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FLARE is a useful tool to call edits for RNA-editing RNA-seq datasets. While I tried to use it to call high-confidence edits, I got a problem with filter_read.py, which was used to remove reads with low quality. Regarding filter_read.py, there is a step filtering reads with
unexpected non-AG mutations. To achieve this aim, for each read, the tool firstly use read.is_reverse function from pysam to judge whether the read is from the reverse strand, then set the sense of this read using "sense = True if read.is_reverse == True else False". But I am confused about this step.
For example, with this workflow, in the case of truseq reverse stranded sequencing and we want to find out A-G mutations, for the read with flag 83, read.is_reverse=TRUE, so the sense=True. It's correct to filter reads with unexpected non-AG mutations. But how about the mate read with flag 163? In this situation, read.is_reverse=False, so the sense=False. the tool will remove this kind of read with unexpected non-TC mutations. But it's incorrect. Because the correct mutation of read with flag 163 is AG, not TC.
I apologize if I have any incorrect understanding. and your assistance will be highly appreciated!
The text was updated successfully, but these errors were encountered:
Hi,
FLARE is a useful tool to call edits for RNA-editing RNA-seq datasets. While I tried to use it to call high-confidence edits, I got a problem with filter_read.py, which was used to remove reads with low quality. Regarding filter_read.py, there is a step filtering reads with
unexpected non-AG mutations. To achieve this aim, for each read, the tool firstly use read.is_reverse function from pysam to judge whether the read is from the reverse strand, then set the sense of this read using "sense = True if read.is_reverse == True else False". But I am confused about this step.
For example, with this workflow, in the case of truseq reverse stranded sequencing and we want to find out A-G mutations, for the read with flag 83, read.is_reverse=TRUE, so the sense=True. It's correct to filter reads with unexpected non-AG mutations. But how about the mate read with flag 163? In this situation, read.is_reverse=False, so the sense=False. the tool will remove this kind of read with unexpected non-TC mutations. But it's incorrect. Because the correct mutation of read with flag 163 is AG, not TC.
I apologize if I have any incorrect understanding. and your assistance will be highly appreciated!
The text was updated successfully, but these errors were encountered: