add selected software

CV_doc/CV.Rmd

@@ -37,7 +37,7 @@ tribble(
 ```{r}
 tribble(
  ~ Experience, ~ Year, ~ Institution, ~Description,
- "Bioinformatics Engineer", "2023-", "Genomics England", "Developing features for and maintaining software for the cancer genomic medicine service.",
+ "Bioinformatics Engineer", "2023-", "Genomics England", "Developing features and maintaining software for the cancer genomic medicine service.",
  "Lecturer", "2021-2023", "Acibadem University", "Worked as a lecturer for the undergrad and grad courses on biostatistics and bioinformatics topics.",
  "Bioinformatics Specialist", "2018-2023", "Epigenetiks", "Worked on developing and maintaining multiple whole exome sequencing-based analysis pipelines (cancer and rare disease applications) for the Istanbul-based medical diagnostics company.",
  "Postdoctoral Associate", "2016", "Yale University", "Briefly worked as a post-doc associate at the Gunel Lab, Yale School of Medicine, where I had previously done multiple internships between 2011-2014. Research in neurogenetics, particularly malformations of cortical development and brain tumours, performing functional in-vitro analyses to investigate the effect of a SNP in the pathogenesis of gliomas.",

about-me.Rmd

@@ -15,73 +15,46 @@ My CV (PDF) is also available [here](./CV_doc/egeulgen_CV.pdf)
 # Experience
 
 ```{r, echo=FALSE}
-library(slickR)
-library(htmltools)
-
-generate_div <- function(role_and_company, years, description, logo_path) {
- description_div <- tags$div(
- tags$h3(role_and_company,
- style = css(color = "black")), 
- tags$div(
- tags$h4(years,
- style = css(color = "black")), 
- tags$p(description,
- style = css(color = "black"))
- )
- )
- 
- d <- tags$div(
- style = css(display = "flex", "align-items" = "center"),
- tags$div(
- style = css(display = "flex", "flex-direction" = "column", "margin-right" = "20px", width = "20%"),
- tags$img(src=logo_path)
- ),
- tags$div(
- style = css(display = "flex", "flex-direction" = "column", "margin-right" = "20px", width = "80%", "text-align" = "left"), 
- description_div
- )
- )
- return(d)
-}
+source("utils.R")
 ```
 
 ```{r, echo=FALSE, out.height="200px"}
 experiences <- slick_list(
  generate_div(
- role_and_company = "Bioinformatics Engineer - Genomics England",
- years = "2023-",
+ header = "Bioinformatics Engineer - Genomics England",
+ sub_header = "2023-",
  description = "Developing features for and maintaining software for the cancer genomic medicine service.",
- logo_path = "images/Genomics_England_logo.svg"
+ img_path = "images/Genomics_England_logo.svg"
  ),
  generate_div(
- role_and_company = "Lecturer - Acibadem University",
- years = "2021-2023",
+ header = "Lecturer - Acibadem University",
+ sub_header = "2021-2023",
  description = "Worked as a lecturer for the undergrad and grad courses on biostatistics and bioinformatics topics.",
- logo_path = "images/ACU_logo.png"
+ img_path = "images/ACU_logo.png"
  ),
  generate_div(
- role_and_company = "Bioinformatics Specialist - Epigenetiks",
- years = "2018-2023",
+ header = "Bioinformatics Specialist - Epigenetiks",
+ sub_header = "2018-2023",
  description = "Worked on developing and maintaining multiple whole exome sequencing-based analysis pipelines (cancer and rare disease applications) for the Istanbul-based medical diagnostics company.",
- logo_path = "images/epigenetiks_logo.png"
+ img_path = "images/epigenetiks_logo.png"
  ),
  generate_div(
- role_and_company = "Postdoctoral Associate - Yale University",
- years = "2016",
+ header = "Postdoctoral Associate - Yale University",
+ sub_header = "2016",
  description = "Briefly worked as a post-doc associate at the Gunel Lab, Yale School of Medicine, where I had previously done multiple internships between 2011-2014. Research in neurogenetics, particularly malformations of cortical development and brain tumours, performing functional in-vitro analyses to investigate the effect of a SNP in the pathogenesis of gliomas.",
- logo_path = "images/yale-logo.svg"
+ img_path = "images/yale-logo.svg"
  ),
  generate_div(
- role_and_company = "Bioinformatics Consultant - NeuroOncology Technologies",
- years = "2015-2023",
+ header = "Bioinformatics Consultant - NeuroOncology Technologies",
+ sub_header = "2015-2023",
  description = "Developed and maintained the Whole Exome Sequencing pipeline for the local medical diagnostics company based in Istanbul-Turkey. The pipeline allows for the identification of clinically-relevant genomics findings in brain tumours, especially regarding gliomas.",
- logo_path = "images/NOT_logo.svg"
+ img_path = "images/NOT_logo.svg"
  ),
  generate_div(
- role_and_company = "Research Group Member - ACU Brain tumour Research Group",
- years = "2012-",
+ header = "Research Group Member - ACU Brain tumour Research Group",
+ sub_header = "2012-",
  description = "Participate in research on brain tumours, particularly on gliomas. I assist in biostatistical as well as bioinformatics analyses, focusing on the integration of molecular biological and clinical data to improve diagnosis, prognosis and treatment of glioma.",
- logo_path = "images/AUBTRG_logo.svg"
+ img_path = "images/AUBTRG_logo.svg"
  )
 )
 

software.Rmd

@@ -1,5 +1,5 @@
 ---
-title: "Selected Software"
+title: Selected Software
 output:
  html_document:
  code_download: false
@@ -8,4 +8,37 @@ output:
  code_folding: "none"
 ---
 
