452 458458 264264 218218 217221 452456 348348 241250 364370 290307 +Psek1in_083 , 464466 458458 264264 218218 217221 449456 348348 241248 364368 293293 +Psek1in_084 , 464466 458458 264264 218218 179221 451456 348348 246246 364370 290290 +Psek1in_085 , 452464 458458 264264 218218 217221 456456 348348 246246 368370 290290 +Psek1in_086 , 464466 458458 264264 218218 212212 456475 348348 241248 364368 293293 +Psek1in_087 , 464464 458458 264264 218218 192215 449456 348348 246246 370370 293293 +Psek1in_088 , 452464 458458 264264 218218 221221 000000 348348 246246 368370 290293 +Psek1in_089 , 462464 458458 264264 218218 217217 448456 348348 246246 364368 293293 +Psek1in_090 , 462464 458458 264264 218218 218218 452456 348348 241246 364370 293307 +Psek1in_091 , 462464 458458 264264 218218 214217 452456 348348 243248 370370 000000 +Psek1in_092 , 452464 458458 264264 218218 210217 452456 348348 248248 000000 290293 +Psek1in_093 , 462466 458458 264264 218218 210210 456456 348348 241241 370370 290290 +Psek1in_094 , 462464 458458 264264 218218 210215 456475 348348 241284 370370 290293 +Psek1in_095 , 452464 458458 264264 218218 217217 473473 348348 241246 370370 290307 +Psek1in_096 , 452464 458458 264264 218218 214217 456475 348348 241246 364368 290307 +Psek1in_097 , 000000 000000 264264 000000 000000 000000 000000 000000 000000 000000 +Psek1in_098 , 460462 458458 264264 218218 215215 452456 348348 246246 370370 290290 +Psek1in_099 , 464464 458458 264264 218218 214217 455455 348348 225248 000000 290290 +Psek1in_100 , 452464 458458 264264 218218 217221 450475 348348 246246 364368 293293 +Psek1in_101 , 462462 452452 264264 218218 214217 455475 348348 248248 364370 290293 +POP +Psek2in_001 , 000000 458458 264264 218218 212212 475475 348348 248248 368368 290290 +Psek2in_002 , 452452 458458 264264 218218 219223 452452 348348 246246 000000 290290 +Psek2in_003 , 464466 458458 264264 218218 217221 452475 348348 246246 364368 290307 +Psek2in_004 , 462464 458458 264264 218218 221221 450475 348348 246246 368370 290290 +Psek2in_005 , 466466 458458 264264 218218 212212 456456 348348 246246 364370 290290 +Psek2in_006 , 464466 458458 264264 218218 214217 452456 348348 246246 368370 290293 +Psek2in_007 , 452464 458458 264264 218218 192221 452477 348348 248248 364368 290290 +Psek2in_008 , 464464 458458 264264 218218 212221 455477 348348 246246 368370 290290 +Psek2in_009 , 000000 458458 264264 218218 192212 448448 348348 250250 364370 290290 +Psek2in_010 , 462462 458458 264264 218218 219223 450456 348348 248248 364368 290293 +Psek2in_011 , 462466 458458 264264 218218 221221 475475 348348 246246 368370 290290 +Psek2in_012 , 452464 458458 264264 218218 210210 452475 348348 246246 368370 290290 +Psek2in_013 , 462462 458458 264264 218218 212221 452475 348348 246246 364370 290293 +Psek2in_014 , 452462 458458 264264 218218 212221 456475 348348 246246 368370 290290 +Psek2in_015 , 452466 458458 264264 218218 212212 456456 348348 246246 368368 290293 +Psek2in_016 , 452452 458458 264264 218218 221221 456456 348348 241246 368370 290293 +Psek2in_017 , 452464 458458 264264 218218 212212 475475 348348 241248 000000 290290 +Psek2in_018 , 462464 458458 264264 218218 221221 452456 348348 246246 000000 290293 +Psek2in_019 , 464466 458458 264264 218218 221221 456475 348348 246246 368370 290290 +Psek2in_020 , 452462 458458 264264 218218 221221 452475 348348 246246 364370 290290 +Psek2in_021 , 464464 458458 264264 218218 210221 452452 348348 241246 364368 290293 +Psek2in_022 , 464464 458458 264264 218218 208221 473473 348348 246246 366366 290290 +Psek2in_023 , 452466 458458 264264 218218 221221 456475 348348 246246 368370 290293 +Psek2in_024 , 452452 458458 264264 218218 212212 475475 348348 246246 364368 290290 +Psek2in_025 , 452464 458458 264264 218218 192221 456456 348348 238246 368370 290293 +Psek2in_026 , 462464 452452 264264 218218 212221 456475 348348 248248 368370 290293 +Psek2in_027 , 464466 458458 264264 218218 192221 456475 348348 246246 368370 290307 +Psek2in_028 , 464466 458458 264264 218218 210214 452456 348348 246246 368370 290290 +Psek2in_029 , 452452 458458 264264 218218 212221 450475 348348 248248 368368 293293 +Psek2in_030 , 452462 458458 264264 218218 214217 450450 348348 246246 368370 290293 +Psek2in_031 , 462464 458458 264264 218218 221221 452475 348348 246246 368370 290293 +Psek2in_032 , 452462 458458 264264 218218 221221 450450 348348 246246 368370 290290 +Psek2in_033 , 452462 458458 264264 218218 179210 450456 348348 241246 364370 290293 +Psek2in_034 , 452464 452452 264264 218218 214217 456475 348348 241246 364368 290293 +Psek2in_035 , 462464 458458 264264 218218 208208 450450 348348 246246 370370 290290 +Psek2in_036 , 452462 458458 264264 218218 212221 452456 348348 246246 368368 290290 +Psek2in_037 , 452464 458458 264264 218218 214217 475475 348348 246246 368370 290293 +Psek2in_038 , 452452 458458 264264 218218 219223 456475 348348 248248 370370 290293 +Psek2in_039 , 466466 458458 264264 218218 210210 456456 348348 248248 364368 293293 +Psek2in_040 , 462462 458458 264264 218218 000000 452475 348348 246246 370370 290293 +Psek2in_041 , 462464 458458 264264 218218 212221 456456 348348 246246 364368 290290 +Psek2in_042 , 452464 458458 264264 218218 210214 456475 348348 246246 364368 290293 +Psek2in_043 , 452466 458458 264264 218218 221221 452456 348348 246246 368368 290293 +Psek2in_044 , 462462 458458 264264 218218 221221 456475 348348 248248 368370 290293 +Psek2in_045 , 452462 458458 264264 218218 212221 452456 348348 246246 364370 290307 +Psek2in_046 , 462464 458458 264264 218218 212221 452477 348348 246246 364370 290290 +Psek2in_047 , 452464 458458 264264 218218 212221 452475 348348 241246 370370 290293 +Psek2in_048 , 464466 458458 264264 218218 212221 456456 348348 246246 370370 290290 +Psek2in_049 , 452452 458458 264264 218218 221221 452475 348348 246246 368368 290290 +Psek2in_050 , 452452 458458 264264 218218 212221 000000 348348 246246 364368 290293 +Psek2in_051 , 466466 458458 264264 218218 217217 458458 348348 246246 368368 293293 +Psek2in_052 , 452462 458458 264264 218218 212212 450450 348348 243246 364368 290290 +Psek2in_053 , 452466 458458 264264 218218 212221 450450 348348 248248 364370 290290 +Psek2in_054 , 452452 458458 264264 218218 217221 456475 348348 246246 364368 293293 +Psek2in_055 , 452462 458458 264264 218218 212212 456456 348348 246246 368370 290290 +Psek2in_056 , 462466 458458 264264 218218 212221 475475 348348 248248 368368 290290 +Psek2in_057 , 452466 458458 264264 218218 211221 450450 348348 248248 364370 290290 +Psek2in_058 , 452466 458458 264264 218218 210214 475475 348348 246246 364370 290293 +Psek2in_059 , 452466 458458 264264 218218 217221 475475 348348 246246 368370 290307 +Psek2in_060 , 462462 458458 264264 218218 212221 452475 348348 246246 368370 290307 +Psek2in_061 , 452464 458458 264264 218218 210217 456475 348348 248248 368370 290293 +Psek2in_062 , 464466 458458 264264 218218 210221 456456 348348 248248 368370 290290 +Psek2in_063 , 452452 458458 264264 218218 221221 475475 348348 246246 368370 290293 +Psek2in_064 , 462464 458458 264264 218218 212221 456475 348348 250250 364368 290293 +Psek2in_065 , 462464 458458 264264 218218 212221 452456 348348 246246 368370 290307 +Psek2in_066 , 452466 458458 264264 218218 210221 450450 348348 246246 368370 293307 +Psek2in_067 , 452452 458458 264264 218218 210210 452475 348348 246246 364370 290293 +Psek2in_068 , 452464 458458 264264 218218 221221 456475 348348 248248 368370 290293 +Psek2in_069 , 466466 458458 264264 218218 221221 475475 348348 248248 368368 290290 +Psek2in_070 , 462462 458458 264264 218218 212212 451456 348348 246246 368368 290293 +Psek2in_071 , 462466 458458 264264 218218 210215 456456 348348 246246 370370 290307 +Psek2in_072 , 452462 458458 264264 218218 221221 452452 348348 246246 364370 290290 +Psek2in_073 , 466466 458458 264264 218218 212221 451475 348348 241246 364368 290293 +Psek2in_074 , 466466 458458 264264 218218 210217 456475 348348 246246 368368 290293 +Psek2in_075 , 452464 458458 264264 218218 221221 450450 348348 246246 368368 293307 +Psek2in_076 , 452466 458458 264264 218218 208221 452475 348348 246246 364368 293293 +Psek2in_077 , 452464 458458 264264 218218 212212 456456 348348 241241 368370 293293 +Psek2in_078 , 452466 458458 264264 218218 221221 452475 348348 241246 364368 290290 +Psek2in_079 , 452462 458458 264264 218218 217221 456475 348348 248248 368368 293307 +Psek2in_080 , 462464 458458 264264 218218 212212 475475 348348 248248 368368 290290 +Psek2in_081 , 452462 458458 264264 218218 221221 456475 348348 246246 364368 290290 +Psek2in_082 , 466466 452452 264264 218218 217221 450475 348348 246246 368368 290293 +Psek2in_083 , 452462 458458 264264 218218 221221 456475 348348 246246 364368 293293 +Psek2in_084 , 464464 458458 264264 218218 208221 438456 348348 246246 368368 290293 +Psek2in_085 , 452466 458458 264264 218218 221221 475475 348348 246246 368368 290290 +Psek2in_086 , 452462 458458 264264 218218 217221 456475 348348 246246 364364 290290 +Psek2in_087 , 462462 452452 264264 218218 221221 456456 348348 246246 368370 293293 +Psek2in_088 , 452464 458458 264264 218218 221221 450455 348348 246246 368370 290290 +Psek2in_089 , 462466 458458 264264 218218 221221 456475 348348 248248 368370 290293 +Psek2in_090 , 462464 458458 264264 218218 210214 450475 348348 246246 368370 290293 +Psek2in_091 , 462464 458458 264264 218218 208221 452455 348348 246246 370370 290290 +Psek2in_092 , 462464 458458 264264 218218 221221 455475 348348 246246 370370 290293 +Psek2in_093 , 464464 458458 264264 218218 210221 455455 348348 248248 368368 290290 +Psek2in_094 , 000000 458458 264264 218218 208208 475475 348348 246246 368368 293293 +Psek2in_095 , 464466 458458 264264 000000 210215 455475 348348 246246 000000 290293 +Psek2in_096 , 452462 458458 264264 218218 212221 475475 348348 241246 000000 293293 +Psek2in_097 , 452466 458458 264264 218218 212221 456456 348348 241246 368370 290293 +Psek2in_098 , 452466 458458 264264 218218 219223 450450 348348 246246 364364 290290 +Psek2in_099 , 464466 458458 264264 218218 217221 475475 348348 246246 368370 290307 +Psek2in_100 , 452466 458458 264264 218218 221221 452456 348348 246246 368368 290293 +Psek2in_101 , 452452 458458 264264 218218 212212 450455 348348 246246 370370 290290 +Psek2in_102 , 464464 458458 264264 218218 212212 448477 348348 246246 000000 290290 +Psek2in_103 , 452464 458458 264264 218218 212221 455455 348348 248248 370370 290290 +POP +Psek1ex_001 , 464464 458458 264264 218218 210210 452456 348348 246246 368368 290293 +Psek1ex_002 , 464466 458458 264264 218218 210217 452475 348348 246246 368368 290290 +Psek1ex_003 , 464466 458458 264264 218218 208221 452475 348348 246246 368368 290293 +Psek1ex_004 , 452466 458458 264264 218218 210221 456475 348348 248248 368368 290307 +Psek1ex_005 , 464466 458458 264264 218218 208208 452475 348348 246246 368368 290293 +Psek1ex_006 , 464466 458458 264264 218218 210221 452458 348348 246246 368368 290290 +Psek1ex_007 , 452464 458458 264264 218218 208221 450456 348348 246246 368368 000000 +Psek1ex_008 , 464464 458458 264264 218218 208221 452475 348348 246246 368368 290293 +Psek1ex_009 , 464466 458458 264264 218218 210219 452456 348348 246246 368370 290307 +Psek1ex_010 , 466466 458458 264264 218218 210221 456456 348348 246246 368368 290290 +Psek1ex_011 , 464466 458458 264264 218218 208221 452452 348348 246246 368370 290290 +Psek1ex_012 , 452466 458458 264264 218218 210221 452452 348348 246246 368370 290293 +Psek1ex_013 , 466466 458458 264264 218218 208221 456456 348348 246246 368368 293293 +Psek1ex_014 , 466466 458458 264264 218218 210221 456456 348348 246246 364364 293293 +Psek1ex_015 , 464466 458458 264264 218218 208221 458475 348348 248248 364370 290293 +Psek1ex_016 , 464468 458458 264264 218218 221221 452456 348348 246246 368370 290293 +Psek1ex_017 , 464464 452452 264264 218218 210210 452452 348348 246246 370370 293293 +Psek1ex_018 , 452466 458458 264264 218218 221221 452456 348348 246246 368370 290293 +Psek1ex_019 , 452464 458458 264264 218218 210215 452475 348348 246246 368368 290293 +Psek1ex_020 , 464466 458458 264264 218218 210210 452456 348348 248248 364370 290290 +Psek1ex_021 , 464464 458458 264264 218218 210214 452456 348348 246246 368370 290290 +Psek1ex_022 , 462466 458458 264264 218218 217221 456475 348348 246246 364368 290293 +Psek1ex_023 , 464466 458458 264264 218218 208208 452456 348348 246246 364368 290290 +Psek1ex_024 , 466466 458458 264264 218218 210210 452475 348348 248248 368368 293293 +Psek1ex_025 , 464464 458458 264264 218218 217221 452456 348348 246246 370370 290290 +Psek1ex_026 , 464464 458458 264264 218218 210210 452456 348348 246246 368368 290290 +Psek1ex_027 , 464464 458458 264264 218218 210214 452452 348348 246246 368368 290293 +Psek1ex_028 , 462466 458458 264264 218218 208221 452475 348348 246246 364370 290293 +Psek1ex_029 , 452464 458458 264264 218218 208221 456475 348348 246246 364368 290293 +Psek1ex_030 , 452452 458458 264264 218218 221221 456475 348348 246246 368370 293293 +Psek1ex_031 , 452466 458458 264264 218218 208208 456475 348348 246246 368370 293293 +Psek1ex_032 , 452466 458458 264264 218218 208221 456475 348348 246246 368368 290290 +Psek2ex_001 , 452466 458458 264264 218218 221221 000000 348348 246246 364370 290293 +Psek2ex_002 , 462466 458458 264264 218218 221221 452456 348348 248248 368370 290290 +Psek2ex_003 , 452464 458458 264264 218218 210210 452452 348348 246246 368370 293293 +Psek2ex_004 , 466466 458458 264264 218218 219223 456475 348348 248248 364368 290293 +Psek2ex_005 , 464466 458458 264264 218218 208208 452452 348348 246246 370372 293293 +Psek2ex_006 , 462466 458458 264264 218218 217221 452456 348348 241246 364368 290290 +Psek2ex_007 , 452466 458458 264264 218218 210221 452456 348348 248248 364368 290293 +Psek2ex_008 , 462466 458458 264264 218218 212221 452456 348348 246246 364368 290290 +Psek2ex_009 , 452464 458458 264264 218218 210217 450450 348348 246246 368368 293293 +Psek2ex_010 , 452462 458458 264264 218218 212212 456475 348348 241246 370370 293293 +Psek2ex_011 , 452462 458458 264264 218218 208221 456475 348348 246246 368370 290290 +Psek2ex_012 , 464466 458458 264264 218218 221221 452475 348348 246246 368370 290293 +Psek2ex_013 , 464466 458458 264264 218218 219223 456456 348348 246246 368368 290293 +Psek2ex_014 , 464466 458458 264264 218218 221221 475475 348348 234246 370370 290293 +Psek2ex_015 , 452452 458458 264264 218218 221221 456475 348348 246246 364370 293293 +Psek2ex_016 , 452452 458458 264264 218218 221221 456475 348348 241246 364370 290307 +Psek2ex_017 , 450450 458458 264264 218218 212221 475475 348348 246246 370370 290290 +Psekex_001 , 452464 458458 264264 218218 192212 456475 348348 246246 364368 290293 +Psekex_002 , 452464 458458 264264 218218 212223 450475 348348 241241 364368 290293 +Psekex_003 , 452466 458458 264264 218218 179212 475475 348348 248248 364368 290293 +Psekex_004 , 452462 458458 264264 218218 179217 450450 348348 246246 368370 290293 +Psekex_005 , 452466 458458 264264 218218 214217 450475 348348 241246 364368 293293 +Psekex_006 , 452464 458458 264264 218218 212212 450456 348348 241246 368370 290293 +Psekex_007 , 452466 458458 264264 218218 179179 450475 348348 241246 364364 293293 +Psekex_008 , 452466 458458 264264 218218 179179 450456 348348 246246 364368 293307 +Psekex_009 , 452466 458458 264264 218218 214217 450450 348348 246246 364368 290293 +Psekex_010 , 452464 458458 264264 218218 179217 450456 348348 241246 368370 290293 +Psekex_011 , 452464 458458 264264 218218 179179 456475 348348 241246 364364 293307 +Psekex_012 , 452464 458458 264264 218218 179215 456475 348348 241246 368370 293293 +Psekex_013 , 452466 458458 264264 218218 179221 456475 348348 246246 364368 293293 +Psekex_014 , 452466 458458 264264 218218 214217 475475 348348 241248 364368 293293 +Psekex_015 , 452464 458458 264264 218218 212221 450456 348348 246246 364368 293293 +Psekex_016 , 452464 458458 264264 218218 178221 456475 348348 246246 364368 293293 +Psekex_017 , 452466 458458 264264 218218 179212 450456 348348 241248 364368 293307 +Psekex_018 , 452464 458458 264264 218218 179210 456475 348348 246246 364368 290293 +Psekex_019 , 452464 458458 264264 218218 212221 450450 348348 241246 364368 293293 +Psekex_020 , 452464 458458 264264 218218 212212 456475 348348 241246 368370 293293 +Psekex_021 , 452464 458458 264264 218218 212212 456473 348348 241246 364368 290293 +Psekex_022 , 452462 458458 264264 218218 210214 450456 348348 241246 368370 293293 +Psekex_023 , 452464 458458 264264 218218 212221 456475 348348 241248 364368 293293 +Psekex_024 , 452466 458458 264264 218218 179215 000000 348348 241246 364368 293293 +Psekex_025 , 452462 458458 264264 218218 214217 450450 348348 246246 368368 293293 +Psekex_026 , 452462 458458 264264 218218 214217 450456 348348 246246 364364 290293 +Psekex_027 , 462462 458458 264264 218218 221221 456475 348348 241246 364368 293293 +Psekex_028 , 464464 458458 264264 218218 214217 450475 348348 248248 364368 293307 +Psekex_029 , 462464 458458 264264 218218 215215 449452 348348 246246 364368 293293 +Psekex_030 , 462466 458458 264264 218218 179215 456475 348348 248248 368370 293293 +Psekex_031 , 464464 458458 264264 218218 214217 449449 348348 248248 368370 293307 +Psekex_032 , 452464 458458 264264 218218 214217 449475 348348 248248 364370 290293 +Psekex_033 , 462464 458458 264264 218218 215215 448475 348348 248248 368370 293293 +Psekex_034 , 464464 458458 264264 218218 179221 448477 348348 246246 364370 293293 +Psekex_035 , 464464 458458 264264 218218 221221 449456 348348 246246 368370 293293 +Psekex_036 , 464466 458458 264264 218218 179221 477477 348348 246246 364364 293293 +Psekex_037 , 464466 458458 264264 218218 217221 456475 348348 246246 364368 293293 +Psekex_038 , 464466 458458 264264 218218 179221 456475 348348 246246 364368 293293 +Psekex_039 , 462464 458458 264264 218218 212221 452456 348348 246246 364368 290293 +Psekex_040 , 464466 458458 264264 218218 192221 452477 348348 241246 364364 290293 +Psekex_041 , 466466 458458 264264 218218 179179 456477 348348 246246 364364 293293 +Psekex_042 , 464464 458458 264264 218218 179221 456477 348348 246246 370370 293293 +Psekex_043 , 464464 458458 264264 218218 179221 477477 348348 246246 364364 293293 +Psekex_044 , 452464 458458 264264 218218 221221 452475 348348 246246 368370 290293 diff --git a/Pekmanii/Pe_wild.gen b/Pekmanii/Pe_wild.gen new file mode 100644 index 0000000..476a672 --- /dev/null +++ b/Pekmanii/Pe_wild.gen @@ -0,0 +1,217 @@ +"Pseudopheonix ekmanii full dataset, subset to only the wild (in) populations" +pse2_1 +pse3_11 +pse3_33b +pse3_34b +pse3_6 +pse5_2 +pse5_4 +pse5_5 +pse5_6 +pse7_26b +POP +Psek1in_001 , 464464 458458 264264 218218 210221 455455 348348 246246 364364 293293 +Psek1in_002 , 462462 458458 264264 218218 214217 448475 348348 246246 364364 290290 +Psek1in_003 , 464464 458458 264264 218218 179217 455455 348348 246246 364370 290293 +Psek1in_004 , 464464 458458 264264 218218 212212 455455 348348 248248 364370 290290 +Psek1in_005 , 452452 458458 264264 218218 214217 455455 348348 246246 370370 290293 +Psek1in_006 , 462466 458458 264264 218218 210221 455473 348348 246246 364364 000000 +Psek1in_007 , 464464 458458 264264 218218 212212 455455 348348 246246 364364 290293 +Psek1in_008 , 452464 458458 264264 218218 215215 455455 348348 246246 364368 293307 +Psek1in_009 , 452464 458458 264264 218218 210214 456456 348348 246246 364368 293293 +Psek1in_010 , 464464 458458 264264 218218 179217 456475 348348 248248 