Get positions in BAM with reads supporting at least 2 different nucleotides

Question

[Roman Hillje]

Hi guys,

I'm currently looking for a tool or script that takes a BAM file (from an RNAseq experiment) and outputs a list of all the positions that have reads supporting at least 2 different nucleotids (WT vs variant or whatever you want to call it). Ideally, it also reports the coverage so I can filter it later. Does anybody have an idea how to do this? I don't really care about the base call quality at the positions at this point.

Cheers, Roman

[ATpoint]

Could you give an example of the desired output?

[swbarnes2]

So you want every location where a single read differs from the consensus? The vast majority of the loci you identify will not be real differences, but will be random errors in the reads.

Answer 1

[Pierre Lindenbaum]

using samfixcigar to convert the cigar string to identify the mismatches. http://lindenb.github.io/jvarkit/SamFixCigar.html

and the samjdk to filter the reads containing a least two cigar elements 'X' or 'I' or 'D'. http://lindenb.github.io/jvarkit/SamJdk.html

java -jar dist/samfixcigar.jar -R src/test/resources/rotavirus_rf.fa src/test/resources/S1.bam |\
java -jar dist/samjdk.jar -e 'return !record.getReadUnmappedFlag() && record.getCigar().getCigarElements().stream().map(C->C.getOperator().name()).filter(OP->OP.equals("X") || OP.equals("I") || OP.equals("D")).count()>1;'

@HD VN:1.5  SO:coordinate
@SQ SN:RF01 LN:3302
@SQ SN:RF02 LN:2687
@SQ SN:RF03 LN:2592
@SQ SN:RF04 LN:2362
@SQ SN:RF05 LN:1579
@SQ SN:RF06 LN:1356
@SQ SN:RF07 LN:1074
@SQ SN:RF08 LN:1059
@SQ SN:RF09 LN:1062
@SQ SN:RF10 LN:751
@SQ SN:RF11 LN:666
@RG ID:S1   SM:S1   LB:L1   CN:Nantes
@CO Processed with samfixcigar compilation: 2018-09-28:14-09-50 githash: 1919e185cb0c676aa912bd7c2b4cf9d1113f3927 htsjdk: 2.15.0
RF01_27_590_3:0:0_1:0:0_68  163 RF01    27  60  4=1X14=1X12=1X37=   =   521 564 GTATCATCTAATCTTGTCATAATATTTATCATATATATATAACTCACAATCCGCAGTTCAAATTCCAATA  2222222222222222222222222222222222222222222222222222222222222222222222  RG:Z:S1 NM:i:3  AS:i:55 XS:i:0
RF01_110_504_2:0:0_1:0:0_5d 163 RF01    110 60  13=1X19=1X36=   =   435 395 ATAGTGAATTAGATAATAGATGTATTGAATTTCCTTCTAAATGCTTAGAAAACTCAAAGAATGGACTATC  2222222222222222222222222222222222222222222222222222222222222222222222RG:Z:S1   NM:i:2  AS:i:60 XS:i:0
RF01_158_624_3:0:0_1:0:0_61 99  RF01    158 60  33=1X21=1X12=1X1=   =   555 467 AAAACTCAAAGAATGGACTATCATTGAAAAAGCACTTTGTTGAATATAGCGATGTAATGGAGAATGCCCC  2222222222222222222222222222222222222222222222222222222222222222222222  RG:Z:S1 NM:i:3  AS:i:58 XS:i:0
RF01_205_734_3:0:0_2:0:0_79 99  RF01    205 60  14=1X27=1X22=1X4=   =   665 530 AGCGATGTTATGGATAATGCCACACTGTTGTCAATATTATCGAACTCTTATGATAAATATAACGCAGTTG  2222222222222222222222222222222222222222222222222222222222222222222222  RG:Z:S1 NM:i:3  AS:i:55 XS:i:0
RF01_295_749_2:0:0_4:0:0_9a 163 RF01    295 60  40=1X20=1X8=    =   680 455 GCAAAAGGTAAGCCGCTAGAAGCAGATTTGACAGTGAATGCGTTGGATTATGAAAATAACACGATAACAT  2222222222222222222222222222222222222222222222222222222222222222222222RG:Z:S1   NM:i:2  AS:i:60 XS:i:0
(...)

. Ideally, it also reports the coverage so I can filter it later.

use any tool giving the coverage.... like GATK DepthOfCoverage