-TODO
+Below are a number of selected software I developed with links to the corresponding repos as well as methodology articles, where applicable.
+
+```{r, echo=FALSE}
+source("utils.R")
+```
+
+```{r, echo=FALSE, out.height="200px"}
+experiences <- slick_list(
+ generate_div(
+ header = "pathfindR",
+ sub_header = tags$a(href="https://github.com/egeulgen/pathfindR", "https://github.com/egeulgen/pathfindR"),
+ description = "pathfindR is an R package for enrichment analysis via active subnetworks. The package also offers functionality to cluster the enriched terms and identify representative terms in each cluster, score the enriched terms per sample, and visualize analysis results. As of the latest version, the package also allows comparison of two pathfindR results.
+ Ulgen E, Ozisik O, Sezerman OU. 2019. pathfindR: An R Package for Comprehensive Identification of Enriched Pathways in Omics Data Through Active Subnetworks. Front. Genet. https://doi.org/10.3389/fgene.2019.00858",
+ img_path = "https://raw.githubusercontent.com/egeulgen/pathfindR/master/inst/extdata/logo.png"
+ ),
+ generate_div(
+ header = "driveR",
+ sub_header = tags$a(href="https://github.com/egeulgen/driveR", "https://github.com/egeulgen/driveR"),
+ description = "driveR is a tool for personalized or batch analysis of genomics data for driver gene prioritization by combining genomics information and prior biological knowledge. As features, driveR uses coding impact metaprediction scores, non-coding impact scores, somatic copy number alteration scores, hotspot gene/double-hit gene condition, ‘phenolyzer’ gene scores and memberships to cancer-related KEGG pathways. It uses these features to estimate cancer-type-specific probabilities for each gene of being a cancer driver using the related task of a multi-task learning classification model.
+ Ülgen E, Sezerman OU. driveR: a novel method for prioritizing cancer driver genes using somatic genomics data. BMC Bioinformatics. 2021 May 24;22(1):263.https://doi.org/10.1186/s12859-021-04203-7",
+ img_path = "https://raw.githubusercontent.com/egeulgen/driveR/master/inst/extdata/driveR_logo.png"
+ ),
+ generate_div(
+ header = "PANACEA",
+ sub_header = tags$a(href="https://github.com/egeulgen/PANACEA", "https://github.com/egeulgen/PANACEA"),
+ description = "PANACEA is a collection of personalized anti-cancer drug prioritization approaches utilizing network methods. The methods utilize personalized “driverness” scores from driveR to rank drugs, mapping these onto a protein-protein interaction network. The “distance-based” method scores each drug based on these scores and distances between drugs and genes to rank given drugs. The “RWR” method propagates these scores via a random-walk with restart framework to rank the drugs.
+ Ulgen E, Ozisik O, Sezerman OU. PANACEA: network-based methods for pharmacotherapy prioritization in personalized oncology. Bioinformatics. 2023 Jan 1;39(1):btad022. https://doi.org/10.1093/bioinformatics/btad022",
+ img_path = "https://raw.githubusercontent.com/egeulgen/PANACEA/master/inst/extdata/PANACEA_logo.png"
+ )
+)
+
+slickR(experiences) + 
+ settings(dots = TRUE, adaptiveHeight = TRUE, draggable = TRUE, autoplay = TRUE, autoplaySpeed = 3000)
+```

utils.R

@@ -0,0 +1,28 @@
+suppressPackageStartupMessages(library(slickR))
+suppressPackageStartupMessages(library(htmltools))
+
+generate_div <- function(header, sub_header, description, img_path) {
+ description_div <- tags$div(
+ tags$h3(header,
+ style = css(color = "black")), 
+ tags$div(
+ tags$h4(sub_header,
+ style = css(color = "black")), 
+ tags$p(description,
+ style = css(color = "black"))
+ )
+ )
+
+ d <- tags$div(
+ style = css(display = "flex", "align-items" = "center"),
+ tags$div(
+ style = css(display = "flex", "flex-direction" = "column", "margin-right" = "20px", width = "20%"),
+ tags$img(src=img_path)
+ ),
+ tags$div(
+ style = css(display = "flex", "flex-direction" = "column", "margin-right" = "20px", width = "80%", "text-align" = "left"), 
+ description_div
+ )
+ )
+ return(d)
+}