370370 290293 +Psek1in_011 , 464464 458458 264264 218218 192215 456475 348348 246246 364364 293293 +Psek1in_012 , 464464 458458 264264 218218 217217 456456 348348 246246 364370 290293 +Psek1in_013 , 452464 458458 264264 218218 217217 475475 348348 243248 364370 293293 +Psek1in_014 , 462466 458458 264264 218218 214217 450475 348348 246246 370370 293307 +Psek1in_015 , 452464 458458 264264 218218 210214 451475 348348 243246 368370 290307 +Psek1in_016 , 452466 458458 264264 218218 192221 457475 348348 246246 364364 290290 +Psek1in_017 , 000000 458458 264264 000000 179217 000000 000000 241246 000000 000000 +Psek1in_018 , 462464 458458 264264 218218 210221 456456 348348 248248 370370 293307 +Psek1in_019 , 462462 458458 264264 218218 212212 450475 348348 246246 364370 293293 +Psek1in_020 , 462462 458458 264264 218218 219223 450450 348348 246246 364368 290293 +Psek1in_021 , 000000 000000 264264 000000 000000 000000 000000 000000 000000 000000 +Psek1in_022 , 452452 458458 264264 218218 179212 450475 348348 241246 000000 293293 +Psek1in_023 , 452464 458458 264264 218218 217221 456477 348348 248248 364370 293293 +Psek1in_024 , 452464 458458 264264 218218 214217 475475 348348 248248 368368 293293 +Psek1in_025 , 464466 458458 264264 218218 217221 448452 348348 236246 370370 293293 +Psek1in_026 , 462462 458458 264264 218218 217221 448448 348348 248248 370370 293307 +Psek1in_027 , 000000 000000 000000 000000 000000 000000 000000 000000 000000 000000 +Psek1in_028 , 452466 458458 264264 218218 214217 458475 348348 248248 364370 293293 +Psek1in_029 , 464464 458458 264264 218218 217217 456456 348348 248248 364370 290307 +Psek1in_030 , 452466 458458 264264 218218 179210 448456 348348 241246 370370 290293 +Psek1in_031 , 452464 458458 264264 000000 179179 000000 000000 246246 000000 000000 +Psek1in_032 , 452452 458458 264264 218218 179215 450456 348348 246246 364370 293293 +Psek1in_033 , 462466 452452 264264 218218 210215 456456 348348 241246 370370 290293 +Psek1in_034 , 462464 458458 264264 218218 214217 448456 348348 243252 000000 290293 +Psek1in_035 , 464466 458458 264264 218218 217217 456475 348348 250250 364368 290293 +Psek1in_036 , 452464 458458 264264 218218 179192 456456 348348 250250 368370 290290 +Psek1in_037 , 462464 458458 264264 218218 210214 456473 348348 248248 364368 290293 +Psek1in_038 , 466466 458458 264264 218218 210215 448456 348348 246246 370370 293293 +Psek1in_039 , 452464 458458 264264 218218 214217 448456 348348 241246 364370 290293 +Psek1in_040 , 452464 458458 264264 218218 212212 456475 348348 248248 364370 290290 +Psek1in_041 , 466466 458458 264264 218218 212212 450450 348348 246246 364368 290293 +Psek1in_042 , 462466 458458 264264 218218 208221 448456 348348 246246 370370 290290 +Psek1in_043 , 464466 458458 264264 218218 215215 475475 348348 246246 364364 000000 +Psek1in_044 , 464464 458458 264264 218218 217221 456475 348348 248248 000000 290307 +Psek1in_045 , 464466 458458 264264 218218 192215 448456 348348 246246 364364 293307 +Psek1in_046 , 464464 458458 264264 218218 179221 456475 348348 246246 368370 290290 +Psek1in_047 , 452464 458458 264264 218218 214217 448456 348348 241246 370370 307307 +Psek1in_048 , 462464 458458 264264 218218 212212 450475 348348 241241 364368 290293 +Psek1in_049 , 466466 458458 264264 218218 215215 456456 348348 241243 368370 293307 +Psek1in_050 , 452464 458458 264264 218218 214217 452475 348348 246246 368370 293307 +Psek1in_051 , 464464 458458 264264 218218 212212 450475 348348 246246 364368 000000 +Psek1in_052 , 452452 458458 264264 218218 217221 456456 348348 248248 364370 290290 +Psek1in_053 , 464464 458458 264264 218218 214217 452452 348348 246246 364370 290293 +Psek1in_054 , 452462 458458 264264 218218 219223 450456 348348 248248 364364 290307 +Psek1in_055 , 460466 458458 264264 218218 214217 456463 348348 248248 370370 290290 +Psek1in_056 , 462464 458458 264264 218218 192212 456456 348348 246246 368370 290290 +Psek1in_057 , 452466 458458 264264 000000 179215 456456 348348 246246 368368 290293 +Psek1in_058 , 462462 458458 264264 218218 210210 456456 348348 246246 364370 290290 +Psek1in_059 , 452464 458458 264264 218218 217217 451451 348348 241246 364368 293293 +Psek1in_060 , 464466 458458 264264 218218 214217 449475 348348 241246 364368 000000 +Psek1in_061 , 466466 458458 264264 218218 192212 456477 348348 241246 368370 290290 +Psek1in_062 , 462464 458458 264264 218218 210217 456475 348348 246246 364364 290290 +Psek1in_06 , 464464 458458 264264 218218 179212 456456 348348 241254 368368 290293 +Psek1in_064 , 452464 458458 264264 218218 192215 456475 348348 246246 364370 293307 +Psek1in_065 , 452462 458458 264264 218218 179212 463475 348348 246246 364370 290293 +Psek1in_066 , 464466 458458 264264 218218 210215 450456 348348 248248 368370 290290 +Psek1in_067 , 464466 458458 264264 218218 210215 452456 348348 246246 364368 290293 +Psek1in_068 , 464466 458458 264264 218218 214217 452475 348348 241241 364368 290290 +Psek1in_069 , 452466 458458 264264 218218 208221 456475 348348 241248 364368 290290 +Psek1in_070 , 000000 000000 000000 000000 000000 000000 000000 000000 000000 000000 +Psek1in_071 , 464466 458458 264264 218218 214217 456456 348348 241246 364364 293293 +Psek1in_072 , 452464 458458 264264 218218 192212 452475 348348 248248 370370 293307 +Psek1in_073 , 452464 458458 264264 218218 221221 456456 348348 246246 370370 290293 +Psek1in_074 , 460464 458458 264264 218218 217221 452456 348348 248248 370370 293293 +Psek1in_075 , 464464 458458 264264 218218 212221 449456 348348 246246 368370 307307 +Psek1in_076 , 452464 458458 264264 218218 216216 456456 348348 248248 364370 293293 +Psek1in_077 , 462464 458458 264266 218218 212221 452458 348348 246246 370370 293293 +Psek1in_078 , 452466 458458 264264 218218 217221 456475 348348 241248 368368 290290 +Psek1in_079 , 464464 458458 264264 218218 214217 449456 348348 248248 364370 290293 +Psek1in_080 , 462464 458458 264264 218218 215215 449456 348348 246246 364368 290293 +Psek1in_081 , 452464 458458 264264 218218 217221 456475 348348 241246 368370 290293 +Psek1in_082 , 452452 458458 264264 218218 217221 452456 348348 241250 364370 290307 +Psek1in_083 , 464466 458458 264264 218218 217221 449456 348348 241248 364368 293293 +Psek1in_084 , 464466 458458 264264 218218 179221 451456 348348 246246 364370 290290 +Psek1in_085 , 452464 458458 264264 218218 217221 456456 348348 246246 368370 290290 +Psek1in_086 , 464466 458458 264264 218218 212212 456475 348348 241248 364368 293293 +Psek1in_087 , 464464 458458 264264 218218 192215 449456 348348 246246 370370 293293 +Psek1in_088 , 452464 458458 264264 218218 221221 000000 348348 246246 368370 290293 +Psek1in_089 , 462464 458458 264264 218218 217217 448456 348348 246246 364368 293293 +Psek1in_090 , 462464 458458 264264 218218 218218 452456 348348 241246 364370 293307 +Psek1in_091 , 462464 458458 264264 218218 214217 452456 348348 243248 370370 000000 +Psek1in_092 , 452464 458458 264264 218218 210217 452456 348348 248248 000000 290293 +Psek1in_093 , 462466 458458 264264 218218 210210 456456 348348 241241 370370 290290 +Psek1in_094 , 462464 458458 264264 218218 210215 456475 348348 241284 370370 290293 +Psek1in_095 , 452464 458458 264264 218218 217217 473473 348348 241246 370370 290307 +Psek1in_096 , 452464 458458 264264 218218 214217 456475 348348 241246 364368 290307 +Psek1in_097 , 000000 000000 264264 000000 000000 000000 000000 000000 000000 000000 +Psek1in_098 , 460462 458458 264264 218218 215215 452456 348348 246246 370370 290290 +Psek1in_099 , 464464 458458 264264 218218 214217 455455 348348 225248 000000 290290 +Psek1in_100 , 452464 458458 264264 218218 217221 450475 348348 246246 364368 293293 +Psek1in_101 , 462462 452452 264264 218218 214217 455475 348348 248248 364370 290293 +POP +Psek2in_001 , 000000 458458 264264 218218 212212 475475 348348 248248 368368 290290 +Psek2in_002 , 452452 458458 264264 218218 219223 452452 348348 246246 000000 290290 +Psek2in_003 , 464466 458458 264264 218218 217221 452475 348348 246246 364368 290307 +Psek2in_004 , 462464 458458 264264 218218 221221 450475 348348 246246 368370 290290 +Psek2in_005 , 466466 458458 264264 218218 212212 456456 348348 246246 364370 290290 +Psek2in_006 , 464466 458458 264264 218218 214217 452456 348348 246246 368370 290293 +Psek2in_007 , 452464 458458 264264 218218 192221 452477 348348 248248 364368 290290 +Psek2in_008 , 464464 458458 264264 218218 212221 455477 348348 246246 368370 290290 +Psek2in_009 , 000000 458458 264264 218218 192212 448448 348348 250250 364370 290290 +Psek2in_010 , 462462 458458 264264 218218 219223 450456 348348 248248 364368 290293 +Psek2in_011 , 462466 458458 264264 218218 221221 475475 348348 246246 368370 290290 +Psek2in_012 , 452464 458458 264264 218218 210210 452475 348348 246246 368370 290290 +Psek2in_013 , 462462 458458 264264 218218 212221 452475 348348 246246 364370 290293 +Psek2in_014 , 452462 458458 264264 218218 212221 456475 348348 246246 368370 290290 +Psek2in_015 , 452466 458458 264264 218218 212212 456456 348348 246246 368368 290293 +Psek2in_016 , 452452 458458 264264 218218 221221 456456 348348 241246 368370 290293 +Psek2in_017 , 452464 458458 264264 218218 212212 475475 348348 241248 000000 290290 +Psek2in_018 , 462464 458458 264264 218218 221221 452456 348348 246246 000000 290293 +Psek2in_019 , 464466 458458 264264 218218 221221 456475 348348 246246 368370 290290 +Psek2in_020 , 452462 458458 264264 218218 221221 452475 348348 246246 364370 290290 +Psek2in_021 , 464464 458458 264264 218218 210221 452452 348348 241246 364368 290293 +Psek2in_022 , 464464 458458 264264 218218 208221 473473 348348 246246 366366 290290 +Psek2in_023 , 452466 458458 264264 218218 221221 456475 348348 246246 368370 290293 +Psek2in_024 , 452452 458458 264264 218218 212212 475475 348348 246246 364368 290290 +Psek2in_025 , 452464 458458 264264 218218 192221 456456 348348 238246 368370 290293 +Psek2in_026 , 462464 452452 264264 218218 212221 456475 348348 248248 368370 290293 +Psek2in_027 , 464466 458458 264264 218218 192221 456475 348348 246246 368370 290307 +Psek2in_028 , 464466 458458 264264 218218 210214 452456 348348 246246 368370 290290 +Psek2in_029 , 452452 458458 264264 218218 212221 450475 348348 248248 368368 293293 +Psek2in_030 , 452462 458458 264264 218218 214217 450450 348348 246246 368370 290293 +Psek2in_031 , 462464 458458 264264 218218 221221 452475 348348 246246 368370 290293 +Psek2in_032 , 452462 458458 264264 218218 221221 450450 348348 246246 368370 290290 +Psek2in_033 , 452462 458458 264264 218218 179210 450456 348348 241246 364370 290293 +Psek2in_034 , 452464 452452 264264 218218 214217 456475 348348 241246 364368 290293 +Psek2in_035 , 462464 458458 264264 218218 208208 450450 348348 246246 370370 290290 +Psek2in_036 , 452462 458458 264264 218218 212221 452456 348348 246246 368368 290290 +Psek2in_037 , 452464 458458 264264 218218 214217 475475 348348 246246 368370 290293 +Psek2in_038 , 452452 458458 264264 218218 219223 456475 348348 248248 370370 290293 +Psek2in_039 , 466466 458458 264264 218218 210210 456456 348348 248248 364368 293293 +Psek2in_040 , 462462 458458 264264 218218 000000 452475 348348 246246 370370 290293 +Psek2in_041 , 462464 458458 264264 218218 212221 456456 348348 246246 364368 290290 +Psek2in_042 , 452464 458458 264264 218218 210214 456475 348348 246246 364368 290293 +Psek2in_043 , 452466 458458 264264 218218 221221 452456 348348 246246 368368 290293 +Psek2in_044 , 462462 458458 264264 218218 221221 456475 348348 248248 368370 290293 +Psek2in_045 , 452462 458458 264264 218218 212221 452456 348348 246246 364370 290307 +Psek2in_046 , 462464 458458 264264 218218 212221 452477 348348 246246 364370 290290 +Psek2in_047 , 452464 458458 264264 218218 212221 452475 348348 241246 370370 290293 +Psek2in_048 , 464466 458458 264264 218218 212221 456456 348348 246246 370370 290290 +Psek2in_049 , 452452 458458 264264 218218 221221 452475 348348 246246 368368 290290 +Psek2in_050 , 452452 458458 264264 218218 212221 000000 348348 246246 364368 290293 +Psek2in_051 , 466466 458458 264264 218218 217217 458458 348348 246246 368368 293293 +Psek2in_052 , 452462 458458 264264 218218 212212 450450 348348 243246 364368 290290 +Psek2in_053 , 452466 458458 264264 218218 212221 450450 348348 248248 364370 290290 +Psek2in_054 , 452452 458458 264264 218218 217221 456475 348348 246246 364368 293293 +Psek2in_055 , 452462 458458 264264 218218 212212 456456 348348 246246 368370 290290 +Psek2in_056 , 462466 458458 264264 218218 212221 475475 348348 248248 368368 290290 +Psek2in_057 , 452466 458458 264264 218218 211221 450450 348348 248248 364370 290290 +Psek2in_058 , 452466 458458 264264 218218 210214 475475 348348 246246 364370 290293 +Psek2in_059 , 452466 458458 264264 218218 217221 475475 348348 246246 368370 290307 +Psek2in_060 , 462462 458458 264264 218218 212221 452475 348348 246246 368370 290307 +Psek2in_061 , 452464 458458 264264 218218 210217 456475 348348 248248 368370 290293 +Psek2in_062 , 464466 458458 264264 218218 210221 456456 348348 248248 368370 290290 +Psek2in_063 , 452452 458458 264264 218218 221221 475475 348348 246246 368370 290293 +Psek2in_064 , 462464 458458 264264 218218 212221 456475 348348 250250 364368 290293 +Psek2in_065 , 462464 458458 264264 218218 212221 452456 348348 246246 368370 290307 +Psek2in_066 , 452466 458458 264264 218218 210221 450450 348348 246246 368370 293307 +Psek2in_067 , 452452 458458 264264 218218 210210 452475 348348 246246 364370 290293 +Psek2in_068 , 452464 458458 264264 218218 221221 456475 348348 248248 368370 290293 +Psek2in_069 , 466466 458458 264264 218218 221221 475475 348348 248248 368368 290290 +Psek2in_070 , 462462 458458 264264 218218 212212 451456 348348 246246 368368 290293 +Psek2in_071 , 462466 458458 264264 218218 210215 456456 348348 246246 370370 290307 +Psek2in_072 , 452462 458458 264264 218218 221221 452452 348348 246246 364370 290290 +Psek2in_073 , 466466 458458 264264 218218 212221 451475 348348 241246 364368 290293 +Psek2in_074 , 466466 458458 264264 218218 210217 456475 348348 246246 368368 290293 +Psek2in_075 , 452464 458458 264264 218218 221221 450450 348348 246246 368368 293307 +Psek2in_076 , 452466 458458 264264 218218 208221 452475 348348 246246 364368 293293 +Psek2in_077 , 452464 458458 264264 218218 212212 456456 348348 241241 368370 293293 +Psek2in_078 , 452466 458458 264264 218218 221221 452475 348348 241246 364368 290290 +Psek2in_079 , 452462 458458 264264 218218 217221 456475 348348 248248 368368 293307 +Psek2in_080 , 462464 458458 264264 218218 212212 475475 348348 248248 368368 290290 +Psek2in_081 , 452462 458458 264264 218218 221221 456475 348348 246246 364368 290290 +Psek2in_082 , 466466 452452 264264 218218 217221 450475 348348 246246 368368 290293 +Psek2in_083 , 452462 458458 264264 218218 221221 456475 348348 246246 364368 293293 +Psek2in_084 , 464464 458458 264264 218218 208221 438456 348348 246246 368368 290293 +Psek2in_085 , 452466 458458 264264 218218 221221 475475 348348 246246 368368 290290 +Psek2in_086 , 452462 458458 264264 218218 217221 456475 348348 246246 364364 290290 +Psek2in_087 , 462462 452452 264264 218218 221221 456456 348348 246246 368370 293293 +Psek2in_088 , 452464 458458 264264 218218 221221 450455 348348 246246 368370 290290 +Psek2in_089 , 462466 458458 264264 218218 221221 456475 348348 248248 368370 290293 +Psek2in_090 , 462464 458458 264264 218218 210214 450475 348348 246246 368370 290293 +Psek2in_091 , 462464 458458 264264 218218 208221 452455 348348 246246 370370 290290 +Psek2in_092 , 462464 458458 264264 218218 221221 455475 348348 246246 370370 290293 +Psek2in_093 , 464464 458458 264264 218218 210221 455455 348348 248248 368368 290290 +Psek2in_094 , 000000 458458 264264 218218 208208 475475 348348 246246 368368 293293 +Psek2in_095 , 464466 458458 264264 000000 210215 455475 348348 246246 000000 290293 +Psek2in_096 , 452462 458458 264264 218218 212221 475475 348348 241246 000000 293293 +Psek2in_097 , 452466 458458 264264 218218 212221 456456 348348 241246 368370 290293 +Psek2in_098 , 452466 458458 264264 218218 219223 450450 348348 246246 364364 290290 +Psek2in_099 , 464466 458458 264264 218218 217221 475475 348348 246246 368370 290307 +Psek2in_100 , 452466 458458 264264 218218 221221 452456 348348 246246 368368 290293 +Psek2in_101 , 452452 458458 264264 218218 212212 450455 348348 246246 370370 290290 +Psek2in_102 , 464464 458458 264264 218218 212212 448477 348348 246246 000000 290290 +Psek2in_103 , 452464 458458 264264 218218 212221 455455 348348 248248 370370 290290 \ No newline at end of file diff --git a/Qboyntonii/Qb_total.gen b/Qboyntonii/Qb_total.gen new file mode 100644 index 0000000..4e9fc4f --- /dev/null +++ b/Qboyntonii/Qb_total.gen @@ -0,0 +1,342 @@ +"Qubo Wild with 6, 8, and 9 MERGED + ex situ as last population" +QrZAG20 +QpZAG110 +QS00314 +QpZAG9 +QS01904 +QS03297 +MSQ4 +QS00562 +QrZAG87 +POP +IMLS1.2_MP1_IMLS001_A01 , 158169 201201 175175 247265 141147 214216 202249 223223 095095 +IMLS1.2_MP1_IMLS002_A02 , 161161 201207 175210 247253 137141 214214 197247 223225 095095 +POP +IMLS1.2_MP1_IMLS003_A03 , 161161 201207 175175 233269 139141 216216 200208 215225 095095 +IMLS1.2_MP1_IMLS004_A04 , 161161 201201 175178 243245 137141 214214 197200 223223 095095 +IMLS1.2_MP1_IMLS021_B11 , 161169 207207 175181 247269 137137 216218 202217 223223 095095 +IMLS1.2_MP1_IMLS022_B12 , 161161 207207 172178 249269 137141 216216 204217 223223 095095 +IMLS1.2_MP1_IMLS023_C01 , 161161 207207 172178 249269 137141 216216 204217 223223 095095 +IMLS1.2_MP1_IMLS024_C02 , 158161 201201 175175 235245 137137 214214 197197 223223 095095 +IMLS1.2_MP1_IMLS025_C03 , 158161 205215 169172 245265 139147 216216 202202 223223 095095 +IMLS1.2_MP1_IMLS026_C04 , 161169 205207 175178 000000 000000 214216 212212 223225 095095 +IMLS1.2_MP1_IMLS027_C05 , 158169 201213 175178 247249 137139 214216 199199 223223 095095 +IMLS1.2_MP1_IMLS028_C06 , 158169 201213 175178 247249 137139 214216 199199 223223 095095 +IMLS1.2_MP1_IMLS029_C07 , 156161 201201 175181 245247 137137 214226 201201 223223 095095 +IMLS1.2_MP1_IMLS030_C08 , 161161 201205 172175 247265 137139 216230 202246 223223 095095 +IMLS1.2_MP1_IMLS031_C09 , 161161 201201 175178 243245 139141 216216 198214 223223 095095 +IMLS1.2_MP1_IMLS032_C10 , 161173 201205 175175 245257 141141 216216 198207 223223 095095 +POP +IMLS1.2_MP1_IMLS005_A05 , 161163 207207 175175 269271 137137 216216 199203 223225 095095 +IMLS1.2_MP1_IMLS006_A06 , 164167 201201 175175 235265 137137 216216 212232 223223 095095 +IMLS1.2_MP1_IMLS033_C11 , 161163 201201 169181 231245 137137 216216 208208 223223 095095 +IMLS1.2_MP1_IMLS034_C12 , 161161 201207 175175 249253 137139 214226 198218 223223 095095 +IMLS1.2_MP1_IMLS035_D01 , 161163 205207 175178 249265 137137 214217 203215 223223 095095 +IMLS1.2_MP1_IMLS036_D02 , 156161 201207 175178 000000 137137 216216 201203 223225 095095 +IMLS1.2_MP1_IMLS037_D03 , 156164 201201 175181 000000 137137 216216 232236 188225 095095 +IMLS1.2_MP1_IMLS038_D04 , 161161 207207 175175 235253 137137 000000 197214 223223 095095 +IMLS1.2_MP1_IMLS039_D05 , 154161 201205 175175 245245 147147 216230 199204 223223 095095 +IMLS1.2_MP1_IMLS041_D07 , 158158 201201 175181 245245 141147 214214 197203 225225 095095 +IMLS1.2_MP1_IMLS042_D08 , 158158 201201 175181 245245 141147 214214 197203 225225 095095 +IMLS1.2_MP1_IMLS043_D09 , 161164 201205 175178 000000 137141 216216 210232 223225 095095 +IMLS1.2_MP1_IMLS044_D10 , 161164 201205 175178 000000 137141 216216 210232 223225 095095 +IMLS1.2_MP1_IMLS045_D11 , 161161 201207 169184 235249 137141 214216 197212 223223 095095 +IMLS1.2_MP1_IMLS046_D12 , 161161 201201 175175 253263 137137 216216 206227 223227 095095 +IMLS1.2_MP1_IMLS047_E01 , 161169 201205 178210 251269 141147 214216 199207 223223 095095 +IMLS1.2_MP1_IMLS048_E02 , 161163 201205 175181 263263 139155 214217 000000 223223 095095 +POP +IMLS1.2_MP1_IMLS007_B01 , 158161 201207 178184 000000 137137 216216 195197 223223 095095 +IMLS1.2_MP1_IMLS008_B02 , 161164 203207 178178 251251 137137 216230 197199 223223 095095 +IMLS1.2_MP1_IMLS049_E03 , 156161 201207 178178 249271 137137 000000 208214 223223 095095 +IMLS1.2_MP1_IMLS050_E04 , 161167 201203 175178 245249 141141 214216 214220 223223 095095 +IMLS1.2_MP1_IMLS051_E05 , 161173 201207 175175 251259 137139 214214 195195 225225 095095 +IMLS1.2_MP1_IMLS052_E06 , 161169 201205 175178 269271 139141 214216 202202 223225 095095 +IMLS1.2_MP1_IMLS053_E07 , 158161 207207 175210 000000 141147 216216 212228 223225 095095 +IMLS1.2_MP1_IMLS054_E08 , 161161 207209 181210 247247 139141 214216 202202 223225 095095 +IMLS1.2_MP1_IMLS055_E09 , 158161 201201 175175 247253 139147 214216 199228 223223 095095 +IMLS1.2_MP1_IMLS056_E10 , 161169 201209 181210 247247 139145 214214 200230 223223 095095 +IMLS1.2_MP1_IMLS057_E11 , 158161 203207 175210 245247 141147 214216 202228 223223 095095 +IMLS1.2_MP1_IMLS058_E12 , 161161 201203 175181 231247 137141 000000 210214 000000 095095 +IMLS1.2_MP1_IMLS059_F01 , 158161 201203 178184 259269 137137 216216 197228 223225 095095 +IMLS1.2_MP1_IMLS060_F02 , 158158 201203 184210 247247 137137 214216 228228 223223 095095 +IMLS1.2_MP1_IMLS061_F03 , 158161 201203 178210 000000 137137 214214 210228 223225 095095 +IMLS1.2_MP1_IMLS062_F04 , 158175 201207 178181 257269 137137 214218 195220 223223 095095 +IMLS1.2_MP1_IMLS063_F05 , 158161 201203 169175 247257 137141 216216 206206 223223 095095 +IMLS1.2_MP1_IMLS064_F06 , 161161 201203 169175 247247 137137 216216 202210 223225 095095 +IMLS1.2_MP1_IMLS065_F07 , 161161 201203 169175 247247 137141 216216 202206 223225 095095 +IMLS1.2_MP1_IMLS066_F08 , 158161 201203 175175 247257 137141 216216 206210 223223 095095 +IMLS1.2_MP1_IMLS067_F09 , 158161 201201 169175 257257 137137 214216 206210 223225 095095 +IMLS1.2_MP1_IMLS068_F10 , 163164 201203 175175 235263 139139 214216 208211 223223 095095 +POP +IMLS1.2_MP1_IMLS009_B03 , 161161 201201 172178 231247 137141 214214 202202 223223 095095 +IMLS1.2_MP1_IMLS010_B04 , 161164 205207 172178 249249 139141 214214 196232 223225 095097 +IMLS1.2_MP1_IMLS069_F11 , 161164 203205 172175 247269 141141 000000 206232 223223 095097 +IMLS1.2_MP1_IMLS070_F12 , 161161 201201 178184 269269 141143 214216 206206 225225 095095 +IMLS1.2_MP1_IMLS131_G01 , 161161 000000 178184 269269 141143 214216 206206 000000 095095 +IMLS1.2_MP1_IMLS132_G02 , 161164 201205 178184 231247 139149 214214 202202 223223 095095 +IMLS1.2_MP1_IMLS133_G03 , 161161 201205 175175 231247 137141 214216 202232 223223 095095 +IMLS1.2_MP1_IMLS134_G04 , 161161 201205 175175 231247 137141 214216 202232 223223 095095 +IMLS1.2_MP1_IMLS135_G05 , 161164 205207 172175 247249 141149 216216 202206 223223 095095 +IMLS1.2_MP1_IMLS136_G06 , 161164 205207 172175 249269 139141 230230 196200 223223 095095 +IMLS1.2_MP1_IMLS137_G07 , 161161 201201 175178 231247 137141 230230 202217 223223 095097 +IMLS1.2_MP1_IMLS138_G08 , 164164 201203 172172 247269 139141 000000 232232 223223 095097 +POP +IMLS1.2_MP1_IMLS011_A07 , 161163 207207 175178 233233 137137 214214 204214 223225 095095 +IMLS1.2_MP1_IMLS012_A08 , 158167 205207 175175 247257 139141 214215 204204 223223 095095 +IMLS1.2_MP1_IMLS139_G09 , 158161 201217 178181 251269 139139 214216 202234 225225 095095 +IMLS1.2_MP1_IMLS140_G10 , 158161 201207 175175 235269 137149 216216 201201 223225 095095 +IMLS1.2_MP1_IMLS141_G11 , 161185 201205 175175 251265 137141 228228 201202 223223 095095 +IMLS1.2_MP1_IMLS142_G12 , 161185 201205 175175 251265 137141 228228 201202 223223 095095 +IMLS1.2_MP1_IMLS143_H01 , 164173 000000 181181 253265 137137 226226 202220 223223 095095 +IMLS1.2_MP1_IMLS144_H02 , 161169 000000 178178 243269 137137 216216 201234 223223 095095 +IMLS1.2_MP1_IMLS145_H03 , 161161 205207 175178 243253 139139 216216 200212 223223 095095 +IMLS1.2_MP1_IMLS146_H04 , 161169 205213 175175 253269 137139 214228 202202 000000 095095 +IMLS1.2_MP1_IMLS147_H05 , 161169 205213 175175 253269 137139 214228 202202 000000 095095 +IMLS1.2_MP1_IMLS148_H06 , 161167 201201 169175 245257 137137 216216 211211 223223 095095 +IMLS1.2_MP1_IMLS149_H07 , 161171 203207 175178 243249 141141 214216 199199 223225 095095 +IMLS1.2_MP1_IMLS150_H08 , 161167 201213 175178 251255 137147 215215 212212 225225 095095 +IMLS1.2_MP1_IMLS151_H09 , 161161 205207 175175 247253 139141 214214 201211 000000 095095 +IMLS1.2_MP1_IMLS152_H10 , 156177 201201 175178 269269 141141 214216 199214 225225 095095 +IMLS2.2_MP1_IMLS153_B01 , 156161 201207 178181 245245 137137 206214 209211 223225 095095 +IMLS2.2_MP1_IMLS154_B02 , 156164 201201 181181 247263 137137 214216 198205 223223 095095 +IMLS2.2_MP1_IMLS155_B03 , 161169 201207 175175 269269 137137 214214 198217 223223 095095 +IMLS2.2_MP1_IMLS156_B04 , 161161 201205 175175 253265 137139 214214 198200 223223 095095 +IMLS2.2_MP1_IMLS157_B05 , 161161 201205 175175 253265 137139 214214 198200 223223 095095 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161175 201203 175181 247249 137139 214216 204209 223223 095095 +IMLS3_MP1_IMLS254_C01 , 161161 201207 181181 231245 137141 215215 202209 223223 093095 +IMLS3_MP1_IMLS255_C02 , 156161 201207 175178 251269 137139 214216 201202 223225 095095 +IMLS3_MP1_IMLS256_C03 , 161161 205207 175175 230249 137137 216228 204209 215223 095095 +IMLS3_MP1_IMLS257_C04 , 161175 205207 175175 269273 137139 214226 195216 223223 095095 +IMLS3_MP1_IMLS259_C06 , 161161 201213 166175 253265 137149 214214 199212 223223 095095 +IMLS3_MP1_IMLS261_C08 , 161161 201201 178181 245245 141143 214214 200212 188188 095095 +IMLS3_MP1_IMLS263_C10 , 161161 205217 175184 247249 137141 000000 200200 223223 095095 +IMLS3_MP1_IMLS265_C12 , 161161 201207 178178 247265 139143 218226 202226 223223 095095 +IMLS3_MP1_IMLS267_D02 , 156161 207207 175178 245247 137143 218226 210226 188188 095095 +IMLS3_MP1_IMLS268_D03 , 161171 207213 172175 243265 137147 226226 199215 223223 095095 +IMLS3_MP1_IMLS269_D04 , 161161 201207 169175 253265 139156 214216 206214 223223 095095 +IMLS3_MP1_IMLS270_D05 , 161163 205207 172175 255255 137139 218226 200200 224224 095095 +IMLS3_MP1_IMLS271_D06 , 161161 201207 175178 000000 137139 216218 200218 223225 095095 +IMLS3_MP1_IMLS272_D08 , 158161 201207 169175 243269 137137 000000 204213 223223 095095 +IMLS3_MP1_IMLS273_D09 , 158161 207213 175175 243257 137137 214214 196228 223223 095095 +IMLS3_MP1_IMLS274_D10 , 163175 201207 178178 247249 137139 214214 202205 223223 095095 +IMLS3_MP1_IMLS275_D11 , 161161 201201 175181 249261 139149 214217 207207 223223 095095 +IMLS3_MP1_IMLS276_D12 , 169175 205207 175178 269271 137137 214216 200204 225225 095095 +IMLS3_MP1_IMLS277_E01 , 161175 207207 175178 247247 137137 214214 199204 223223 095095 +IMLS1.2_MP1_IMLS017_B07 , 161173 201201 175178 245257 000000 206216 204207 000000 095095 +IMLS1.2_MP1_IMLS018_B08 , 169173 201201 178181 245245 137151 214216 197197 223223 095095 +IMLS3_MP1_IMLS258_C05 , 161169 201205 175181 247269 137137 214214 201216 000000 095095 +IMLS3_MP1_IMLS260_C07 , 161167 201207 173178 245245 137149 214214 207207 223223 095095 +IMLS3_MP1_IMLS262_C09 , 161163 201213 172175 249265 137137 000000 199199 223223 095095 +IMLS3_MP1_IMLS264_C11 , 156161 201217 175175 255265 137141 000000 199199 224224 095095 +IMLS3_MP1_IMLS278_E02 , 163167 199201 175178 245247 141141 216216 197197 223223 095095 +IMLS3_MP1_IMLS279_E03 , 156161 205207 175178 247271 137137 206214 197207 223223 095095 +IMLS3_MP1_IMLS280_E04 , 161169 201201 178181 245247 137137 216216 204211 223223 095095 +POP +IMLS1.2_MP1_IMLS013_A09 , 161173 201203 169175 235235 141141 214224 204209 223225 095095 +IMLS1.2_MP1_IMLS014_A10 , 161163 201203 172210 253253 137137 216216 200234 225225 095095 +IMLS2.2_MP1_IMLS181_D05 , 161161 201201 175178 247247 137137 214214 202206 223223 095095 +IMLS2.2_MP1_IMLS182_B02 , 169169 201205 172178 235235 137141 214216 000000 223225 095095 +IMLS2.2_MP1_IMLS183_D07 , 161161 201201 175210 251251 137137 000000 210210 223223 095095 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161161 201205 172178 235247 137137 214230 213215 215223 095095 +IMLS3_MP1_IMLS290_F02 , 161161 201207 172175 247263 137141 214230 200216 223227 095095 +IMLS3_MP1_IMLS291_F03 , 161161 205219 169178 245247 139141 214216 207215 223223 095095 +IMLS3_MP1_IMLS292_F04 , 161167 209209 172172 245263 137141 216224 208215 190227 095095 +IMLS3_MP1_IMLS293_F05 , 161167 203207 172175 263269 137141 224224 204208 227227 095095 +IMLS3_MP1_IMLS294_F06 , 161161 209209 172172 245263 137141 000000 200209 190227 095095 +IMLS3_MP1_IMLS295_F07 , 156163 201205 177178 247253 137139 216240 209220 223223 095095 +IMLS3_MP1_IMLS296_F08 , 161163 207219 175184 245257 137137 214214 201206 223223 095095 +IMLS3_MP1_IMLS297_F09 , 161177 201205 175181 247263 137141 000000 000000 000000 095095 +IMLS3_MP1_IMLS298_F10 , 156163 201203 175181 249269 137141 214214 000000 223223 095095 +IMLS3_MP1_IMLS299_F11 , 161169 199219 175175 245269 137137 214214 201208 223223 095095 +IMLS3_MP1_IMLS300_F12 , 161163 203205 175184 253269 137156 214216 201214 000000 095095 +IMLS3_MP1_IMLS301_G01 , 156161 215219 175175 269269 137141 214214 212214 000000 095095 +IMLS3_MP1_IMLS302_G02 , 161164 205207 175175 000000 137149 214245 206211 223223 095095 +IMLS3_MP1_IMLS303_G03 , 169171 201203 175178 251257 141147 214216 197208 223223 095095 +IMLS3_MP1_IMLS304_G04 , 156158 201207 169181 245247 141141 214216 211211 223223 095095 +IMLS3_MP1_IMLS305_G05 , 163171 203207 175175 245257 137141 214214 208211 223223 095095 +IMLS3_MP1_IMLS306_G06 , 156161 201207 178181 000000 139149 214216 202202 223225 095095 +IMLS3_MP1_IMLS307_G07 , 161161 207207 175178 257265 137137 000000 206208 215223 095095 +POP +IMLS3_MP1_IMLS308_G08 , 161161 201209 178178 245245 141149 216216 202202 000000 095095 +IMLS3_MP1_IMLS309_G09 , 161161 201209 175178 249257 137141 216216 202220 223223 095095 +IMLS3_MP1_IMLS310_G10 , 158161 201207 178184 245249 141149 216216 202210 223223 095095 +IMLS3_MP1_IMLS311_G11 , 161164 201201 178178 233245 139141 214216 202211 223223 095095 +IMLS3_MP1_IMLS312_G12 , 158169 201201 184184 249255 141149 216216 200202 000000 095095 +POP +IMLS3_MP1_IMLS313_H01 , 158161 201207 175210 247265 137147 214214 197247 223223 095095 +IMLS3_MP1_IMLS314_H02 , 158161 201205 175178 235247 137147 216216 206210 223225 095095 +IMLS3_MP1_IMLS315_H03 , 158161 201205 178178 247247 137147 214214 202206 223223 095095 +IMLS4_MP1_IMLS355_E01 , 161161 201207 175210 245247 137141 214214 204247 223223 095095 +IMLS4_MP1_IMLS356_E02 , 161161 201207 175175 245247 137141 214214 204247 223223 095095 +IMLS4_MP1_IMLS357_E03 , 161161 201207 175210 245253 141141 214214 197199 225225 095095 +IMLS4_MP1_IMLS358_E04 , 161161 207207 175210 247253 137141 214214 197247 223225 095095 +IMLS4_MP1_IMLS359_E05 , 161161 201201 175175 245247 141141 214214 204247 223223 095095 +IMLS4_MP1_IMLS360_E06 , 161161 201207 175210 245247 141141 214214 197199 223223 095095 +IMLS4_MP1_IMLS361_E07 , 158161 201207 175175 247253 137147 216216 197247 223225 095095 +IMLS4_MP1_IMLS362_E08 , 156175 207207 175178 230247 137139 206216 199207 215215 093095 +IMLS4_MP1_IMLS363_E09 , 158161 201201 169175 247257 137137 216216 202206 223223 095095 +IMLS4_MP1_IMLS364_E10 , 158161 201201 175175 247257 137137 214216 202210 223223 095095 +IMLS4_MP1_IMLS365_E11 , 161161 201201 169175 247247 137137 216216 206210 223225 095095 +IMLS4_MP1_IMLS366_E12 , 161161 201203 175176 247247 137137 216216 202206 223223 095095 +IMLS4_MP1_IMLS367_F01 , 156171 201205 177178 265271 137137 214224 197232 223223 095095 +IMLS4_MP1_IMLS368_F02 , 156173 201201 178181 245271 137137 214214 197197 223223 095095 +IMLS4_MP1_IMLS369_F03 , 161161 205207 177178 245271 137137 214214 197207 223223 095095 +IMLS4_MP1_IMLS345_D02 , 161171 201201 169175 235247 137137 216216 210210 223223 095095 +IMLS4_MP1_IMLS352_D10 , 161169 201207 175210 247265 137147 214214 202247 223223 095095 +IMLS4_MP1_IMLS353_D11 , 161169 201201 175175 247247 137147 214214 202247 223223 095095 +IMLS3_MP1_IMLS318_H06 , 161161 201201 175175 245247 137141 214214 204247 223223 095095 +IMLS3_MP1_IMLS319_H07 , 161161 201201 172210 247269 137147 214216 197210 223225 095095 +IMLS3_MP1_IMLS320_H08 , 161161 201201 175175 245253 137141 214214 197199 225225 095095 +IMLS3_MP1_IMLS321_H09 , 161161 201203 175175 247247 137137 216216 202206 223223 095095 +IMLS3_MP1_IMLS322_H10 , 161161 201201 169175 247247 137141 216216 202206 223225 095095 +IMLS4_MP1_IMLS323_B04 , 161161 201201 169175 247257 137137 216216 202210 223223 095095 +IMLS3_MP1_IMLS317_H05 , 158161 201203 169178 245247 137141 216216 202208 188225 095095 +IMLS3_MP1_IMLS316_H04 , 161161 203205 169172 000000 141141 214216 210210 223225 095097 +IMLS4_MP1_IMLS326_B07 , 158158 201205 175210 247247 141147 214214 206210 223225 095095 +IMLS4_MP1_IMLS327_B08 , 161169 201201 172178 247247 137147 214214 197206 223225 095095 +IMLS4_MP1_IMLS330_B11 , 161171 205217 175175 247263 137139 216216 000000 223227 095095 +IMLS4_MP1_IMLS331_B12 , 158161 201203 175175 257257 137141 216216 206210 223225 095095 +IMLS4_MP1_IMLS337_C06 , 156161 201217 178181 247263 137138 000000 204209 223223 095095 +IMLS4_MP1_IMLS338_C07 , 161161 203205 175175 249269 137137 216226 201232 223223 095095 +IMLS4_MP1_IMLS339_C08 , 158161 201201 175175 247253 139147 214216 199228 223223 095095 +IMLS4_MP1_IMLS340_C09 , 161163 201201 172172 000000 137141 216216 202204 223225 095095 +IMLS4_MP1_IMLS341_C10 , 158164 201207 172175 264267 137137 216216 199206 223225 095095 +IMLS4_MP1_IMLS342_C11 , 161169 203203 172175 245245 137139 214216 204209 223225 095095 +IMLS4_MP1_IMLS343_C12 , 161163 201201 175175 231253 137137 216216 204224 223223 095095 +IMLS4_MP1_IMLS344_D01 , 156164 207207 175175 243253 137137 216217 204232 223223 095095 +IMLS4_MP1_IMLS324_B05 , 161169 201201 175178 235247 147147 214216 206210 223225 095095 +IMLS4_MP1_IMLS325_B06 , 158161 201201 172178 247264 147147 214216 206206 223223 095095 +IMLS4_MP1_IMLS328_B09 , 158163 203205 172172 000000 137141 216216 000000 223225 095095 +IMLS4_MP1_IMLS329_B10 , 161161 201205 172172 000000 141141 230230 199234 223225 095095 +IMLS4_MP1_IMLS346_D03 , 161161 201203 169175 247247 141141 216216 202206 223225 095095 +IMLS4_MP1_IMLS347_D04 , 161161 201203 175175 247247 137141 216216 202202 223225 095095 +IMLS4_MP1_IMLS348_D05 , 161161 201203 169175 247247 141141 216216 206206 223225 095095 +IMLS4_MP1_IMLS349_D06 , 158161 201201 169175 247257 137137 216216 206206 223223 095095 +IMLS4_MP1_IMLS350_D08 , 158161 201203 175175 257257 137137 214216 206210 223225 095095 +IMLS4_MP1_IMLS351_D09 , 158161 201201 175176 257257 137137 216216 206206 225225 095095 +IMLS4_MP1_IMLS354_D12 , 158163 203205 178210 253253 137141 216216 204234 223223 095095 +IMLS4_MP1_IMLS370_F04 , 161161 201203 169175 247247 137141 216216 202206 223225 095095 +IMLS4_MP1_IMLS371_F05 , 161169 201201 178181 245245 139151 000000 197197 223223 095095 +IMLS4_MP1_IMLS372_F06 , 161161 201201 175178 000000 137137 214214 199201 215225 095095 +IMLS4_MP1_IMLS373_F07 , 161161 201207 175181 230245 137139 214216 197199 215223 093095 +IMLS4_MP1_IMLS374_F08 , 000000 000000 000000 245271 137137 214216 197228 188223 093095 +IMLS4_MP1_IMLS375_F09 , 156161 201205 178178 245261 137141 000000 197226 223223 095095 +IMLS4_MP1_IMLS376_F10 , 156161 201205 175178 245253 137139 216216 197199 223223 095095 +IMLS4_MP1_IMLS377_F11 , 156164 201205 177177 255271 135137 000000 197202 223223 095099 +IMLS4_MP1_IMLS378_F12 , 161161 201207 175210 245247 141141 214214 197199 223223 095095 +IMLS4_MP1_IMLS379_G01 , 161169 201207 175175 247265 141147 214214 202247 000000 095095 +IMLS4_MP1_IMLS380_G02 , 161161 201207 175176 245247 141141 214214 204247 000000 095095 +IMLS4_MP1_IMLS381_G03 , 161161 207207 210210 247253 137137 000000 197247 223225 095095 +IMLS4_MP1_IMLS382_G04 , 161161 201201 175176 245247 141141 214214 199247 000000 000000 +IMLS4_MP1_IMLS383_G05 , 161169 201201 175210 253265 137141 214214 197202 223225 095095 +IMLS4_MP1_IMLS384_G06 , 161169 201207 175210 253265 137147 214214 197247 223225 095095 +IMLS4_MP1_IMLS385_G07 , 156161 201207 178178 249271 137141 206206 197204 223223 095095 +IMLS4_MP1_IMLS386_G08 , 161161 201207 175175 249271 137139 214214 197201 223223 095095 +IMLS4_MP1_IMLS387_G10 , 000000 000000 175176 000000 137139 214216 000000 000000 093095 +IMLS4_MP1_IMLS388_G09 , 161163 201207 175175 247247 137141 206214 205212 223223 095095 +IMLS4_MP1_IMLS389_G11 , 156161 201207 175178 230245 137139 216216 197199 215223 095095 +IMLS4_MP1_IMLS332_C01 , 158161 201207 175175 247247 141147 214230 204214 223225 095095 +IMLS4_MP1_IMLS333_C02 , 161161 205205 172210 235247 137141 214214 206214 223223 095095 +IMLS4_MP1_IMLS334_C03 , 158161 201203 172175 000000 137141 214214 214214 223225 095095 +IMLS4_MP1_IMLS335_C04 , 158161 205207 172175 245247 137141 000000 199199 188223 095095 +IMLS4_MP1_IMLS336_C05 , 161161 201207 172175 247247 141141 215216 202204 223223 095095 diff --git a/Qboyntonii/Qb_wild.gen b/Qboyntonii/Qb_wild.gen new file mode 100644 index 0000000..713471b --- /dev/null +++ b/Qboyntonii/Qb_wild.gen @@ -0,0 +1,264 @@ +"Qubo Wild ALL populations even small ones with 6, 8, and 9 MERGED" +QrZAG20 +QpZAG110 +QS00314 +QpZAG9 +QS01904 +QS03297 +MSQ4 +QS00562 +QrZAG87 +POP +IMLS1.2_MP1_IMLS001_A01 , 158169 201201 175175 247265 141147 214216 202249 223223 095095 +IMLS1.2_MP1_IMLS002_A02 , 161161 201207 175210 247253 137141 214214 197247 223225 095095 +POP +IMLS1.2_MP1_IMLS003_A03 , 161161 201207 175175 233269 139141 216216 200208 215225 095095 +IMLS1.2_MP1_IMLS004_A04 , 161161 201201 175178 243245 137141 214214 197200 223223 095095 +IMLS1.2_MP1_IMLS021_B11 , 161169 207207 175181 247269 137137 216218 202217 223223 095095 +IMLS1.2_MP1_IMLS022_B12 , 161161 207207 172178 249269 137141 216216 204217 223223 095095 +IMLS1.2_MP1_IMLS023_C01 , 161161 207207 172178 249269 137141 216216 204217 223223 095095 +IMLS1.2_MP1_IMLS024_C02 , 158161 201201 175175 235245 137137 214214 197197 223223 095095 +IMLS1.2_MP1_IMLS025_C03 , 158161 205215 169172 245265 139147 216216 202202 223223 095095 +IMLS1.2_MP1_IMLS026_C04 , 161169 205207 175178 000000 000000 214216 212212 223225 095095 +IMLS1.2_MP1_IMLS027_C05 , 158169 201213 175178 247249 137139 214216 199199 223223 095095 +IMLS1.2_MP1_IMLS028_C06 , 158169 201213 175178 247249 137139 214216 199199 223223 095095 +IMLS1.2_MP1_IMLS029_C07 , 156161 201201 175181 245247 137137 214226 201201 223223 095095 +IMLS1.2_MP1_IMLS030_C08 , 161161 201205 172175 247265 137139 216230 202246 223223 095095 +IMLS1.2_MP1_IMLS031_C09 , 161161 201201 175178 243245 139141 216216 198214 223223 095095 +IMLS1.2_MP1_IMLS032_C10 , 161173 201205 175175 245257 141141 216216 198207 223223 095095 +POP +IMLS1.2_MP1_IMLS005_A05 , 161163 207207 175175 269271 137137 216216 199203 223225 095095 +IMLS1.2_MP1_IMLS006_A06 , 164167 201201 175175 235265 137137 216216 212232 223223 095095 +IMLS1.2_MP1_IMLS033_C11 , 161163 201201 169181 231245 137137 216216 208208 223223 095095 +IMLS1.2_MP1_IMLS034_C12 , 161161 201207 175175 249253 137139 214226 198218 223223 095095 +IMLS1.2_MP1_IMLS035_D01 , 161163 205207 175178 249265 137137 214217 203215 223223 095095 +IMLS1.2_MP1_IMLS036_D02 , 156161 201207 175178 000000 137137 216216 201203 223225 095095 +IMLS1.2_MP1_IMLS037_D03 , 156164 201201 175181 000000 137137 216216 232236 188225 095095 +IMLS1.2_MP1_IMLS038_D04 , 161161 207207 175175 235253 137137 000000 197214 223223 095095 +IMLS1.2_MP1_IMLS039_D05 , 154161 201205 175175 245245 147147 216230 199204 223223 095095 +IMLS1.2_MP1_IMLS041_D07 , 158158 201201 175181 245245 141147 214214 197203 225225 095095 +IMLS1.2_MP1_IMLS042_D08 , 158158 201201 175181 245245 141147 214214 197203 225225 095095 +IMLS1.2_MP1_IMLS043_D09 , 161164 201205 175178 000000 137141 216216 210232 223225 095095 +IMLS1.2_MP1_IMLS044_D10 , 161164 201205 175178 000000 137141 216216 210232 223225 095095 +IMLS1.2_MP1_IMLS045_D11 , 161161 201207 169184 235249 137141 214216 197212 223223 095095 +IMLS1.2_MP1_IMLS046_D12 , 161161 201201 175175 253263 137137 216216 206227 223227 095095 +IMLS1.2_MP1_IMLS047_E01 , 161169 201205 178210 251269 141147 214216 199207 223223 095095 +IMLS1.2_MP1_IMLS048_E02 , 161163 201205 175181 263263 139155 214217 000000 223223 095095 +POP +IMLS1.2_MP1_IMLS007_B01 , 158161 201207 178184 000000 137137 216216 195197 223223 095095 +IMLS1.2_MP1_IMLS008_B02 , 161164 203207 178178 251251 137137 216230 197199 223223 095095 +IMLS1.2_MP1_IMLS049_E03 , 156161 201207 178178 249271 137137 000000 208214 223223 095095 +IMLS1.2_MP1_IMLS050_E04 , 161167 201203 175178 245249 141141 214216 214220 223223 095095 +IMLS1.2_MP1_IMLS051_E05 , 161173 201207 175175 251259 137139 214214 195195 225225 095095 +IMLS1.2_MP1_IMLS052_E06 , 161169 201205 175178 269271 139141 214216 202202 223225 095095 +IMLS1.2_MP1_IMLS053_E07 , 158161 207207 175210 000000 141147 216216 212228 223225 095095 +IMLS1.2_MP1_IMLS054_E08 , 161161 207209 181210 247247 139141 214216 202202 223225 095095 +IMLS1.2_MP1_IMLS055_E09 , 158161 201201 175175 247253 139147 214216 199228 223223 095095 +IMLS1.2_MP1_IMLS056_E10 , 161169 201209 181210 247247 139145 214214 200230 223223 095095 +IMLS1.2_MP1_IMLS057_E11 , 158161 203207 175210 245247 141147 214216 202228 223223 095095 +IMLS1.2_MP1_IMLS058_E12 , 161161 201203 175181 231247 137141 000000 210214 000000 095095 +IMLS1.2_MP1_IMLS059_F01 , 158161 201203 178184 259269 137137 216216 197228 223225 095095 +IMLS1.2_MP1_IMLS060_F02 , 158158 201203 184210 247247 137137 214216 228228 223223 095095 +IMLS1.2_MP1_IMLS061_F03 , 158161 201203 178210 000000 137137 214214 210228 223225 095095 +IMLS1.2_MP1_IMLS062_F04 , 158175 201207 178181 257269 137137 214218 195220 223223 095095 +IMLS1.2_MP1_IMLS063_F05 , 158161 201203 169175 247257 137141 216216 206206 223223 095095 +IMLS1.2_MP1_IMLS064_F06 , 161161 201203 169175 247247 137137 216216 202210 223225 095095 +IMLS1.2_MP1_IMLS065_F07 , 161161 201203 169175 247247 137141 216216 202206 223225 095095 +IMLS1.2_MP1_IMLS066_F08 , 158161 201203 175175 247257 137141 216216 206210 223223 095095 +IMLS1.2_MP1_IMLS067_F09 , 158161 201201 169175 257257 137137 214216 206210 223225 095095 +IMLS1.2_MP1_IMLS068_F10 , 163164 201203 175175 235263 139139 214216 208211 223223 095095 +POP +IMLS1.2_MP1_IMLS009_B03 , 161161 201201 172178 231247 137141 214214 202202 223223 095095 +IMLS1.2_MP1_IMLS010_B04 , 161164 205207 172178 249249 139141 214214 196232 223225 095097 +IMLS1.2_MP1_IMLS069_F11 , 161164 203205 172175 247269 141141 000000 206232 223223 095097 +IMLS1.2_MP1_IMLS070_F12 , 161161 201201 178184 269269 141143 214216 206206 225225 095095 +IMLS1.2_MP1_IMLS131_G01 , 161161 000000 178184 269269 141143 214216 206206 000000 095095 +IMLS1.2_MP1_IMLS132_G02 , 161164 201205 178184 231247 139149 214214 202202 223223 095095 +IMLS1.2_MP1_IMLS133_G03 , 161161 201205 175175 231247 137141 214216 202232 223223 095095 +IMLS1.2_MP1_IMLS134_G04 , 161161 201205 175175 231247 137141 214216 202232 223223 095095 +IMLS1.2_MP1_IMLS135_G05 , 161164 205207 172175 247249 141149 216216 202206 223223 095095 +IMLS1.2_MP1_IMLS136_G06 , 161164 205207 172175 249269 139141 230230 196200 223223 095095 +IMLS1.2_MP1_IMLS137_G07 , 161161 201201 175178 231247 137141 230230 202217 223223 095097 +IMLS1.2_MP1_IMLS138_G08 , 164164 201203 172172 247269 139141 000000 232232 223223 095097 +POP +IMLS1.2_MP1_IMLS011_A07 , 161163 207207 175178 233233 137137 214214 204214 223225 095095 +IMLS1.2_MP1_IMLS012_A08 , 158167 205207 175175 247257 139141 214215 204204 223223 095095 +IMLS1.2_MP1_IMLS139_G09 , 158161 201217 178181 251269 139139 214216 202234 225225 095095 +IMLS1.2_MP1_IMLS140_G10 , 158161 201207 175175 235269 137149 216216 201201 223225 095095 +IMLS1.2_MP1_IMLS141_G11 , 161185 201205 175175 251265 137141 228228 201202 223223 095095 +IMLS1.2_MP1_IMLS142_G12 , 161185 201205 175175 251265 137141 228228 201202 223223 095095 +IMLS1.2_MP1_IMLS143_H01 , 164173 000000 181181 253265 137137 226226 202220 223223 095095 +IMLS1.2_MP1_IMLS144_H02 , 161169 000000 178178 243269 137137 216216 201234 223223 095095 +IMLS1.2_MP1_IMLS145_H03 , 161161 205207 175178 243253 139139 216216 200212 223223 095095 +IMLS1.2_MP1_IMLS146_H04 , 161169 205213 175175 253269 137139 214228 202202 000000 095095 +IMLS1.2_MP1_IMLS147_H05 , 161169 205213 175175 253269 137139 214228 202202 000000 095095 +IMLS1.2_MP1_IMLS148_H06 , 161167 201201 169175 245257 137137 216216 211211 223223 095095 +IMLS1.2_MP1_IMLS149_H07 , 161171 203207 175178 243249 141141 214216 199199 223225 095095 +IMLS1.2_MP1_IMLS150_H08 , 161167 201213 175178 251255 137147 215215 212212 225225 095095 +IMLS1.2_MP1_IMLS151_H09 , 161161 205207 175175 247253 139141 214214 201211 000000 095095 +IMLS1.2_MP1_IMLS152_H10 , 156177 201201 175178 269269 141141 214216 199214 225225 095095 +IMLS2.2_MP1_IMLS153_B01 , 156161 201207 178181 245245 137137 206214 209211 223225 095095 +IMLS2.2_MP1_IMLS154_B02 , 156164 201201 181181 247263 137137 214216 198205 223223 095095 +IMLS2.2_MP1_IMLS155_B03 , 161169 201207 175175 269269 137137 214214 198217 223223 095095 +IMLS2.2_MP1_IMLS156_B04 , 161161 201205 175175 253265 137139 214214 198200 223223 095095 +IMLS2.2_MP1_IMLS157_B05 , 161161 201205 175175 253265 137139 214214 198200 223223 095095 +IMLS2.2_MP1_IMLS158_B06 , 161169 201207 175175 269269 137137 214214 198217 223223 095095 +IMLS2.2_MP1_IMLS159_B07 , 173175 201207 175175 235257 137141 214216 000000 215223 095095 +IMLS2.2_MP1_IMLS160_B08 , 161163 201201 178181 235245 137141 216216 200214 223223 095095 +IMLS2.2_MP1_IMLS161_B09 , 156161 201201 175175 253263 137141 216216 216218 223227 095095 +IMLS2.2_MP1_IMLS162_B10 , 158161 207217 175181 253265 137137 216216 204206 223223 095095 +IMLS2.2_MP1_IMLS163_B11 , 171171 201201 175175 247269 139139 216216 198204 215215 095097 +IMLS2.2_MP1_IMLS164_B12 , 161161 203207 178181 253253 141141 216216 203208 223223 095095 +IMLS2.2_MP1_IMLS165_C01 , 161169 201207 178178 269269 137137 214216 206218 000000 095095 +IMLS2.2_MP1_IMLS166_C02 , 161175 207217 175181 251265 137137 216216 198219 223223 095095 +IMLS2.2_MP1_IMLS167_C03 , 161175 207217 175181 251265 137137 216216 198219 223223 095095 +IMLS2.2_MP1_IMLS168_C04 , 156161 207207 175184 245245 137141 216216 206212 188188 095095 +IMLS2.2_MP1_IMLS169_C05 , 156161 207207 175184 245245 137141 216216 206212 188188 095095 +IMLS2.2_MP1_IMLS170_C06 , 158161 205215 175181 247247 137141 216217 202206 223223 095095 +IMLS2.2_MP1_IMLS171_C07 , 163171 207207 175175 251271 137139 214216 000000 215215 095095 +IMLS2.2_MP1_IMLS172_C08 , 161171 207207 175175 271271 137139 216216 197230 223223 095095 +IMLS2.2_MP1_IMLS173_C09 , 161163 205215 175181 000000 141141 214216 204206 225225 095095 +IMLS2.2_MP1_IMLS174_C10 , 161161 205215 175181 245265 137141 215215 202202 223223 095095 +IMLS2.2_MP1_IMLS175_C11 , 158161 205207 175178 253271 137138 226226 198216 223225 095095 +IMLS2.2_MP1_IMLS176_C12 , 161161 201205 175175 265269 137139 000000 197218 223223 095095 +IMLS2.2_MP1_IMLS177_D01 , 161161 201205 176176 265269 137139 000000 197218 223223 095095 +IMLS2.2_MP1_IMLS178_D02 , 158167 205207 175175 247257 139141 000000 204204 223223 095095 +IMLS2.2_MP1_IMLS179_D03 , 156161 201207 178178 000000 139147 214216 204216 223225 095095 +IMLS2.2_MP1_IMLS180_D04 , 158161 207207 178178 247265 138139 214230 201204 223223 095095 +IMLS1.2_MP1_IMLS015_B05 , 161167 201207 175175 243247 137139 216216 199244 223223 095095 +IMLS1.2_MP1_IMLS016_B06 , 156161 207207 175175 269271 139139 214214 204214 223225 095095 +IMLS3_MP1_IMLS245_B04 , 175175 205207 175175 247269 139141 216216 206208 000000 095095 +IMLS3_MP1_IMLS246_B05 , 175175 205207 175175 247269 139141 216216 206208 000000 095095 +IMLS3_MP1_IMLS247_B06 , 161169 201201 175181 245249 137141 214216 197199 223223 095095 +IMLS3_MP1_IMLS248_B07 , 156161 201207 175181 253253 000000 000000 000000 223223 095095 +IMLS3_MP1_IMLS249_B08 , 161169 201207 181181 247249 137139 216230 197197 223223 095095 +IMLS3_MP1_IMLS250_B09 , 163169 201213 166175 247255 137137 218218 198198 224224 095095 +IMLS3_MP1_IMLS251_B10 , 161175 207207 175178 249271 137141 214214 197214 223223 095095 +IMLS3_MP1_IMLS252_B11 , 161175 199203 178181 247264 137141 214214 196209 215223 095095 +IMLS3_MP1_IMLS253_B12 , 161175 201203 175181 247249 137139 214216 204209 223223 095095 +IMLS3_MP1_IMLS254_C01 , 161161 201207 181181 231245 137141 215215 202209 223223 093095 +IMLS3_MP1_IMLS255_C02 , 156161 201207 175178 251269 137139 214216 201202 223225 095095 +IMLS3_MP1_IMLS256_C03 , 161161 205207 175175 230249 137137 216228 204209 215223 095095 +IMLS3_MP1_IMLS257_C04 , 161175 205207 175175 269273 137139 214226 195216 223223 095095 +IMLS3_MP1_IMLS259_C06 , 161161 201213 166175 253265 137149 214214 199212 223223 095095 +IMLS3_MP1_IMLS261_C08 , 161161 201201 178181 245245 141143 214214 200212 188188 095095 +IMLS3_MP1_IMLS263_C10 , 161161 205217 175184 247249 137141 000000 200200 223223 095095 +IMLS3_MP1_IMLS265_C12 , 161161 201207 178178 247265 139143 218226 202226 223223 095095 +IMLS3_MP1_IMLS267_D02 , 156161 207207 175178 245247 137143 218226 210226 188188 095095 +IMLS3_MP1_IMLS268_D03 , 161171 207213 172175 243265 137147 226226 199215 223223 095095 +IMLS3_MP1_IMLS269_D04 , 161161 201207 169175 253265 139156 214216 206214 223223 095095 +IMLS3_MP1_IMLS270_D05 , 161163 205207 172175 255255 137139 218226 200200 224224 095095 +IMLS3_MP1_IMLS271_D06 , 161161 201207 175178 000000 137139 216218 200218 223225 095095 +IMLS3_MP1_IMLS272_D08 , 158161 201207 169175 243269 137137 000000 204213 223223 095095 +IMLS3_MP1_IMLS273_D09 , 158161 207213 175175 243257 137137 214214 196228 223223 095095 +IMLS3_MP1_IMLS274_D10 , 163175 201207 178178 247249 137139 214214 202205 223223 095095 +IMLS3_MP1_IMLS275_D11 , 161161 201201 175181 249261 139149 214217 207207 223223 095095 +IMLS3_MP1_IMLS276_D12 , 169175 205207 175178 269271 137137 214216 200204 225225 095095 +IMLS3_MP1_IMLS277_E01 , 161175 207207 175178 247247 137137 214214 199204 223223 095095 +IMLS1.2_MP1_IMLS017_B07 , 161173 201201 175178 245257 000000 206216 204207 000000 095095 +IMLS1.2_MP1_IMLS018_B08 , 169173 201201 178181 245245 137151 214216 197197 223223 095095 +IMLS3_MP1_IMLS258_C05 , 161169 201205 175181 247269 137137 214214 201216 000000 095095 +IMLS3_MP1_IMLS260_C07 , 161167 201207 173178 245245 137149 214214 207207 223223 095095 +IMLS3_MP1_IMLS262_C09 , 161163 201213 172175 249265 137137 000000 199199 223223 095095 +IMLS3_MP1_IMLS264_C11 , 156161 201217 175175 255265 137141 000000 199199 224224 095095 +IMLS3_MP1_IMLS278_E02 , 163167 199201 175178 245247 141141 216216 197197 223223 095095 +IMLS3_MP1_IMLS279_E03 , 156161 205207 175178 247271 137137 206214 197207 223223 095095 +IMLS3_MP1_IMLS280_E04 , 161169 201201 178181 245247 137137 216216 204211 223223 095095 +POP +IMLS1.2_MP1_IMLS013_A09 , 161173 201203 169175 235235 141141 214224 204209 223225 095095 +IMLS1.2_MP1_IMLS014_A10 , 161163 201203 172210 253253 137137 216216 200234 225225 095095 +IMLS2.2_MP1_IMLS181_D05 , 161161 201201 175178 247247 137137 214214 202206 223223 095095 +IMLS2.2_MP1_IMLS182_B02 , 169169 201205 172178 235235 137141 214216 000000 223225 095095 +IMLS2.2_MP1_IMLS183_D07 , 161161 201201 175210 251251 137137 000000 210210 223223 095095 +IMLS2.2_MP1_IMLS184_D08 , 158161 201207 172175 253253 137147 214216 202202 223223 095095 +IMLS2.2_MP1_IMLS185_D09 , 163169 201201 172175 247247 139141 216216 198214 223223 095095 +IMLS2.2_MP1_IMLS186_D10 , 161161 201207 172175 243253 137137 214216 202210 223223 095095 +IMLS2.2_MP1_IMLS187_D11 , 158161 201201 172175 243243 139141 216216 206214 223223 095095 +IMLS2.2_MP1_IMLS188_D12 , 158161 201203 169178 245245 147147 214214 210212 188225 095095 +IMLS2.2_MP1_IMLS189_E01 , 158161 201203 169178 000000 139149 216216 199206 225225 095095 +IMLS2.2_MP1_IMLS190_E02 , 161161 201205 172175 235237 137141 214216 210212 223223 095095 +IMLS2.2_MP1_IMLS191_E03 , 158161 201201 175175 245253 141147 230230 200234 188188 095095 +IMLS2.2_MP1_IMLS192_E04 , 158161 201209 169175 000000 137139 216216 216242 223225 095095 +IMLS2.2_MP1_IMLS193_E05 , 158169 201201 169175 000000 141141 216216 204214 223223 095095 +IMLS2.2_MP1_IMLS194_E06 , 158161 201203 175210 235235 141141 214216 212238 223225 095095 +IMLS2.2_MP1_IMLS195_E07 , 161163 203203 172178 235235 139141 216216 197214 223225 095095 +IMLS2.2_MP1_IMLS196_E08 , 158161 201207 169172 235245 137141 214216 232232 188223 095095 +IMLS2.2_MP1_IMLS197_E09 , 158161 201201 175178 247251 141141 216216 214214 225225 095097 +IMLS2.2_MP1_IMLS198_E10 , 161164 201203 175178 243247 137137 216216 204204 223225 095095 +IMLS2.2_MP1_IMLS199_E11 , 161161 201203 175178 257257 137141 214216 202216 223225 095095 +IMLS2.2_MP1_IMLS200_E12 , 161163 201207 172175 235235 141141 214216 212216 223223 095095 +IMLS2.2_MP1_IMLS201_F01 , 158161 201201 169175 243245 137141 214216 199211 223223 095095 +IMLS2.2_MP1_IMLS202_F02 , 161161 201203 175178 247247 141147 214216 199216 223223 095095 +IMLS2.2_MP1_IMLS209_F03 , 158161 000000 175210 245245 137141 216216 202209 225225 095095 +IMLS2.2_MP1_IMLS210_F04 , 158158 000000 169175 245245 137141 214214 212212 223225 095095 +IMLS2.2_MP1_IMLS211_F05 , 161169 201201 172210 245253 137147 216216 199204 223225 095095 +IMLS2.2_MP1_IMLS212_F06 , 161173 201203 175175 245245 141141 214216 210210 188223 095095 +IMLS2.2_MP1_IMLS213_F07 , 158161 201201 169172 245245 137137 000000 212212 188188 095095 +IMLS2.2_MP1_IMLS214_F08 , 156161 201203 172178 235247 137137 216216 202202 223223 095095 +IMLS2.2_MP1_IMLS215_F09 , 161173 199203 175210 000000 137141 214216 204210 223223 095095 +IMLS2.2_MP1_IMLS216_F10 , 171173 201207 172178 235247 137141 214216 199210 223223 095095 +IMLS2.2_MP1_IMLS217_F11 , 158173 199209 169178 235235 137147 216216 207214 223225 095095 +IMLS2.2_MP1_IMLS218_F12 , 167173 201209 172175 253253 141141 214216 202202 223223 095095 +IMLS2.2_MP1_IMLS219_G01 , 158161 000000 169178 000000 141159 214230 197214 223225 095095 +IMLS2.2_MP1_IMLS220_G02 , 158167 000000 172175 253265 137141 214214 202202 223223 095095 +IMLS2.2_MP1_IMLS221_G03 , 161173 201205 175175 253253 137141 216216 200214 223223 095095 +IMLS2.2_MP1_IMLS222_G04 , 158158 201205 178178 000000 141159 216230 214214 223225 095095 +IMLS2.2_MP1_IMLS223_G05 , 158173 201201 172178 231263 137137 214214 202214 225225 095095 +IMLS2.2_MP1_IMLS224_G06 , 158161 201203 169175 251251 137147 214230 202214 223223 095095 +IMLS2.2_MP1_IMLS225_G07 , 158161 201201 172175 235235 147147 214216 206210 223223 095095 +IMLS2.2_MP1_IMLS226_G08 , 158161 199205 175178 235245 137141 214216 199210 223225 095095 +IMLS2.2_MP1_IMLS227_G09 , 158161 201209 172175 245245 137147 224224 210234 188225 095095 +IMLS2.2_MP1_IMLS228_G10 , 161173 203207 172175 243253 139141 214216 000000 223223 095095 +IMLS2.2_MP1_IMLS229_G11 , 161169 203205 172175 247267 137137 214214 200257 223225 095095 +IMLS2.2_MP1_IMLS230_G12 , 161161 201201 175181 247247 137149 214214 214214 225225 095095 +IMLS2.2_MP1_IMLS231_H01 , 161161 201203 175178 235243 137141 214214 204206 217223 095095 +IMLS2.2_MP1_IMLS232_H02 , 158161 201207 175178 235245 137147 216240 204214 215223 095095 +IMLS2.2_MP1_IMLS233_H03 , 161161 201203 172175 000000 137141 214214 204216 225225 095095 +IMLS2.2_MP1_IMLS234_H04 , 158158 201201 172175 243247 141147 214216 210214 223223 095095 +IMLS2.2_MP1_IMLS235_H05 , 161161 201201 175175 235235 137141 214216 199206 217225 095095 +IMLS2.2_MP1_IMLS236_H06 , 169173 201203 172175 247247 137137 214216 199204 223223 095095 +IMLS2.2_MP1_IMLS237_H07 , 158161 201207 175184 243257 141141 214217 210214 223223 095095 +IMLS2.2_MP1_IMLS238_H08 , 158161 201207 172175 245245 141141 214214 199199 188225 095095 +IMLS2.2_MP1_IMLS239_H09 , 161161 203207 172172 245245 137141 214214 199199 188225 095097 +IMLS2.2_MP1_IMLS240_H10 , 158161 201203 169178 235245 137139 214216 207209 000000 000000 +IMLS2.2_MP1_IMLS241_B03 , 161173 201201 172184 245245 141147 214216 199207 223225 095095 +IMLS3_MP1_IMLS242_B01 , 158161 203203 172178 247247 137139 216240 202204 223223 095095 +IMLS3_MP1_IMLS243_B02 , 158173 201203 175175 245245 149149 214214 199214 188225 095095 +IMLS3_MP1_IMLS244_B03 , 161171 201203 172175 245251 137137 214216 210214 188223 095095 +POP +IMLS1.2_MP1_IMLS019_B09 , 156161 215219 175184 249269 141141 214214 201204 223225 095095 +IMLS1.2_MP1_IMLS020_B10 , 161171 201201 175181 243253 139141 214214 199210 223223 095095 +IMLS3_MP1_IMLS266_D01 , 161163 201217 176176 255255 000000 216216 199199 000000 000000 +IMLS3_MP1_IMLS281_E05 , 163164 201201 175178 245257 137141 214245 203211 223223 095095 +IMLS3_MP1_IMLS282_E06 , 161164 201201 178181 245265 137139 216245 211214 223223 095095 +IMLS3_MP1_IMLS283_E07 , 161161 207219 175175 253269 137137 214214 200207 223225 095095 +IMLS3_MP1_IMLS284_E08 , 161173 201201 175175 249251 137137 214214 204236 223223 095095 +IMLS3_MP1_IMLS285_E09 , 161164 201205 175178 249251 137139 214214 000000 000000 095095 +IMLS3_MP1_IMLS286_E10 , 161161 201209 172172 247263 141141 000000 200215 223227 095095 +IMLS3_MP1_IMLS287_E11 , 161173 201209 172172 245263 137141 214215 209215 190227 095095 +IMLS3_MP1_IMLS288_E12 , 158161 201201 175178 253265 137137 214214 196213 223223 095095 +IMLS3_MP1_IMLS289_F01 , 161161 201205 172178 235247 137137 214230 213215 215223 095095 +IMLS3_MP1_IMLS290_F02 , 161161 201207 172175 247263 137141 214230 200216 223227 095095 +IMLS3_MP1_IMLS291_F03 , 161161 205219 169178 245247 139141 214216 207215 223223 095095 +IMLS3_MP1_IMLS292_F04 , 161167 209209 172172 245263 137141 216224 208215 190227 095095 +IMLS3_MP1_IMLS293_F05 , 161167 203207 172175 263269 137141 224224 204208 227227 095095 +IMLS3_MP1_IMLS294_F06 , 161161 209209 172172 245263 137141 000000 200209 190227 095095 +IMLS3_MP1_IMLS295_F07 , 156163 201205 177178 247253 137139 216240 209220 223223 095095 +IMLS3_MP1_IMLS296_F08 , 161163 207219 175184 245257 137137 214214 201206 223223 095095 +IMLS3_MP1_IMLS297_F09 , 161177 201205 175181 247263 137141 000000 000000 000000 095095 +IMLS3_MP1_IMLS298_F10 , 156163 201203 175181 249269 137141 214214 000000 223223 095095 +IMLS3_MP1_IMLS299_F11 , 161169 199219 175175 245269 137137 214214 201208 223223 095095 +IMLS3_MP1_IMLS300_F12 , 161163 203205 175184 253269 137156 214216 201214 000000 095095 +IMLS3_MP1_IMLS301_G01 , 156161 215219 175175 269269 137141 214214 212214 000000 095095 +IMLS3_MP1_IMLS302_G02 , 161164 205207 175175 000000 137149 214245 206211 223223 095095 +IMLS3_MP1_IMLS303_G03 , 169171 201203 175178 251257 141147 214216 197208 223223 095095 +IMLS3_MP1_IMLS304_G04 , 156158 201207 169181 245247 141141 214216 211211 223223 095095 +IMLS3_MP1_IMLS305_G05 , 163171 203207 175175 245257 137141 214214 208211 223223 095095 +IMLS3_MP1_IMLS306_G06 , 156161 201207 178181 000000 139149 214216 202202 223225 095095 +IMLS3_MP1_IMLS307_G07 , 161161 207207 175178 257265 137137 000000 206208 215223 095095 +POP +IMLS3_MP1_IMLS308_G08 , 161161 201209 178178 245245 141149 216216 202202 000000 095095 +IMLS3_MP1_IMLS309_G09 , 161161 201209 175178 249257 137141 216216 202220 223223 095095 +IMLS3_MP1_IMLS310_G10 , 158161 201207 178184 245249 141149 216216 202210 223223 095095 +IMLS3_MP1_IMLS311_G11 , 161164 201201 178178 233245 139141 214216 202211 223223 095095 +IMLS3_MP1_IMLS312_G12 , 158169 201201 184184 249255 141149 216216 200202 000000 095095 diff --git a/Qgeorgiana/Qg_total.gen b/Qgeorgiana/Qg_total.gen new file mode 100644 index 0000000..51d92d9 --- /dev/null +++ b/Qgeorgiana/Qg_total.gen @@ -0,0 +1,293 @@ +"Quercus georgiana complete dataset all markers, wild (by pop) including NC (2 samp) and ex situ (last pop)" +FIR039 +FIR013 +FIR048 +FIR043 +GOT037 +PIE200 +FIR035 +VIT081 +VIT086 +PIE125 +FIR028 +QUi21a +QUm07a +QUf02a +QUC19a +QUE09a +QUC08a +QUG07a +QUH14a +POP +MR01 , 120120 140140 214214 112122 252254 110113 146148 107107 201201 159162 204204 191219 217219 177177 236262 192210 287299 226228 299299 +MR02 , 120120 140140 212214 122122 244254 110110 146146 107107 203203 159162 204204 205219 217223 177177 262264 210212 281287 228228 295307 +MR03 , 118120 137140 206212 126134 246254 110113 146148 107107 201201 147159 204204 207219 207219 183183 238262 192192 281283 228242 295301 +MR04 , 120120 140140 212214 122126 254254 110113 146146 107107 201201 159162 204204 205219 223223 177177 236264 210210 287287 226228 299299 +MR05 , 118120 137137 206212 118122 246246 110113 146146 107107 201201 159159 204204 207207 207219 177183 236248 192212 281283 228228 295301 +MR06 , 120120 140140 208214 118122 246246 110113 148148 107107 201201 153159 204224 191219 201217 183199 248262 192192 281281 224242 295299 +MR07 , 126126 140140 212214 112126 244252 110113 146150 107107 201201 147159 204230 191219 209217 179197 262262 192210 283295 228228 295323 +MR08 , 120120 140140 208212 112126 254254 110113 146146 107107 201201 147159 204226 191191 209217 183195 248262 192192 295299 228228 291295 +MR09 , 122126 137140 202206 112124 254256 110113 146146 107107 201201 159159 204224 199207 219227 185195 256258 192218 281281 226234 299301 +MR10 , 118126 137140 206208 120134 248260 113113 146150 107107 201201 147156 204224 191207 217217 181183 248262 192192 281293 228228 301301 +MR11 , 120122 131140 192212 122126 250254 113113 148152 107107 201201 147159 204204 191209 201209 177195 258262 210214 283299 226228 000000 +MR12 , 120126 137140 206210 126126 246252 113113 146146 107107 201201 159159 204226 191191 223223 177183 248248 210210 281283 228228 299307 +MR13 , 120126 137137 206206 122126 244252 113113 146146 107107 201201 159159 204208 207207 219223 177197 246250 192218 281283 226228 297307 +MR14 , 120120 137140 206214 124134 246246 113113 146148 107107 201201 156159 204226 191207 217219 183199 248250 210210 293299 228228 297301 +MR15 , 120120 137140 204214 118122 248254 110110 148148 107107 201201 159159 204204 207219 219219 181195 262262 192210 281299 228228 295303 +MR16 , 120120 140140 190212 118126 248254 110113 148148 107107 201201 159162 226226 191205 207217 183199 236250 192210 285295 228228 299309 +MR17 , 120126 137140 200212 112126 248254 107113 146146 107107 201201 159159 204232 203205 217219 195195 248264 192210 283287 228228 291323 +MR18 , 120126 140140 200210 112126 248254 107113 146148 107107 201201 147159 204226 191201 209217 177195 248262 192214 281293 228228 295309 +MR19 , 118124 137140 200208 112122 248248 110113 146150 107107 201201 147159 204226 191207 209219 195195 248262 210214 281281 228228 301307 +MR20 , 120126 137137 190208 112124 252252 113113 148150 107107 201201 159162 204218 193207 217219 183197 236250 192210 281293 228228 301309 +MR21 , 120126 137137 200204 112122 248248 110113 146148 107107 201201 147159 204218 189205 219223 177177 238264 192210 285293 228228 295301 +MR22 , 120120 140140 206212 122126 248254 110113 146150 107107 201201 147153 204218 205219 219219 181181 238262 192192 281293 228228 295299 +MR23 , 118120 140140 212214 122122 252254 107113 146148 107107 201201 159159 204230 219219 219219 195197 248264 192214 293299 228228 291323 +MR24 , 118120 140140 208212 122126 248254 110113 148148 107107 201201 159159 204204 205219 219223 177195 262264 210210 295295 228228 299301 +POP +EDEN01 , 124124 140140 000000 122134 246246 113113 146148 107107 201201 159162 222222 191197 207221 177193 242250 192192 271287 228228 299301 +EDEN02 , 000000 137140 208210 126128 236236 113113 148148 107107 201201 159159 204220 191197 217217 177183 250254 192214 283287 228228 293301 +EDEN03 , 124124 137140 208210 126126 248248 113113 148148 107107 201201 159159 222224 195197 217221 177177 242250 192192 281301 228228 301301 +EDEN05 , 124124 137140 208212 120122 246246 113113 148148 107107 201201 162162 204220 191193 223223 177177 248250 192192 295295 228228 303303 +EDEN06 , 122124 137140 206210 120136 246262 110113 148148 107107 201201 156159 204204 191191 217221 177179 248262 192210 287299 228228 291301 +EDEN07 , 120124 137143 194210 116122 236246 110110 146148 107107 201201 159159 204204 191199 217221 179199 248252 192196 283285 228236 309315 +EDEN09 , 120126 140143 200210 120128 236248 113113 148148 107107 201201 147159 216216 191197 217217 177179 250250 192210 281295 228228 295301 +EDEN10 , 120124 137140 210210 122128 236246 000000 148148 107111 201201 159162 000000 195207 217217 177179 250250 192210 271295 228228 299299 +EDEN11 , 124124 000000 210212 130134 246246 110110 148148 107107 203203 159162 204204 191193 217217 177177 000000 192210 281295 228228 289297 +EDEN13 , 120120 140140 210210 116116 246246 113113 146148 107107 201203 159165 204220 191191 217217 177183 236250 192210 279295 228228 291307 +EDEN14 , 120120 140143 212220 116118 246246 113113 148148 107107 201201 159165 204204 193193 217223 177177 248250 192192 281285 228228 307307 +EDEN15 , 118120 137140 204212 130134 246246 110113 148148 107107 201201 159162 204220 191217 217217 181195 250252 210214 281281 228228 297307 +EDEN17 , 120124 140140 204210 124134 248248 113113 148148 107107 201201 153159 204220 191197 217223 177193 242250 192192 283299 228228 295299 +EDEN18 , 118120 137140 204210 116136 246246 110113 148148 107107 201201 159159 204204 191195 217221 177183 248250 192210 281281 228228 299299 +Eden19 , 120126 137140 206206 122134 244244 110110 148148 107107 201201 159159 204224 000000 000000 179183 250256 192192 293295 000000 299301 +EDEN20 , 124126 140143 204210 120128 236246 113113 148148 107107 201201 147159 216220 189191 217217 177183 248248 192192 283299 228228 291295 +EDEN22 , 122126 140140 204206 120120 246254 110113 146148 107107 201201 159162 204204 189191 207221 177179 250250 192192 279295 228228 299299 +EDEN23 , 124126 000000 204210 118118 246262 107110 148148 107107 201201 159162 204222 191205 217219 183197 248250 192192 279279 228228 299301 +EDEN24 , 120124 137137 200204 120128 246248 107113 148148 107107 201201 159159 220220 191193 217217 177195 248254 192192 289299 228228 301301 +EDEN26 , 000000 137137 204212 116130 246248 113113 146148 107107 201201 153159 220220 191203 217219 177181 248250 192218 279287 228228 299301 +EDEN27 , 000000 137140 204206 120124 248250 110113 146148 107107 201201 159162 204220 191205 217223 177177 000000 192220 281283 228242 289299 +EDEN28 , 120124 140140 204210 116128 232246 113113 146148 107107 201201 153159 204204 191217 217217 179195 252254 192192 281295 228228 295299 +EDEN30 , 120126 140143 200210 128128 246246 110113 148148 107107 199201 159165 204220 191197 217221 177183 248248 192210 283289 228228 291295 +EDEN31 , 120124 140140 204212 118128 246246 113113 148148 107107 201201 159165 220230 197213 217223 177177 250250 192192 281295 228228 291295 +EDEN32 , 118120 137140 204212 128128 246246 110113 146148 107107 201201 147165 206230 195197 221223 177177 250250 192192 295305 228228 291299 +POP +Pen01 , 120122 140143 202202 122130 244254 110113 146148 107107 201201 159159 204204 191203 205223 185201 250250 192206 281285 228228 303303 +Pen02 , 122122 137143 202202 122130 244258 110113 148148 107107 203203 159159 204204 191199 205211 181185 250250 206206 281285 228234 291303 +Pen03 , 122128 137137 202208 116134 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137140 204212 132138 250250 113113 146148 107107 201203 159159 204220 191191 205215 189189 000000 192210 279301 228242 295301 +WG28 , 120122 140140 198212 122126 246254 110113 148148 107107 201201 153159 220220 191193 217223 195199 248262 192192 287293 228228 295295 +WG30 , 124126 140140 202204 130132 236250 113113 148148 107107 201201 159159 206206 193197 211219 187195 250252 200210 281287 228228 295297 +WG32 , 120120 137140 204212 122128 236254 113113 148148 107107 201201 159159 224226 191213 217217 179179 252256 192208 281287 228228 301303 +WGHerb , 118122 137140 202206 122134 248248 110110 146148 107111 201203 159159 204204 189191 000000 177179 246250 192192 283285 000000 299325 +POP +93.2058 , 120122 140143 206206 122134 244244 107113 148148 107111 201201 159159 204204 195201 207213 177195 244252 192200 281293 000000 000000 +93.2059 , 118120 137137 198204 122134 236236 113113 146148 107107 201201 159159 204204 000000 219223 177183 242250 192200 293299 000000 295301 +94.2123 , 120122 137140 198212 122134 244248 107113 146146 107107 201201 156156 204222 189189 223223 179191 252258 192198 281285 000000 303303 +94.2212 , 120126 140143 206212 122134 236236 113113 148148 107107 201201 159159 204220 191201 217223 181183 246246 192206 279295 000000 291325 +2001.324 , 122122 137140 200212 122134 246246 107113 148148 107107 201201 159159 204204 191201 209217 177183 238250 202210 287303 000000 297303 +2008.0001 , 120122 137140 204212 122134 236236 107113 146148 107107 201201 153159 204224 189189 205221 177183 244256 198198 281285 000000 297301 +5237 , 118122 137137 200210 122134 246248 110110 148148 107107 201201 159165 204204 199209 219225 181181 252254 198210 281301 228234 295313 +5242 , 120124 140140 214216 122134 244244 107113 148148 107111 201203 156159 204204 191191 207219 177181 250250 192192 281287 228228 291297 +5263 , 120120 000000 210214 122134 248252 107113 148148 107107 201201 156159 204206 191191 217217 181181 250252 192214 279285 228234 295305 +12265 , 118120 140140 200216 122134 246246 113113 146148 107107 201201 156159 204204 191191 217217 000000 250258 192192 285295 228228 297303 +45450 , 120126 140140 206208 122134 246258 110113 148148 107107 201203 159159 204204 189189 205221 181195 252252 192192 285287 228228 291297 +AdRTlB , 122126 137137 202216 122134 244248 107113 146148 107107 201203 156159 204222 201217 217223 177181 248250 206220 279281 228234 293303 +AP01030 , 120126 137140 204210 122134 248248 107113 148150 107107 201201 156159 204204 191201 207207 177177 244250 000000 281281 000000 299307 +AP0594 , 118120 137140 204206 122134 244252 107113 148148 107107 199201 159165 204204 191201 217217 177195 250252 192210 287295 228228 299299 +AUDAVIS.2008156 , 124124 137146 204204 122134 236246 110113 148148 107107 201201 159159 204204 205205 217223 181195 242252 198200 281299 234242 283291 +AUDAVIS.2009114A , 124124 140140 204206 122134 252254 107110 148148 107107 201203 153159 204206 201207 215217 000000 244252 210210 279281 228228 293297 +AUDAVIS.2009114B , 122124 140140 206210 122134 236252 110113 148148 107107 201201 153159 204206 207207 215217 187197 000000 192216 285289 228242 279299 +CHARLES.KEITH , 122124 140140 202206 122134 246254 107113 148148 107111 201201 153162 204206 201209 000000 165183 258258 198206 281285 228236 297297 +DukeLivingColl , 116124 134137 204208 122134 236254 107113 148148 107111 201201 159159 208208 201201 217225 181199 256256 192206 281283 228242 297297 +Morton94.2002x3 , 120124 137137 198206 122134 246252 110110 148148 107111 201201 153159 204222 191201 207217 177179 246258 198206 279285 228242 301307 +Morton95.2002x1 , 120126 137140 206210 122134 236248 113113 148148 107107 201201 153159 204220 191191 217217 177181 250250 192192 283293 226228 299301 +Morton95.2002x4 , 120122 137140 204206 122134 236244 113113 146148 107107 201201 159159 204222 191191 000000 177183 000000 192192 000000 000000 289297 +Morton99.2002x5 , 122124 140146 204208 122134 236248 107107 148148 107107 201201 156156 204204 191203 217219 181183 248252 000000 279291 234242 301303 +972A(Morton95.20 , 120126 140140 202210 122134 240248 107113 148148 107107 201201 159165 204222 189191 205205 177181 248250 214214 293293 000000 291291 +PEZANN , 120120 140140 206212 122134 244244 110113 148148 107107 201203 159159 204204 189203 217217 197197 238252 192192 283293 228228 301301 +SBG98.0221.1 , 120122 137140 200210 122134 236254 110113 146148 107107 201201 159159 204220 191193 207217 179179 250250 204210 283293 228228 295299 +SBG98.0221.2 , 120122 140146 192210 122134 244244 107113 148148 107107 201201 156159 204204 189201 205213 177183 252256 192198 281293 228234 291303 +SBG98.0221.3 , 000000 137140 202204 122128 244254 107113 148148 107111 201203 159165 204204 189209 205207 177181 248252 192198 279285 228234 295299 +SCBG.13M3 , 120126 137140 204208 122134 244254 000000 148148 107111 201203 159165 204204 189191 205205 177197 250258 192192 281299 228228 295301 +SCBG.13N2 , 120122 140140 200204 122134 236244 107113 146148 107107 201201 162162 204206 189191 205219 177195 244252 192192 287303 228228 000000 +StarhillArbLot1 , 120126 140140 202210 122134 240248 107113 148148 107107 201201 159165 000000 191191 201221 181189 252256 192210 281293 228228 293295 +StarhillArbLot2 , 118120 140140 198206 122134 234244 000000 000000 000000 000000 162162 206206 191199 000000 000000 000000 192210 000000 000000 000000 +973A(StarArbLot2 , 120124 137140 204210 122134 248248 113113 148148 107107 201201 156159 204204 191215 201221 181191 252256 192210 281293 228228 293295 +Taltree , 120126 137140 200208 122134 244244 107113 148148 107111 201203 159165 204204 191203 223225 177181 250254 192218 281285 228228 307307 +TIGY , 118120 137140 214214 122134 246246 107113 148148 111111 201203 156159 204220 191191 000000 177181 248250 192210 285287 228228 293305 +VStA1532.9253.41 , 120120 137140 200214 122134 244244 110110 146146 107107 201201 156162 204222 191195 205207 181191 248254 206210 281281 228228 301301 diff --git a/Qgeorgiana/Qg_wild.gen b/Qgeorgiana/Qg_wild.gen new file mode 100644 index 0000000..235f1d2 --- /dev/null +++ b/Qgeorgiana/Qg_wild.gen @@ -0,0 +1,256 @@ +"Quercus georgiana complete dataset all markers, wild (by pop) excluding NC (2 samp)" +FIR039 +FIR013 +FIR048 +FIR043 +GOT037 +PIE200 +FIR035 +VIT081 +VIT086 +PIE125 +FIR028 +QUi21a +QUm07a +QUf02a +QUC19a +QUE09a +QUC08a +QUG07a +QUH14a +POP +MR01 , 120120 140140 214214 112122 252254 110113 146148 107107 201201 159162 204204 191219 217219 177177 236262 192210 287299 226228 299299 +MR02 , 120120 140140 212214 122122 244254 110110 146146 107107 203203 159162 204204 205219 217223 177177 262264 210212 281287 228228 295307 +MR03 , 118120 137140 206212 126134 246254 110113 146148 107107 201201 147159 204204 207219 207219 183183 238262 192192 281283 228242 295301 +MR04 , 120120 140140 212214 122126 254254 110113 146146 107107 201201 159162 204204 205219 223223 177177 236264 210210 287287 226228 299299 +MR05 , 118120 137137 206212 118122 246246 110113 146146 107107 201201 159159 204204 207207 207219 177183 236248 192212 281283 228228 295301 +MR06 , 120120 140140 208214 118122 246246 110113 148148 107107 201201 153159 204224 191219 201217 183199 248262 192192 281281 224242 295299 +MR07 , 126126 140140 212214 112126 244252 110113 146150 107107 201201 147159 204230 191219 209217 179197 262262 192210 283295 228228 295323 +MR08 , 120120 140140 208212 112126 254254 110113 146146 107107 201201 147159 204226 191191 209217 183195 248262 192192 295299 228228 291295 +MR09 , 122126 137140 202206 112124 254256 110113 146146 107107 201201 159159 204224 199207 219227 185195 256258 192218 281281 226234 299301 +MR10 , 118126 137140 206208 120134 248260 113113 146150 107107 201201 147156 204224 191207 217217 181183 248262 192192 281293 228228 301301 +MR11 , 120122 131140 192212 122126 250254 113113 148152 107107 201201 147159 204204 191209 201209 177195 258262 210214 283299 226228 000000 +MR12 , 120126 137140 206210 126126 246252 113113 146146 107107 201201 159159 204226 191191 223223 177183 248248 210210 281283 228228 299307 +MR13 , 120126 137137 206206 122126 244252 113113 146146 107107 201201 159159 204208 207207 219223 177197 246250 192218 281283 226228 297307 +MR14 , 120120 137140 206214 124134 246246 113113 146148 107107 201201 156159 204226 191207 217219 183199 248250 210210 293299 228228 297301 +MR15 , 120120 137140 204214 118122 248254 110110 148148 107107 201201 159159 204204 207219 219219 181195 262262 192210 281299 228228 295303 +MR16 , 120120 140140 190212 118126 248254 110113 148148 107107 201201 159162 226226 191205 207217 183199 236250 192210 285295 228228 299309 +MR17 , 120126 137140 200212 112126 248254 107113 146146 107107 201201 159159 204232 203205 217219 195195 248264 192210 283287 228228 291323 +MR18 , 120126 140140 200210 112126 248254 107113 146148 107107 201201 147159 204226 191201 209217 177195 248262 192214 281293 228228 295309 +MR19 , 118124 137140 200208 112122 248248 110113 146150 107107 201201 147159 204226 191207 209219 195195 248262 210214 281281 228228 301307 +MR20 , 120126 137137 190208 112124 252252 113113 148150 107107 201201 159162 204218 193207 217219 183197 236250 192210 281293 228228 301309 +MR21 , 120126 137137 200204 112122 248248 110113 146148 107107 201201 147159 204218 189205 219223 177177 238264 192210 285293 228228 295301 +MR22 , 120120 140140 206212 122126 248254 110113 146150 107107 201201 147153 204218 205219 219219 181181 238262 192192 281293 228228 295299 +MR23 , 118120 140140 212214 122122 252254 107113 146148 107107 201201 159159 204230 219219 219219 195197 248264 192214 293299 228228 291323 +MR24 , 118120 140140 208212 122126 248254 110113 148148 107107 201201 159159 204204 205219 219223 177195 262264 210210 295295 228228 299301 +POP +EDEN01 , 124124 140140 000000 122134 246246 113113 146148 107107 201201 159162 222222 191197 207221 177193 242250 192192 271287 228228 299301 +EDEN02 , 000000 137140 208210 126128 236236 113113 148148 107107 201201 159159 204220 191197 217217 177183 250254 192214 283287 228228 293301 +EDEN03 , 124124 137140 208210 126126 248248 113113 148148 107107 201201 159159 222224 195197 217221 177177 242250 192192 281301 228228 301301 +EDEN05 , 124124 137140 208212 120122 246246 113113 148148 107107 201201 162162 204220 191193 223223 177177 248250 192192 295295 228228 303303 +EDEN06 , 122124 137140 206210 120136 246262 110113 148148 107107 201201 156159 204204 191191 217221 177179 248262 192210 287299 228228 291301 +EDEN07 , 120124 137143 194210 116122 236246 110110 146148 107107 201201 159159 204204 191199 217221 179199 248252 192196 283285 228236 309315 +EDEN09 , 120126 140143 200210 120128 236248 113113 148148 107107 201201 147159 216216 191197 217217 177179 250250 192210 281295 228228 295301 +EDEN10 , 120124 137140 210210 122128 236246 000000 148148 107111 201201 159162 000000 195207 217217 177179 250250 192210 271295 228228 299299 +EDEN11 , 124124 000000 210212 130134 246246 110110 148148 107107 203203 159162 204204 191193 217217 177177 000000 192210 281295 228228 289297 +EDEN13 , 120120 140140 210210 116116 246246 113113 146148 107107 201203 159165 204220 191191 217217 177183 236250 192210 279295 228228 291307 +EDEN14 , 120120 140143 212220 116118 246246 113113 148148 107107 201201 159165 204204 193193 217223 177177 248250 192192 281285 228228 307307 +EDEN15 , 118120 137140 204212 130134 246246 110113 148148 107107 201201 159162 204220 191217 217217 181195 250252 210214 281281 228228 297307 +EDEN17 , 120124 140140 204210 124134 248248 113113 148148 107107 201201 153159 204220 191197 217223 177193 242250 192192 283299 228228 295299 +EDEN18 , 118120 137140 204210 116136 246246 110113 148148 107107 201201 159159 204204 191195 217221 177183 248250 192210 281281 228228 299299 +Eden19 , 120126 137140 206206 122134 244244 110110 148148 107107 201201 159159 204224 000000 000000 179183 250256 192192 293295 000000 299301 +EDEN20 , 124126 140143 204210 120128 236246 113113 148148 107107 201201 147159 216220 189191 217217 177183 248248 192192 283299 228228 291295 +EDEN22 , 122126 140140 204206 120120 246254 110113 146148 107107 201201 159162 204204 189191 207221 177179 250250 192192 279295 228228 299299 +EDEN23 , 124126 000000 204210 118118 246262 107110 148148 107107 201201 159162 204222 191205 217219 183197 248250 192192 279279 228228 299301 +EDEN24 , 120124 137137 200204 120128 246248 107113 148148 107107 201201 159159 220220 191193 217217 177195 248254 192192 289299 228228 301301 +EDEN26 , 000000 137137 204212 116130 246248 113113 146148 107107 201201 153159 220220 191203 217219 177181 248250 192218 279287 228228 299301 +EDEN27 , 000000 137140 204206 120124 248250 110113 146148 107107 201201 159162 204220 191205 217223 177177 000000 192220 281283 228242 289299 +EDEN28 , 120124 140140 204210 116128 232246 113113 146148 107107 201201 153159 204204 191217 217217 179195 252254 192192 281295 228228 295299 +EDEN30 , 120126 140143 200210 128128 246246 110113 148148 107107 199201 159165 204220 191197 217221 177183 248248 192210 283289 228228 291295 +EDEN31 , 120124 140140 204212 118128 246246 113113 148148 107107 201201 159165 220230 197213 217223 177177 250250 192192 281295 228228 291295 +EDEN32 , 118120 137140 204212 128128 246246 110113 146148 107107 201201 147165 206230 195197 221223 177177 250250 192192 295305 228228 291299 +POP +Pen01 , 120122 140143 202202 122130 244254 110113 146148 107107 201201 159159 204204 191203 205223 185201 250250 192206 281285 228228 303303 +Pen02 , 122122 137143 202202 122130 244258 110113 148148 107107 203203 159159 204204 191199 205211 181185 250250 206206 281285 228234 291303 +Pen03 , 122128 137137 202208 116134 260260 110113 148148 107107 201201 159159 204204 189195 217221 181181 258258 192198 285285 228240 301303 +Pen05 , 118122 140140 202202 116122 244244 107113 148148 107111 201203 159159 204204 215215 205223 177179 250252 206206 281285 228228 289301 +Pen06 , 118118 137140 208208 116116 244250 107113 148148 107111 203203 159159 204204 199215 217217 179201 250252 192206 281285 228242 289309 +Pen07 , 118122 140140 202208 126130 244250 110113 146148 111111 201203 159159 204204 189215 205223 197201 250252 192192 281285 228244 291303 +Pen08 , 122122 137140 200210 122134 246262 000000 146148 107107 201201 159159 204204 191201 000000 179183 246256 192192 285305 000000 307307 +Pen10 , 118122 140140 202202 126126 244250 113113 146148 107107 000000 147159 204204 191191 205225 185197 250252 206206 285285 228244 291309 +Pen11 , 120124 140140 208208 116130 246248 107113 148148 111111 000000 153159 204210 191215 217223 179195 250250 192206 279281 234242 295303 +Pen12 , 120120 140140 202202 122122 252254 110113 146148 107111 201203 159159 204204 191191 205223 181197 250252 192206 281283 228234 291303 +Pen14 , 118120 137143 202212 116124 244248 110110 148148 111111 201201 159159 204204 191199 205219 177197 250252 192206 281285 228234 303303 +Pen15 , 118120 140143 202208 122126 244244 113113 148148 107111 201201 159159 204204 191215 217225 179179 250252 192206 281285 228242 289289 +Pen16 , 118122 137140 202212 120122 252252 110113 148148 107107 201201 159159 204204 199217 217221 197197 252252 192206 281281 240242 299303 +PEN17 , 118122 137140 204206 122134 244260 110113 146148 107107 201201 153159 204222 191191 217223 195201 250252 200200 285297 228242 291291 +Pen18 , 118122 140143 202202 122126 244254 110113 146148 107107 203203 159159 204204 191203 205217 179179 250250 206206 285285 228228 291291 +Pen19 , 118120 137137 210210 116124 244250 110113 146148 107107 201201 159159 204204 195203 205217 183197 250256 192192 281285 228242 291297 +Pen20 , 122122 137137 202210 116130 250250 110113 148148 107107 201201 159159 204210 195207 211223 179181 250250 206206 281297 228242 291307 +Pen21 , 118118 137140 202212 116122 250250 110113 148148 107107 000000 159159 204204 211215 205211 185197 252252 192206 281285 228228 291309 +Pen23 , 120122 140140 202202 122130 244244 107113 148148 107107 203203 159159 204204 191201 205205 177197 254260 206206 285285 228228 303309 +Pen24 , 120122 140140 202212 124130 244258 110113 146148 107111 201201 159159 204204 189191 205217 179181 250260 192192 281285 228242 303303 +Pen26 , 118124 137137 200206 116124 244248 107113 148148 107115 201203 159159 204204 195195 219219 183197 234244 196198 281285 228234 285297 +Pen27 , 120124 137143 200202 130130 244244 107113 148148 107111 201201 153159 204220 191195 219219 189197 244252 198206 281281 228242 285297 +Pen28 , 122126 137140 194202 122122 244252 107113 148148 107111 201201 147159 204220 195217 205211 185185 250250 192198 281281 228234 301303 +Pen30 , 118120 140140 202202 122122 244254 110113 146148 107107 201203 147159 204204 203203 205217 179185 250252 192206 281285 228234 297297 +Pen31 , 122122 140140 202202 122122 244254 110110 146148 107107 201201 147159 204204 191203 217217 179185 250260 192192 281285 228228 291297 +Pen32 , 120122 137140 202202 116126 244254 107113 148148 107107 201201 159159 204204 203207 205205 177197 250250 206206 281283 226228 301309 +POP +CB01 , 120124 000000 198210 116126 246262 110113 148148 107107 201201 156159 204222 189205 217227 165177 252254 192198 285285 228228 295297 +CB02 , 120124 137143 208210 124124 246246 110110 148148 107111 201201 156159 204204 191215 205219 183193 252256 192192 281293 226228 295299 +CB03 , 120126 137137 196208 122126 236246 110110 148148 107107 201201 156159 204226 215215 207217 177179 250256 192192 279293 228228 295299 +CB05 , 126126 137137 202210 118120 236246 113113 146148 107107 201201 156159 204220 000000 217217 187193 252252 202210 281291 228228 297307 +CB06 , 120120 140140 188204 124134 250262 113113 146148 107111 201203 153159 206206 199199 205217 181189 244250 192192 291295 228228 295299 +CB07 , 120126 137137 202210 122130 246250 113113 146148 107107 201203 156159 204224 191219 205205 179183 244252 192210 281285 228228 299299 +CB09 , 120124 137140 204212 124136 250262 113113 146146 107107 201201 156159 204206 191191 205217 183187 244250 192210 285285 228228 303309 +CB10 , 120126 140140 202212 122130 236250 113113 146148 107107 201203 156159 204204 189191 205217 179183 244252 202210 281281 234242 297297 +CB11 , 120126 137140 188210 120122 236246 113113 146148 107107 201205 159159 204224 199199 217227 177181 252256 192192 281291 228236 291299 +CB13 , 120122 137137 194202 116136 236250 107113 146148 107107 203203 153159 204204 199199 217217 183187 234244 198198 291295 228234 299305 +CB14 , 120124 140140 188200 122130 250250 113113 148148 107107 201203 159159 204204 199199 221227 177181 252256 198210 281295 228234 299307 +CB15 , 120120 140140 204212 124124 250250 113113 148148 111111 201201 156165 204206 191191 217217 179187 244250 192192 285295 228228 297307 +CB18 , 120126 137140 202212 118122 262262 113113 148148 107107 201203 156159 204204 191205 205217 177187 244250 192216 285291 228242 295297 +CB19 , 120126 140140 188212 120122 236262 107113 146146 107111 201201 156159 204206 191199 205205 181187 244244 192202 281295 228228 295295 +CB20 , 000000 137137 000000 122134 236246 113113 146148 107107 201203 159159 204204 191191 217227 177187 250260 192192 281285 000000 295299 +CB21 , 120120 137140 188212 120136 236250 113113 146148 107111 201203 153153 204206 191199 217217 181181 244250 192210 281295 228228 295295 +CB22 , 000000 137140 202212 000000 246262 113113 146146 107107 203205 162162 204206 205205 205219 183187 244244 192216 281285 234238 295297 +CB24 , 120120 137140 188210 108108 236236 113113 146148 107111 201201 159159 204204 199199 217217 181183 244250 192202 295295 228234 295295 +CB25 , 120120 137140 204206 000000 236248 113113 146148 107107 201201 156159 204204 191191 201219 177193 248252 210216 285291 228228 295295 +CB26 , 120120 140140 188210 000000 236246 113113 146148 107107 201203 159159 204204 199199 217217 179187 246250 192202 281295 228238 295299 +CB28 , 120126 137137 210212 000000 236250 113113 146148 107107 201203 159159 204206 191191 217227 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140140 202204 130132 236250 113113 148148 107107 201201 159159 206206 193197 211219 187195 250252 200210 281287 228228 295297 +WG32 , 120120 137140 204212 122128 236254 113113 148148 107107 201201 159159 224226 191213 217217 179179 252256 192208 281287 228228 301303 +WGHerb , 118122 137140 202206 122134 248248 110110 146148 107111 201203 159159 204204 189191 000000 177179 246250 192192 283285 000000 299325 diff --git a/README.md b/README.md deleted file mode 100644 index e709324..0000000 --- a/README.md +++ /dev/null @@ -1 +0,0 @@ -# IMLS_Safeguarding diff --git a/README.md.txt b/README.md.txt new file mode 100644 index 0000000..4978d93 --- /dev/null +++ b/README.md.txt @@ -0,0 +1,17 @@ +# This code will recreate all plots and all analyses for the paper "The optimal size of an ex situ +# conservation population: a comparison among 11 taxa in 5 genera" +# This project was made possible through the support of +# the Institute of Museum and Library Services [Grants MA-05-12-0336-12, MA-30-14-0123-14, MA-30-18-0273-18, and MG-30-16-0085-16] +# and the National Science Foundation (DEB 1050340, DBI 1203242 and DBI 1561346) +# Fieldwork was supported by +# the Plant Exploration Fund, the Association of Zoological Horticulture, SOS—Save Our Species (Grant 2012A-035), +# and the Mohamed bin Zayed Species Conservation Fund (Projects 0925331, 12254271, and 162512606). +# Code primarily written by S. Hoban, with small contributions or comments from E Spence and E Schumacher +# Note: some of this code was originally developed for the Flowers et al 2018 white ash genetic study + +In this folder you will find data and files for recreating results in the paper "The optimal size of an ex situ conservation population: a comparison among 11 taxa in 5 genera". Note to reviewers. Only five species are included in this zip file. The other files will be submitted to Dryad upon paper acceptance. These will be requested to be on embargo for one year. Nonetheless, all code should run for these five species with very minimal adjustment + +The data files are of the format "Gs_total.gen" and "Gs_wild.gen" where G is the genus initial and s is the taxa initial. For example "Qb_total.gen" for Quercus boyntonii. All files are in genpop format (thus are delimited by POP). "total" is all wild populations (each one as a separate pop) plus a population representing all ex situ accessions pooled together. "wild" is all wild populations only. Each data file is in a folder for that species (necessary because the sampling code will output a file that is named the same for all species so it has to be in its own folder to avoid being wiped each time as it loops over species. + +Run the sampling code and ex situ vs. in situ comparison by running the Spp_sampling_for_pub.R file +Once this is complete, run the plotting code by running Spp_plotting.R \ No newline at end of file diff --git a/Spp_plotting.R b/Spp_plotting.R new file mode 100644 index 0000000..ccfa892 --- /dev/null +++ b/Spp_plotting.R @@ -0,0 +1,624 @@ +# This code will recreate all plots and all analyses for the paper "The optimal size of an ex situ +# conservation population: a comparison among 11 taxa in 5 genera" +# This project was made possible through the support of +# the Institute of Museum and Library Services [Grants MA-05-12-0336-12, MA-30-14-0123-14, MA-30-18-0273-18, and MG-30-16-0085-16] +# and the National Science Foundation (DEB 1050340, DBI 1203242 and DBI 1561346) +# Fieldwork was supported by +# the Plant Exploration Fund, the Association of Zoological Horticulture, SOS—Save Our Species (Grant 2012A-035), +# and the Mohamed bin Zayed Species Conservation Fund (Projects 0925331, 12254271, and 162512606). +# Code primarily written by S. Hoban, with small contributions or comments from E Spence and E Schumacher +# Note: some of this code was originally developed for the Flowers et al 2018 white ash genetic study + +############################################################################### +# The code is arranged to first produce figures then run the stats +# The figures and tables are: +# Table 1: Attributes of each species- composed by hand, NOT in the code +# Table 2: genetic diversity actually captured in the botanic garden collections today along with collection size +# This is actually crated in the "sampling" R file - look for the "ex_vs_in_situ",n_drop_file,".csv" +# To actually make the table in the word doc did require moving numbers from the dr0 file into a table +# from the non dr0 file in Excel, using parentheses for those dr0 numbers +# Figure 1: Genetic diversity in current collections vs. size of current collections (one point per species) +# This is created in the code in this document- it reads in subsets of columns in Table 2 +# Figure 2: genetic diversity captured on number of samples (from simulated sampling) +# This is created in the code in this document, it uses the summ_results_tree file +# Table 3: collector gap +# This is created in the code in this document, it uses BOTH of the aforementioned docs (ex_situ_vs and summ_results) +# The stats are: +# Stats: ANOVA of genetic diversity captured and number of samples needed ~ genus +# Stats: regression of genetic diversity captured and number of samples needed ~ allele frequency summaries +# Stats: regression of genetic diversity captured and number of samples needed ~ FST summaries +# +# +# Supplemental +# +# It is assumed you have already run the "sampling" code file and thus you have +# files summ_results_tree and ex_situ_vs_in_situ as output of that code + + +#The following should always be run first- setwd, load libraries, set folder names and plot colors +library(adegenet); library(hierfstat) + +#Get working directory (only for sean) +which_comp<-getwd() + if (grepl("shoban",which_comp)) prefix_wd<-"C:/Users/shoban/Dropbox/Projects/IN_PROGRESS/IMLS_synthesis_analysis/" + if (grepl("shoban.DE",which_comp)) prefix_wd<-"C:/Users/shoban.DESKTOP-DLPV5IJ/Dropbox/Projects/IN_PROGRESS/IMLS_synthesis_analysis/" + if (grepl("home",which_comp)) prefix_wd<-"/home/user/Dropbox/Projects/IN_PROGRESS/IMLS_synthesis_analysis/" +setwd(prefix_wd) + +folder_names<-c("Hhannerae","Hwaimeae","Masheii","Mpyramidata","Pekmanii","Psargentii","Qboyntonii","Qgeorgiana","Qoglethorpensis","Zdecumbens","Zlucayana") +species_names<-c("Hibiscus w. subsp hannerae","Hibiscus w. subsp waimeae","Magnolia ashei","Magnolia pyramidata","Pseudopheonix ekmanii","Pseudopheonix sargentii","Quercus boyntonii","Quercus georgiana","Quercus oglethorpensis", "Zamia decumbens","Zamia lucayana") + +sp_colors<-c("palevioletred1","palevioletred1","limegreen","limegreen","mediumorchid3","mediumorchid3","dodgerblue3","dodgerblue3","dodgerblue3","orange","orange") +list_allele_cat<-c("global","glob_v_com","glob_com","glob_lowfr","glob_rare","reg_comm","loc_com_d1","loc_com_d2","loc_rare") + +num_reps<-75000 + + +##################################### +# FIGURE 1- COMPARE EX SITU AND IN SITU +# This figure is a simple plot of the current conservation of genetic diversity in the current collection sizes +# One point per species, and a log relationship across them +# The first chunk of code creates plots of all allele types and over Reduced and Full Datasets +# The second chunk of code is only the Reduced and only the two alleles shown in figure in paper +##################################### + +for (n_to_drop in c(0,2)){ + if (n_to_drop==2) n_drop_file<-""; if (n_to_drop==0) n_drop_file<-"_dr_0" + + species_names<-folder_names + + wild_results<-read.csv(paste("ex_vs_in_situ",n_drop_file,".csv",sep=""))[,-1] + setwd(paste(prefix_wd,"/Fig1_ex_vs_in/",sep="")) + pdf(file=paste("captured_ex_situ",n_drop_file,".pdf",sep=""),width=5,height=5) + for (i in 2:6){ + plot(wild_results[,11],as.numeric(wild_results[,i])*100,ylim=c(0,100), main="",xlab="number of plants in ex situ collections",ylab="percentage of alleles captured") + text(as.numeric(wild_results[,11]),as.numeric(wild_results[,i])*100+5,substr(wild_results[,1],1,2),cex=1,col=sp_colors) + #Fitting data + d <- as.data.frame(list(plants=wild_results[,11], gendiv=wild_results[,i]*100)) + #d<-rbind(c(0,0),d) + mod <- lm(gendiv ~ I(log(plants)), d) #Note: a square root relationship was tested and is ok but not as good as log + new.df <- data.frame(plants=seq(10,250,by=1)) + out <- predict(mod, newdata = new.df) + #plot(d,pch = 16, xlim = c(0,250), ylim = c(0,100)) + lines(unlist(c(new.df)), out, col = "grey", lwd=1.5) + text(193,10,paste("adj R2 =",round(as.numeric(summary(mod)[9]),2)),col="black") + } + dev.off(); setwd("..") + #interesting no global rare alleles for P ekmanii (considering the min freq) +} #close num to drop loop + +wild_results<-read.csv("ex_vs_in_situ.csv")[,-1] +pdf(file="captured_ex_situ_for_pub.pdf",width=9,height=5) +par(mfrow=c(1,2)) +for (i in c(2,5)){ + if (i==2) y_text<-"percentage of 'all alleles' captured"; if (i==5) y_text<-"percentage of 'low frequency alleles' captured" + plot(wild_results[,11],as.numeric(wild_results[,i])*100,ylim=c(0,100), main="",xlab="",ylab=y_text) + mtext(side=1,line=-2,"number of plants living in ex situ collections", outer=T) + text(as.numeric(wild_results[,11]),as.numeric(wild_results[,i])*100+5,substr(wild_results[,1],1,2),cex=1,col=sp_colors) + d <- as.data.frame(list(plants=wild_results[,11], gendiv=wild_results[,i]*100)) + mod <- lm(gendiv ~ I(log(plants)), d) #Note: a square root relationship was tested and is ok but not as good as log + new.df <- data.frame(plants=seq(10,250,by=1)) + out <- predict(mod, newdata = new.df) + lines(unlist(c(new.df)), out, col = "grey", lwd=1.5) + text(193,10,paste("adj R2 =",round(as.numeric(summary(mod)[9]),2)),col="black") + } +dev.off() +setwd("..") + + + + +############################################################## +# Figure 2: OVERLAY PLOTS OF SIMULATED SAMPLING, MULTIPLE SPECIES BY ALLELE +# +# This creates a single figure used in the paper, with two subpanels +# It shows the genetic diversity accumulation for all alleles +# Focusing on a 95% threshold target +# Panel A is Reduced Dataset and Panel B is Full Dataset +# Thus there is a loop over n_to_drop +############################################################ + +#NOTE COULD ADD GREY LINE TO THIS PLOT TO SHOW HOW LOW IT IS + +min_thresh<-95; y_lower<-90 # y_lower is the lower y axis limit for the plot +list_allele_cat<-c("global","glob_v_com","glob_com","glob_lowfr","glob_rare","reg_comm","loc_com_d1","loc_com_d2","loc_rare") + +setwd(paste(prefix_wd,"/Fig2_simulated_sampling_overlay_threshold/",sep="")) + +pdf(file=paste("bytrees_overlay_merged_t_",min_thresh,".pdf",sep=""),width=10, height=12) +par(mfrow=c(2,1)) +for (n_to_drop in c(2,0)){ + if (n_to_drop==0) { n_drop_file<-"_dr_0" ; main_title<-"(B) Full Dataset"} + if (n_to_drop==2) { n_drop_file<-""; main_title<-"(A) Reduced Dataset"} + + #calc_min will be a matrix to hold numbers for the minimum collection size thresholds for "sufficiency" + calc_min<-matrix(nrow=length(species_names),ncol=length(list_allele_cat)) + rownames(calc_min)<-c("H. w. hannerae","H. w. waimeae","M. ashei","M. pyramidata","P. ekmanii","P. sargentii","Q. boyntonii","Q. georgiana","Q. oglethorpensis","Z. decumbens","Z. lucayana") + colnames(calc_min)<-list_allele_cat + + i<-3 #all alleles (global) only + sp_colors<-c("palevioletred1","palevioletred1","limegreen","limegreen","mediumorchid3","mediumorchid3","dodgerblue3","dodgerblue3","dodgerblue3","orange","orange") #note this needs to be here because it is re-sorted below and needs to be reset + + for (sp in 1:length(folder_names)){ + + this_species<-folder_names[sp] + setwd(paste(prefix_wd,this_species,sep="")) + load(file=paste("summ_results_tree",n_drop_file,".R",sep="")); load(file="params_run.Rda") + + #optional if proportions- CAN DELETE THIS? + for (n in 1:num_reps) summ_results_tree[,i,1,n]<-t(t(summ_results_tree[,i,1,n])/summ_results_tree[length(summ_results_tree[,1,1,1]),i,1,n]) + #mean across reps + all_mean<-apply(summ_results_tree[,i,1,1:num_reps],1,mean)*100 + + if (sp==1) { + plot(all_mean,ylim=c(y_lower,100),type="l",lwd=4,xlim=c(0,250),xlab="number of plants (using simulated sampling)", + ylab="percentage of genetic variation", cex.lab=1.2,col=sp_colors[sp],main=main_title) + } else {lines(all_mean,lwd=4,col=sp_colors[sp])} + calc_min[sp,i-2]<-min(which(all_mean>min_thresh)) + } #end species loop + + #now just add text in rectangle for the figure legends with the numbers crossing 95% and line showing that threshold + min_to_plot<-sort(calc_min[,i-2],decreasing=T) + sp_colors<-sp_colors[order(calc_min[,i-2], decreasing=T)] + abline(h=95, lty=2, col="darkgrey") + rect(158,89.9,240,98.8,col=rgb(1,1,1,alpha=0.89)) ; text(200,98.5,"minimum to capture 95% of alleles") + for (sp in 1:length(folder_names)) text(200,(89.6+.75*sp),paste(names(min_to_plot)[sp],": ",min_to_plot[sp]),col=sp_colors[sp]) + +} #end to drop loop +dev.off(); setwd("..") + + +############################################################# +# OVERLAY PLOTS OF SIMULATED SAMPLING MULTIPLE SPECIES BY ALLELE # +# +# This will create four PDFs actually: each combination of threshold (70, 95%) and allele dropping choice (0 or 2) +# And it will go through all the allele types +# Thus it has more nested loops (n_to_drop, threshold, and allele category) +# This PDF is NOT in the publication, but is rather an expanded version of the Figure in the publication, with all results +# Some of which are in the Supplemental +############################################################ + +setwd(paste(prefix_wd,"/Fig2_simulated_sampling_overlay_threshold/",sep="")) +for (n_to_drop in c(0,2)){ + if (n_to_drop==0) n_drop_file<-"_dr_0" + if (n_to_drop==2) n_drop_file<-"" + + #thresholds for "sufficiency" + for (min_thresh in c(70,95)){ + + y_lower<-65; if (min_thresh==95) y_lower<-90 + + pdf(file=paste("bytrees_overlay",n_drop_file,"_t_",min_thresh,".pdf",sep=""),width=10, height=6) + calc_min<-matrix(nrow=length(species_names),ncol=length(list_allele_cat)) + rownames(calc_min)<-c("H. w. hannerae","H. w. waimeae","M. ashei","M. pyramidata","P. ekmanii","P. sargentii","Q. boyntonii","Q. georgiana","Q. oglethorpensis","Z. decumbens","Z. lucayana") + colnames(calc_min)<-list_allele_cat + + for (i in c(3,5,6,7,8)){ + + if (i==5|i==8) {x_ax_lim<-100; text_x<-80} else {x_ax_lim<-250; text_x<-200} + sp_colors<-c("palevioletred1","palevioletred1","limegreen","limegreen","mediumorchid3","mediumorchid3","dodgerblue3","dodgerblue3","dodgerblue3","orange","orange") + + for (sp in 1:length(folder_names)){ + + this_species<-folder_names[sp] + + load(file=paste(prefix_wd,this_species,"/summ_results_tree",n_drop_file,".R",sep="")) + + list_allele_cat<-c("global","glob_v_com","glob_com","glob_lowfr","glob_rare","reg_comm","loc_com_d1","loc_com_d2","loc_rare") + + #optional if proportions + for (n in 1:num_reps) summ_results_tree[,i,1,n]<-t(t(summ_results_tree[,i,1,n])/summ_results_tree[length(summ_results_tree[,1,1,1]),i,1,n]) + #mean across reps + all_mean<-apply(summ_results_tree[,i,1,1:num_reps],1,mean)*100 + + if (sp==1) { + plot(all_mean,ylim=c(y_lower,100),type="l",lwd=4,xlim=c(0,x_ax_lim),xlab="number of plants",ylab="percentage of genetic variation", + cex.lab=1.2,col=sp_colors[sp],main=paste(list_allele_cat[i-2]," alleleles")) + } else {lines(all_mean,lwd=4,col=sp_colors[sp])} + calc_min[sp,i-2]<-min(which(all_mean>min_thresh)) + } #end species loop + + #now just add text in rectangle and lines + min_to_plot<-sort(calc_min[,i-2], decreasing=T) + sp_colors<-sp_colors[order(calc_min[,i-2],decreasing=T)] + if (min_thresh==70) { + abline(h=70, lty=2, col="darkgrey") + rect(158,65.9,240,97.5,col=rgb(1,1,1,alpha=0.89)) ; text(text_x,96.0,"minimum to capture 70% of alleles") + } + if (min_thresh==95) { + abline(h=95, lty=2, col="darkgrey") + rect(158,89.9,240,98.8,col=rgb(1,1,1,alpha=0.89)) ; text(text_x,98.5,"minimum to capture 95% of alleles") + } + for (sp in 1:length(folder_names)) { + if (min_thresh==70) text(text_x,(65.6+2.5*sp),paste(names(min_to_plot)[sp],": ",min_to_plot[sp]),col=sp_colors[sp]) + if (min_thresh==95) text(text_x,(89.6+.75*sp),paste(names(min_to_plot)[sp],": ",min_to_plot[sp]),col=sp_colors[sp]) + } + + write.csv(calc_min,file=paste("min_for_",min_thresh,n_drop_file,".csv",sep="")) #make sure this works + } #end allele loop + + dev.off() + + } #end min thresh loop + +} #end to drop loop +setwd("..") + + + + +##################### +## TABLE 3- COLELCTOR GAP +## This will do two calculations: +## A- the number of samples to get the same % we have now (reduce sample size) +## B- the % we could get with the samples we have now (increase genetic capture) +##################### + + allele<-3 + +for (n_to_drop in c(0,2)){ + if (n_to_drop==0) n_drop_file<-"_dr_0" + if (n_to_drop==2) n_drop_file<-"" + min_p_needed<-vector(length=11) #min needed is the amount that current collections could be reduced to without losing diversity + + setwd(prefix_wd) + curr_ex_situ<-read.csv(file=paste0("ex_vs_in_situ",n_drop_file,".csv")) + collector_gap_res<-matrix(nrow=11,ncol=7) + + for (sp in 1:length(folder_names)){ + + this_species<-folder_names[sp] + load(file=paste(prefix_wd,this_species,"/summ_results_tree",n_drop_file,".R",sep="")) + + #part A ideal number of plants + #use the ex situ vs in situ table (read in above) and first take note of the current % conserved e.g. 71%, 95% (gd_current) + #then we want to find the number of samples needed to reach that amount of diversity under ideal sampling (use the summ_results) -> min_p_needed + #later we want to compare this ideal sampling minimum to the current sample size + + for (n in 1:num_reps) summ_results_tree[,allele,1,n]<-t(t(summ_results_tree[,allele,1,n])/summ_results_tree[length(summ_results_tree[,1,1,1]),allele,1,n]) + all_mean<-apply(summ_results_tree[,allele,1,1:num_reps],1,mean) #mean across reps + + #take the first row that exceeds the currently protected percentage + gd_current<-curr_ex_situ[sp,allele] + min_p_needed[sp]<-which(all_mean>gd_current)[1] + + #part B ideal genetic capture + #take the current number of samples- what is in ex situ collections + #we want to find what could ideally be conserved for that number- so simply get that row number in summ_results + + plants_current<-curr_ex_situ[sp,12] #the number of samples ex situ + #go to that line in the in situ results table + #to find the % captured, under ideal sampling, for the same number of plants currently held + gd_ideal<-all_mean[plants_current+1] + + collector_gap_res[sp,]<-c(folder_names[sp],length(summ_results_tree[,1,1,1]), plants_current, + min_p_needed[sp]-plants_current, min_p_needed[sp]/plants_current, + gd_ideal-gd_current, gd_ideal/gd_current) #changed 8 March for Paper Revision, Table 3 + } +collector_gap_res<-cbind(folder_names,collector_gap_res) #make sure this works +colnames(collector_gap_res)<-c("species", "species", "N ex situ samples", "N in situ garden samples", "reduction num garden plants", "proportional reduction garden", "diff genetic diversity from ideal", "increase in gen diversity") +write.csv(collector_gap_res,file=paste0("Table3_collector_gaps",n_drop_file,".csv")) + +} + + +################################### +# STATS: ANOVAS ON GENUS +# Here we are testing the influence of genus on three response variables +# CURRENT EX SITU VS IN SITU: Current genetic diversity conserved ex situ in collections today +# This is 8 ANOVAs (2 files to analyze and 4 allele categories) +# MINIMUM TO CATCH: Minimum sampling needed to achieve a sufficiency threshold (e.g. 70%, 95%) +# This is 16 ANOVAs (4 files to analyze and 4 allele categories) +# COLLECTOR GAP: The collector gap in terms of reduction in collection size and improved collection capture +# This is 4 ANOVAs (2 files to analyze and 2 ways of viewing the collector gap) +##################################### +setwd(prefix_wd) +library(broom) +extr_r_sq<-function(aov){ #code to extract R squared value + tidy_aov<-tidy(aov) + sum_squares_regression <- tidy_aov$sumsq[1]; sum_squares_residuals <- tidy_aov$sumsq[2] + R_squared <- sum_squares_regression / (sum_squares_regression + sum_squares_residuals) + R_squared +} + + # CURRENT EX SITU (VS IN SITU) # +files_for_minimum<-c("ex_vs_in_situ.csv","ex_vs_in_situ_dr_0.csv") +pval_ex_situ<-matrix(ncol=5,nrow=2); rsq_ex_situ<-matrix(ncol=5,nrow=2) +rownames(pval_ex_situ)<-files_for_minimum; colnames(pval_ex_situ)<-c("genus","all","comm","low_freq","rare") +for(f in 1:2){ + curr_ex_situ<-read.csv(file=files_for_minimum[f])[,-1] + curr_ex_situ[,1]<-substr(curr_ex_situ[,1],0,1) #replace first column with genus letter (for ANOVA) + curr_ex_situ<-curr_ex_situ[,c(1,2,4,5,6)] + curr_ex_situ[curr_ex_situ=="NaN"]<-NA; colnames(curr_ex_situ)<-c("genus","all","comm","low_freq","rare") + colnames(curr_ex_situ)[1]<-"genus" + for (i in 1:4) pval_ex_situ[f,i+1]<- as.numeric(unlist(summary(aov(curr_ex_situ[,i+1]~genus,data=curr_ex_situ))[[1]][5]))[1] + for (i in 1:4) rsq_ex_situ[f,i+1]<- extr_r_sq(aov(curr_ex_situ[,i+1]~genus,data=curr_ex_situ)) +} + + # MINIMUM_TO_CATCH # +files_for_minimum<-c("70.csv","95.csv","70_dr_0.csv","95_dr_0.csv") +pval_min_to_catch<-matrix(ncol=5,nrow=4); rsq_min_to_catch<-matrix(ncol=5,nrow=4) +rownames(pval_min_to_catch)<-files_for_minimum; colnames(pval_min_to_catch)<-c("genus","all","comm","low_freq","rare") +for(f in 1:4){ + min_to_catch<-read.csv(paste0("min_for_",files_for_minimum[f])) + min_to_catch[,1]<-substr(min_to_catch[,1],0,1) #replace first column with genus letter + min_to_catch<-min_to_catch[,c(1,2,4,5,6)] + min_to_catch[min_to_catch==Inf]<-NA; ; colnames(min_to_catch)<-c("genus","all","comm","low_freq","rare") + colnames(min_to_catch)[1]<-"genus" + for (i in 1:4) pval_min_to_catch[f,i+1]<- as.numeric(unlist(summary(aov(min_to_catch[,i+1]~genus,data=min_to_catch))[[1]][5]))[1] + for (i in 1:4) rsq_min_to_catch[f,i+1]<- extr_r_sq(aov(min_to_catch[,i+1]~genus,data=min_to_catch)) +} + + # COLLECTOR GAP # +pval_coll_gap<-matrix(ncol=2,nrow=2); rsq_coll_gap<-matrix(ncol=2,nrow=2) +rownames(pval_coll_gap)<-c("dr0","dr2"); colnames(pval_coll_gap)<-c("times_reduce","times_increase") +for (n_to_drop in c(0,2)){ + if (n_to_drop==0) {n_drop_file<-"_dr_0"; which_row<-1} + if (n_to_drop==2) {n_drop_file<-""; which_row<-2} + collector_gap_res<-read.csv(file=paste0("collector_gaps",n_drop_file,".csv")) + collector_gap_res<-collector_gap_res[,-1] + collector_gap_res[,1]<-substr(collector_gap_res[,1],0,1) #replace first column with genus letter + colnames(collector_gap_res)<-c("genus","n_insitu","n_exsitu","n_reduce","n_times_reduce","percent_inc","times_increase") + pval_coll_gap[[which_row,1]]<-summary(aov(n_times_reduce~genus,data=collector_gap_res))[[1]][5][[1]][1] + pval_coll_gap[[which_row,2]]<-summary(aov(times_increase~genus,data=collector_gap_res))[[1]][5][[1]][1] + rsq_coll_gap[[which_row,1]]<-extr_r_sq(aov(n_times_reduce~genus,data=collector_gap_res)) + rsq_coll_gap[[which_row,2]]<-extr_r_sq(aov(times_increase~genus,data=collector_gap_res)) +} + +write.csv(rbind(round(pval_ex_situ,3), + round(matrix(p.adjust(pval_ex_situ,method="BH"), + dimnames=list(paste0("adj.",rownames(pval_ex_situ)),colnames(pval_ex_situ)),ncol=ncol(pval_ex_situ)),3)), + file="p_values/pvals_AOV_ex_situ_current.csv") +write.csv(rbind(round(pval_min_to_catch,3), + round(matrix(p.adjust(pval_min_to_catch,method="BH"), + dimnames=list(paste0("adj.",rownames(pval_min_to_catch)),colnames(pval_min_to_catch)),ncol=ncol(pval_min_to_catch)),3)), + file="p_values/pvals_AOV_min_to_reach_thresh.csv") +write.csv(rbind(round(pval_coll_gap,3), + round(matrix(p.adjust(pval_coll_gap,method="BH"), + dimnames=list(paste0("adj.",rownames(pval_coll_gap)),colnames(pval_coll_gap)),ncol=ncol(pval_coll_gap)),3)), + file="p_values/pvals_AOV_collector_gap.csv") + + + +############################################################################## +# STATS: REGRESSIONS WITH FST +# Here we test the influence of the mean, SD, max and min of each species pairwise FSTs on the genetic capture etc. +# FST is a quantitative, continuous variable so we use linear regression +# As above, we have three sets of tests +# CURRENT EX SITU VS IN SITU: Current genetic diversity conserved ex situ in collections today +# This is 32 regressions (2 files to analyze (Full/ Red), 4 allele categories, and 4 summaries of FST) +# MINIMUM TO CATCH: Minimum sampling needed to achieve a sufficiency threshold (e.g. 70%, 95%) +# This is 64 regressions (2 files to analyze (Full/ Red), 4 allele categories, 2 min thresholds and 4 summaries of FST) +# COLLECTOR GAP: The collector gap in terms of reduction in collection size and improved collection capture +# This is 16 regressions (2 files to analyze (Full/ Red), 2 types of collector gap, and 4 summaries of FST) +############################################################################### + + +setwd(prefix_wd) +#Places to put FST summary statistics +sp_summ_fst<- matrix(nrow=length(folder_names),ncol=4); rownames(sp_summ_fst)<-folder_names +colnames(sp_summ_fst)<-c("PwFst","SD","Max","Min") + +##generate Fst values and input into a table +for (sp in 1:length(folder_names)){ + this_species<-folder_names[sp]; setwd(paste("./",this_species,sep="")) + Spp_genind<-read.genepop(paste(substr(this_species,1,2),"_wild.gen",sep=""),ncode=3); print(table(Spp_genind@pop)) + sm_fst<-as.matrix(pairwise.fst(Spp_genind)); sm_fst[sm_fst==0]<-NA + Qsp_pwfst<-mean(sm_fst,na.rm=T) + print(this_species); print(sm_fst) + sp_summ_fst[sp,1:4]<-c(mean(Qsp_pwfst), sd(sm_fst, na.rm = T), max(sm_fst, na.rm = T), min(sm_fst, na.rm = T)) + setwd("..") #Done- double checked FSTs compare to magnolia ms (ashei) and oaks paper + } + + + par(mfrow=c(3,3)) +results_min<-matrix(nrow=1,ncol=4) #all have four columns because that is the number of summary stats for FST (mean,sd,max,min) +results_capture<-matrix(nrow=1,ncol=4) +results_gap<-matrix(nrow=1,ncol=4) + +for (n_to_drop in c(0,2)){ + if (n_to_drop==0) n_drop_file<-"_dr_0" + if (n_to_drop==2) n_drop_file<-"" + + #regressions of pairwise Fst with current ex situ genetic capture + gen_cap<-read.csv(paste0("ex_vs_in_situ",n_drop_file,".csv"))[,-1]; gen_cap[gen_cap=="Inf"]<-NA + reg_pval<-matrix(nrow=5, ncol=4); reg_r2<-matrix(nrow=5, ncol=4) + + for (ss in 1:4){ #this is a loop over min, max, mean and sd + for (at in c(2,4:6)){ #this is the loop over each allele type + reg_pval[at-1,ss]<-((summary(lm(gen_cap[,at] ~ sp_summ_fst[,ss]))$coefficients[,4]))[2] + reg_r2[at-1,ss]<-summary(lm(gen_cap[,at] ~ sp_summ_fst[,ss]))$r.squared + } + } + colnames(reg_pval)<-colnames(sp_summ_fst); colnames(reg_r2)<-colnames(sp_summ_fst) + reg_pval<-reg_pval[-2,]; reg_2<-reg_r2[-2,] + rownames(reg_pval)<-paste(c("global", "common", "low freq", "rare"),n_drop_file) + results_capture<-rbind(results_capture,reg_pval) + + ##regression of pairwise Fst with min to reach sufficiency thresholds for allele sampling + for (min_thresh in c(70,95)){ + + min_samp<-read.csv(paste0("min_for_",min_thresh,n_drop_file,".csv")); min_samp[min_samp=="Inf"]<-NA + reg_pval<-matrix(nrow=5, ncol=4); reg_r2<-matrix(nrow=5, ncol=4) + + for (ss in 1:4){ #this is a loop over min, max, mean and sd + for (at in c(2,4:6)){ #this is the loop over each allele type + reg_pval[at-1,ss]<-((summary(lm(min_samp[,at] ~ sp_summ_fst[,ss]))$coefficients[,4]))[2] + reg_r2[at-1,ss]<-summary(lm(min_samp[,at] ~ sp_summ_fst[,ss]))$r.squared + if (reg_pval[at-1,ss]<0.05) plot(min_samp[,at], sp_summ_fst[,ss],main=paste(n_drop_file,"thresh",min_thresh,"allele type", at), + ylab=colnames(sp_summ_fst)[ss]) + } + } + colnames(reg_pval)<-colnames(sp_summ_fst); colnames(reg_r2)<-colnames(sp_summ_fst) + reg_pval<-reg_pval[-2,]; reg_2<-reg_r2[-2,] + rownames(reg_pval)<-paste(c("global", "common", "low freq", "rare"),paste(n_drop_file,"thresh",min_thresh)) + results_min<-rbind(results_min,reg_pval) + } + + ##regressions of pairwise FST for collector gap calculation + collector_gap_res<-read.csv(file=paste0("collector_gaps",n_drop_file,".csv")) + collector_gap_res<-collector_gap_res[,-1] + reg_pval<-matrix(nrow=2, ncol=4); reg_r2<-matrix(nrow=2, ncol=4) + + for (ss in 1:4){ + reg_pval[1,ss]<-((summary(lm(collector_gap_res[,6] ~ sp_summ_fst[,ss]))$coefficients[,4]))[2] + reg_r2[1,ss]<-summary(lm(collector_gap_res[,6] ~ sp_summ_fst[,ss]))$r.squared + reg_pval[2,ss]<-((summary(lm(collector_gap_res[,8] ~ sp_summ_fst[,ss]))$coefficients[,4]))[2] + reg_r2[2,ss]<-summary(lm(collector_gap_res[,8] ~ sp_summ_fst[,ss]))$r.squared + } + colnames(reg_pval)<-colnames(sp_summ_fst); colnames(reg_r2)<-colnames(sp_summ_fst) + rownames(reg_pval)<-paste(c("times_reduce","percent_increas"),paste(n_drop_file,"thresh",min_thresh)) + results_gap<-rbind(results_gap,reg_pval) + +} +#print raw p value results and p value correction + +write.csv(rbind(round(results_capture,3), + round(matrix(p.adjust(results_capture,method="BH"), + dimnames=list(paste0("adj.",rownames(results_capture)),colnames(results_capture)),ncol=ncol(results_capture)),3)), + file="p_values/pvals_reg_fst_ex_situ_current.csv") +write.csv(rbind(round(results_min,3), + round(matrix(p.adjust(results_min,method="BH"), + dimnames=list(paste0("adj.",rownames(results_min)),colnames(results_min)),ncol=ncol(results_min)),3)), + file="p_values/pvals_reg_fst_min_to_reach_thresh.csv") +write.csv(rbind(round(results_gap,3), + round(matrix(p.adjust(results_gap,method="BH"), + dimnames=list(paste0("adj.",rownames(results_gap)),colnames(results_gap)),ncol=ncol(results_gap)),3)), + file="p_values/pvals_reg_fst_collector_gap.csv") + + + + +###################################### +# STATS: Regressions on properties of the Allele freq histograms +# Here we test the influence of properties of the allele frequency spectrum (basically proportion of rare alleles, +# as you'd see looking at a frequency histogram) on the genetic capture etc. +# proportion of alleles below a given frequency (0.1, 0.05, 0.01, 0.005) will be our predictor variable +# this is a quantitative, continuous variable so we use linear regression +# As above, we have three sets of tests +# CURRENT EX SITU VS IN SITU: Current genetic diversity conserved ex situ in collections today +# This is 32 regressions (2 files to analyze (Full/ Red), 4 allele categories, and 4 summaries of allele freqs) +# MINIMUM TO CATCH: Minimum sampling needed to achieve a sufficiency threshold (e.g. 70%, 95%) +# This is 64 regressions (2 files to analyze (Full/ Red), 4 allele categories, 2 min thresholds and 4 summaries of allele freqs) +# COLLECTOR GAP: The collector gap in terms of reduction in collection size and improved collection capture +# This is 16 regressions (2 files to analyze (Full/ Red), 2 types of collector gap, and 4 summaries of allele freqs) +# +# NOTE: The variables for results matrices (results_gap, results_capture, and results_min) are the same as those from above code +# It was easy to jut copy and re-use them so just be careful- these are not totally unique to this section +############################################################################### + +##################################### + +#This will go through each species and make allele frequency histograms as well as report proportion of alleles in bins +#below 0.05, 0.01, and 0.005 frequency, and save this table as .csv +setwd(prefix_wd) + +#This needed simply to know which populations are "wild" +region_makeup_list<-list(list(1:2,3:4),list(1:2,3),list(1,2),list(1:2,3:4),list(1,2),list(1:2,3),list(1:2,3,4,5:9),list(1:2,3,4,5:10),list(1:2,3,4,5:8),list(1,2),list(1:2,3)) +#Place to store results- columns are types of allele, rows are species, elements are the proportion of alleles that fall below a freq threshold +allele_freq_counts<-matrix(nrow=length(folder_names),ncol=4); rownames(allele_freq_counts)<-folder_names +colnames(allele_freq_counts)<-c("f_0.005","f_0.01","f_0.05","f_0.1") +pdf("allele_freq_hist.pdf",height=10,width=14) + +for (sp in 1:length(folder_names)){ + this_species<-folder_names[sp] + Spp_tot_genind<-read.genepop(paste(prefix_wd,this_species,"/",substr(this_species,1,2),"_total.gen",sep=""),ncode=3) + + wild_p<-unlist(region_makeup_list[[sp]]); n_ind_W<-sum(table(Spp_tot_genind@pop)[wild_p]) + Spp_tot_genpop<-genind2genpop(Spp_tot_genind) + #Get the frequencies, and get the total number of alleles- this will allow calculating how many alleles are below a frequency + wild_all_freqs<-colSums(Spp_tot_genpop[wild_p]@tab,na.rm=T)/(n_ind_W*2) + total_num_alleles<-length(Spp_tot_genpop[wild_p]@tab[1,]) + + #plots of allele frequency histograms + par(fig = c(0,1,0,1)) + hist(sort(wild_all_freqs),breaks=seq(0,1,by=.01),xlim=c(0,.15),main=paste0("allele freq histogram for ",species_names[sp]), xlab="allele frequency",ylab="number alleles in that frequency"); abline(v=c(0.01,0.05),col="red") + par(fig = c(0.4,1, 0.4, 1), new = T) + hist(sort(wild_all_freqs),breaks=seq(0,1,by=.02),main="",ylab="",xlab="") + + #calculating how many alleles are below a frequency + allele_freq_counts[sp,1:4]<-c((sum(wild_all_freqs<0.005)/total_num_alleles),(sum(wild_all_freqs<0.01)/total_num_alleles), + (sum(wild_all_freqs<0.05)/total_num_alleles), (sum(wild_all_freqs<0.1)/total_num_alleles)) +} +dev.off() +write.csv(allele_freq_counts,"allele_freq_counts_by_spp.csv") + + + par(mfrow=c(3,3)) +results_min<-matrix(nrow=1,ncol=4) #all have four columns because that is the number of summary stats of the allele freqs +results_capture<-matrix(nrow=1,ncol=4) +results_gap<-matrix(nrow=1,ncol=4) + +for (n_to_drop in c(0,2)){ + if (n_to_drop==0) n_drop_file<-"_dr_0" + if (n_to_drop==2) n_drop_file<-"" + + #regressions of prop alleles below thresholds with current ex situ genetic capture + gen_cap<-read.csv(paste0("ex_vs_in_situ",n_drop_file,".csv"))[,-1]; gen_cap[gen_cap=="Inf"]<-NA + reg_pval<-matrix(nrow=5, ncol=4); reg_r2<-matrix(nrow=5, ncol=4) + + for (ss in 1:4){ #this is a loop over min, max, mean and sd + for (at in c(2,4:6)){ #this is the loop over each allele type + reg_pval[at-1,ss]<-((summary(lm(gen_cap[,at] ~ allele_freq_counts[,ss]))$coefficients[,4]))[2] + reg_r2[at-1,ss]<-summary(lm(gen_cap[,at] ~ allele_freq_counts[,ss]))$r.squared + } + } + colnames(reg_pval)<-colnames(allele_freq_counts); colnames(reg_r2)<-colnames(allele_freq_counts) + reg_pval<-reg_pval[-2,]; reg_2<-reg_r2[-2,] + rownames(reg_pval)<-paste(c("global", "common", "low freq", "rare"),n_drop_file) + results_capture<-rbind(results_capture,reg_pval) + + ##regression of prop alleles below thresholds with min to reach sufficiency thresholds for allele sampling + for (min_thresh in c(70,95)){ + + min_samp<-read.csv(paste0("min_for_",min_thresh,n_drop_file,".csv")); min_samp[min_samp=="Inf"]<-NA + reg_pval<-matrix(nrow=5, ncol=4); reg_r2<-matrix(nrow=5, ncol=4) + + for (ss in 1:4){ #this is a loop over min, max, mean and sd + for (at in c(2,4:6)){ #this is the loop over each allele type + reg_pval[at-1,ss]<-((summary(lm(min_samp[,at] ~ allele_freq_counts[,ss]))$coefficients[,4]))[2] + reg_r2[at-1,ss]<-summary(lm(min_samp[,at] ~ allele_freq_counts[,ss]))$r.squared + if (reg_pval[at-1,ss]<0.05) plot(min_samp[,at], allele_freq_counts[,ss],main=paste(n_drop_file,"thresh",min_thresh,"allele type", at), + ylab=colnames(allele_freq_counts)[ss]) + } + } + colnames(reg_pval)<-colnames(allele_freq_counts); colnames(reg_r2)<-colnames(allele_freq_counts) + reg_pval<-reg_pval[-2,]; reg_2<-reg_r2[-2,] + rownames(reg_pval)<-paste(c("global", "common", "low freq", "rare"),paste(n_drop_file,"thresh",min_thresh)) + results_min<-rbind(results_min,reg_pval) + } + + ##regressions of prop alleles below thresholds for collector gap calculation + collector_gap_res<-read.csv(file=paste0("collector_gaps",n_drop_file,".csv")) + collector_gap_res<-collector_gap_res[,-1] + reg_pval<-matrix(nrow=2, ncol=4); reg_r2<-matrix(nrow=2, ncol=4) + + for (ss in 1:4){ + reg_pval[1,ss]<-((summary(lm(collector_gap_res[,6] ~ allele_freq_counts[,ss]))$coefficients[,4]))[2] + reg_r2[1,ss]<-summary(lm(collector_gap_res[,6] ~ allele_freq_counts[,ss]))$r.squared + reg_pval[2,ss]<-((summary(lm(collector_gap_res[,8] ~ allele_freq_counts[,ss]))$coefficients[,4]))[2] + reg_r2[2,ss]<-summary(lm(collector_gap_res[,8] ~ allele_freq_counts[,ss]))$r.squared + } + colnames(reg_pval)<-colnames(allele_freq_counts); colnames(reg_r2)<-colnames(allele_freq_counts) + rownames(reg_pval)<-paste(c("times_reduce","percent_increas"),paste(n_drop_file,"thresh",min_thresh)) + results_gap<-rbind(results_gap,reg_pval) + +} + +write.csv(rbind(round(results_capture,3), + round(matrix(p.adjust(results_capture,method="BH"), + dimnames=list(paste0("adj.",rownames(results_capture)),colnames(results_capture)),ncol=ncol(results_capture)),3)), + file="p_values/pvals_reg_af_ex_situ_current.csv") +write.csv(rbind(round(results_min,3), + round(matrix(p.adjust(results_min,method="BH"), + dimnames=list(paste0("adj.",rownames(results_min)),colnames(results_min)),ncol=ncol(results_min)),3)), + file="p_values/pvals_reg_af_min_to_reach_thresh.csv") +write.csv(rbind(round(results_gap,3), + round(matrix(p.adjust(results_gap,method="BH"), + dimnames=list(paste0("adj.",rownames(results_gap)),colnames(results_gap)),ncol=ncol(results_gap)),3)), + file="p_values/pvals_reg_af_collector_gap.csv") + round(matrix(p.adjust(results_capture,method="BH"),ncol=4,dimnames=list(rownames(results_capture),colnames(results_capture))),2) + round(matrix(p.adjust(results_min,method="BH"),ncol=4,dimnames=list(rownames(results_min),colnames(results_min))),2) + round(matrix(p.adjust(results_gap,method="BH"),ncol=4,dimnames=list(rownames(results_gap),colnames(results_gap))),2) + + diff --git a/Spp_sampling_for_pub.r b/Spp_sampling_for_pub.r new file mode 100644 index 0000000..248b51a --- /dev/null +++ b/Spp_sampling_for_pub.r @@ -0,0 +1,206 @@ +# This code will recreate all plots and all analyses for the paper "The optimal size of an ex situ +# conservation population: a comparison among 11 taxa in 5 genera" +# This project was made possible through the support of +# the Institute of Museum and Library Services [Grants MA-05-12-0336-12, MA-30-14-0123-14, MA-30-18-0273-18, and MG-30-16-0085-16] +# and the National Science Foundation (DEB 1050340, DBI 1203242 and DBI 1561346) +# Fieldwork was supported by +# the Plant Exploration Fund, the Association of Zoological Horticulture, SOS—Save Our Species (Grant 2012A-035), +# and the Mohamed bin Zayed Species Conservation Fund (Projects 0925331, 12254271, and 162512606). +# Code primarily written by S. Hoban, with small contributions or comments from E Spence and E Schumacher +# Note: some of this code was originally developed for the Flowers et al 2018 white ash genetic study + +###################################################################### + +# There are three sections in this file: Prep work, Part 1, and Part 2. They are explained below +# To run this you will need a folder for each species and the files "Sp_total.gen" and "Sp_wild.gen" +# Within each folder, where Sp stands for species name, for example Qboyntonii or Mpyramidata +# Thus you have 11 folders (for 11 species) and withing each folder two gen data files +# +# SUMMARY PREP +# loads in libraries, defines species list (which is also the list of folders the data are found in) +# +# SUMMARY PART 1: Code for testing different collection sizes (number of trees) +# +# There are several loops. +# The outer loop is over the two options of what kind of rare alleles to consider +# drop zero is to not drop any allles; drop 2 is to drop alleles present in two or less copies +# The next loop is over the number of species (e.g. eleven species +# Within this loop it loads in the data file (all in situ populations) and categorizes all alleles existing in the datasets +# e.g. as "global", "very common" etc. The file does NOT include ex situ individuals, only in situ (wild) +# The next loop is the actual sampling, which is actually another nested loop +# There are a certain number of reps to include stochasticity (some thousands, usually) +# For each rep, there is a loop over all possible numbers of trees, randomly, up through the total population size +# For every sampling effort, for every rep, for every species, it records the +# number of alleles captured in that set of trees +# This will later be converted to a proportion of genetic diversity and will be used for plotting all results, +# e.g how much genetic diversity is gained by adding more samples (separate .Rfile) +# There will be two output files- a "summ_results_tree.R". and a "summ_results_tree_dr_0.R" file +# Each of these will be a 4 dimensional array with dimensions +# (number of trees in the wild) x (number of allele categories+2) x (1) x (number of reps) +# Note there are 9 allele categories in this code even though only 5 will be used in this paper- +# the remaining four are for local and regional alleles that COULD be examined in future work +# Note also the first two columns in the array are blank; an example is below +# The columns are (blank) (blank) (global alleles captured) (very common) (common) (low freq) (rare) +# [2,] NA NA 36 24 32 12 0 (ignore rest) +# [3,] NA NA 47 23 33 24 0 (ignore rest) +# +# SUMMARY PART 2: Code for calculating current allele capture + +# This has a similar loop structure over n_to_drop and species as noted in Part 1 +# However it is reading in files that are all wild populations plus all ex situ individuals merged into one population +# And similar to above it categorizes alleles into categories +# And it is simply counting the number of alleles total and then the number captured in the ex situ population. +# It records results in ex_situ_vs_in_situ.csv a single spreadsheet type file +# +# The code can be run using parallel processing or not +# It is currently set up to run parallel processing on 24 processors +# if NOT using this, just comment out the foreach and uncomment out the for loop code adjacent +# +#################################################################################################################### + + +##################### +# PREP WORK +##################### + +library(adegenet) +library(parallel); library(doParallel) #will load foreach +library(abind) + +#source("C:/Users/shoban/Dropbox/Projects/IN_PROGRESS/Oak_popgen_analyses/Fa_sample_funcs.R") +source("/home/user/Dropbox/Projects/IN_PROGRESS/Oak_popgen_analyses/Fa_sample_funcs.R") +#source("C:/Users/shoban.DESKTOP-DLPV5IJ/Dropbox/Projects/IN_PROGRESS/Oak_popgen_analyses/Fa_sample_funcs.R") + +species_names<-c("Hhannerae","Hwaimeae","Masheii","Mpyramidata","Pekmanii","Psargentii","Qboyntonii","Qgeorgiana","Qoglethorpensis","Zdecumbens","Zlucayana") +region_makeup_list<-list(list(1:2,3:4),list(1:2,3),list(1,2),list(1:2,3:4),list(1,2),list(1:2,3),list(1:2,3,4,5:9),list(1:2,3,4,5:10),list(1:2,3,4,5:8),list(1,2),list(1:2,3)) +alleles_existing_by_sp<-matrix(nrow=length(species_names),ncol=9) + + +########################################################## +# PART 1- SAMPLING IN SITU POPS FOR NUMBER OF TREES +########################################################### + +#This will run over a loop of "Include all alleles (n_to_drop=0)" and "Include only alleles present in more than two copies (n_to_drop=2)" +for (n_to_drop in c(0,2)){ + if (n_to_drop==2) n_drop_file<-"" + if (n_to_drop==0) n_drop_file<-"_dr_0" + +#################################### + +for (sp in 1:length(species_names)){ + this_species<-species_names[sp] +# setwd(paste("C:/Users/shoban.DESKTOP-DLPV5IJ/Dropbox/Projects/IN_PROGRESS/Oak_popgen_analyses/",this_species,sep="")) +# setwd(paste("C:/Users/shoban/Dropbox/Projects/IN_PROGRESS/Oak_popgen_analyses/",this_species,sep="")) + setwd(paste("/home/user/Dropbox/Projects/IN_PROGRESS/Oak_popgen_analyses/",this_species,sep="")) + Spp_genind<-read.genepop(paste(substr(this_species,1,2),"_wild.gen",sep=""),ncode=3); print(table(Spp_genind@pop)) + Spp_genpop<-genind2genpop(Spp_genind); Spp_genind_sep<-seppop(Spp_genind) + max_num_trees<-max_num_trees_vect[sp]; region_makeup<-region_makeup_list[[sp]] + #########################################3 + + n_pops<-length(levels(Spp_genind@pop)) + n_total_indivs<- length(Spp_genind@tab[,1]) + n_ind_p_pop<-table(Spp_genind@pop) + allele_freqs<-colSums(Spp_genpop@tab)/(n_total_indivs*2) + num_reps<-75000 + + list_allele_cat<-c("global","glob_v_com","glob_com","glob_lowfr","glob_rare","reg_rare","loc_com_d1","loc_com_d2","loc_rare") + + ####################################################### + #----DETERMINE WHAT ALLELES FALL IN WHAT CATEGORIES---# + ####################################################### + allele_cat<-get.allele.cat(Spp_genpop, region_makeup, 2, n_ind_p_pop,n_drop=n_to_drop) + #glob; glob_v_com; glob_com; glob_lowfr; glob_rare + #reg_com_int; loc_com_d1; loc_com_d2; loc_rare + #Beware of NAs + for (i in 1:9) alleles_existing_by_sp[sp,i]<- (sum((allele_cat[[i]])>0,na.rm=T)) + #!!!RESULT!!!- HOW MANY ALLELES IN EACH CATEGORY + #proportion rare + #alleles_existing_by_sp[,5]/alleles_existing_by_sp[,1] + + + cl <- makeCluster(24) # create a cluster with X cores + registerDoParallel(cl) # register the cluster + + + ######################################################### + #--JUST BY SAMPLING NUMBER OF TREES --# + ######################################################### + + summ_results_tree<-array(dim=c(nrow(Spp_genind@tab)-1,11,num_scen,num_reps)) + #for (nrep in 1:num_reps) { #if not parallel comment IN + temp<-foreach(nrep=1:num_reps) %dopar% { #if not parallel comment OUT + alleles<-matrix(nrow=nrow(Spp_genind@tab)-1,ncol=length(allele_freqs)) + #For number of rows minus one + for (t in 2:(nrow(Spp_genind@tab)-1)){ + alleles<-colSums(Spp_genind@tab[sample(1:nrow(Spp_genind@tab), t+1),],na.rm=T) + for (l in 1:length(allele_cat)) summ_results_tree[(t),(l+2),scen,nrep]<-sum(alleles[allele_cat[[l]]]>0, na.rm=T) + } + summ_results_tree[,,,nrep] #if not parallel comment OUT + } + summ_results_tree[,,1,]<-abind(temp,along=3) #if not parallel comment OUT + save(summ_results_tree,file=paste("summ_results_tree",n_drop_file,".R",sep="")) + + stopCluster(cl) + +#end of loop over species +} + + + + +##################################### +# PART 2- COMPARE EX SITU AND IN SITU # +##################################### + + #setwd("C:/Users/shoban/Dropbox/Projects/IN_PROGRESS/Oak_popgen_analyses/") + setwd("C:/Users/shoban.DESKTOP-DLPV5IJ/Dropbox/Projects/IN_PROGRESS/Oak_popgen_analyses/") + #setwd("/home/user/Dropbox/Projects/IN_PROGRESS/Oak_popgen_analyses/") + +#This will run over a loop of "Include all alleles (n_to_drop=0)" and "Include only alleles present in more than two copies (n_to_drop=2)" +for (n_to_drop in c(0,2)){ + if (n_to_drop==2) n_drop_file<-"" + if (n_to_drop==0) n_drop_file<-"_dr_0" + + species_names<-c("Hhannerae","Hwaimeae","Masheii","Mpyramidata","Pekmanii","Psargentii","Qboyntonii","Qgeorgiana","Qoglethorpensis","Zdecumbens","Zlucayana") + region_makeup_list<-list(list(1:2,3:4),list(1:2,3),list(1,2),list(1:2,3:4),list(1,2),list(1:2,3),list(1:2,3,4,5:9),list(1:2,3,4,5:10),list(1:2,3,4,5:8),list(1,2),list(1:2,3)) + set_garden_p<-c(5,4,3,5,3,4,10,11,9,3,4) + wild_results<-matrix(nrow=length(species_names),ncol=9+1) + alleles_existing_by_sp<-matrix(nrow=length(species_names),ncol=9) + + for (sp in 1:length(species_names)){ + this_species<-species_names[sp] + setwd(paste("C:/Users/shoban.DESKTOP-DLPV5IJ/Dropbox/Projects/IN_PROGRESS/Oak_popgen_analyses/",this_species,sep="")) + #setwd(paste("C:/Users/shoban/Dropbox/Projects/IN_PROGRESS/Oak_popgen_analyses/",this_species,sep="")) + #setwd(paste("/home/user/Dropbox/Projects/IN_PROGRESS/Oak_popgen_analyses/",this_species,sep="")) + Spp_tot_genind<-read.genepop(paste(substr(this_species,1,2),"_total.gen",sep=""),ncode=3) + + #This code compares the wild to various ex situ populations or all the ex situ merged + #Just put in garden and wild population numbers... currently all gardens are merged into one "population" + wild_p<-unlist(region_makeup_list[[sp]]); garden_p<-set_garden_p[sp] + n_ind_W<-table(Spp_tot_genind@pop)[wild_p]; n_ind_G<-table(Spp_tot_genind@pop)[garden_p]; + Spp_tot_genpop<-genind2genpop(Spp_tot_genind) + Spp_tot_genind_sep<-seppop(Spp_tot_genind) + alleles_cap<-colSums(Spp_tot_genind_sep[[garden_p]]@tab,na.rm=T) + + #Allele categories based only on wild populations (can look at all wild pop'ns or only one if you want) + allele_cat_tot<-get.allele.cat(Spp_tot_genpop[wild_p], region_makeup_list[[sp]], 2, n_ind_W, glob_only=F,n_drop=n_to_drop) + #This goes through each allele category and divides the number captured ex situ (alleles_cap) by the number of alleles existing (allele_cat_tot) + list_allele_cat<-c("global","glob_v_com","glob_com","glob_lowfr","glob_rare","reg_rare","loc_com_d1","loc_com_d2","loc_rare") + + for (i in 1:9) alleles_existing_by_sp[sp,i]<- (sum((allele_cat_tot[[i]])>0,na.rm=T)) + + for (l in 1:length(allele_cat_tot)) wild_results[sp,l]<-round(sum(alleles_cap[allele_cat_tot[[l]]]>0)/length(allele_cat_tot[[l]]),4) + + wild_results[sp,10]<-n_ind_G + } + + #setwd("C:/Users/shoban/Dropbox/Projects/IN_PROGRESS/Oak_popgen_analyses/") + setwd("C:/Users/shoban.DESKTOP-DLPV5IJ/Dropbox/Projects/IN_PROGRESS/Oak_popgen_analyses/") + #setwd("/home/user/Dropbox/Projects/IN_PROGRESS/Oak_popgen_analyses/") + wild_results<-cbind(species_names,wild_results) + write.csv(wild_results,file=paste("ex_vs_in_situ",n_drop_file,".csv",sep="")) + +} #close num to drop loop + + +