I'm trying to run FreeBayes with Human genomic sample. Here is my command.
freebayes --no-indels --no-mnps --no-complex -v snp0.vcf -p 2 -f Homo_sapiens.nucleotide.fa -b sample1.bam
BAM file as SAM format (output from BWA)
HWI-ST313_0162:7:46:20191:40694#CTTGTA 177 Y 2786195 0 100M 6 73049336 0 CATAGTATTCCATGGTGTATATGTGCCACATTTTCTTCATCCAGTCTATCATTGNTGGACATTTGGGTTGGTTCCAAGTCTTTGCTATTGTGAATAGTGC ggffedccb_fcadefdcfdfceaedS`ddehdafgfggdgcggddddfd]]]]BbT`]bgaggbggggggeggggegggggggggffgggfgggggggg XT:A:R NM:i:1 SM:i:0 AM:i:0 X0:i:38 XM:i:1 XO:i:0 XG:i:0 MD:Z:54T45
HWI-ST313_0162:7:63:14158:88065#CTTGTA 113 Y 2925844 0 100M = 2925844 0 AAAGGAGGCATCTCAAAGGAAATGGAATTTAGTTGAGCTGAAGGATAAGAATTAGATTGCACTGTATTAAAAGTTGGTGAAGGGCTTCCCAGGCAAAGAA gdgggcedegfacfcggggggcgggefecffggggfdgeggfgggegggggggffgeeggcgggeggfggggggffgffegfgfggbggggggggggfgf XT:A:R NM:i:71 SM:i:0 AM:i:0 X0:i:2 X1:i:0 XM:i:1 XO:i:0 XG:i:0 MD:Z:0T1T1T0T1C2C0A0G0A1C0T0T0T0T0G0C0A0A0A0T0C1G2T1A0T2A0A0C0T0T0A0A0C0A0C1T0T0G1A0G0T0T0A1T0T0G0T0A1A0C0G2T0T0T2C0T0C1T0T0C0A1A0T1G0A0G1T0A0C2G3G0 XA:Z:X,-88657279,100M,1;
When result generated, it got all position as SNP.
#CHROM POS ID REF ALT QUAL FILTER INFO FORMAT unknown
Y 3044167 . G T 14.6236 . AB=0.25;ABP=5.18177;AC=1;AF=0.5;AN=2;AO=1;CIGAR=1X;DP=4;DPRA=0;EPP=5.18177;EPPR=3.0103;HWE=-0;LEN=1;MEANALT=2;MQM=37;MQMR=37;NS=1;NUMALT=1;ODDS=0;PAIRED=0;PAIREDR=0;RO=2;RPP=5.18177;RPPR=3.0103;RUN=1;SAP=5.18177;SRP=7.35324;TYPE=snp;XAI=0;XAM=0.81;XAS=0.81;XRI=0;XRM=0.4;XRS=0.4;BVAR GT:DP:RO:QR:AO:QA:GL0/1:4:2:90:1:33:-6.27,-3.72597,-11.48
Y 3044168 . G T 13.2124 . AB=0.25;ABP=5.18177;AC=1;AF=0.5;AN=2;AO=1;CIGAR=1X;DP=4;DPRA=0;EPP=5.18177;EPPR=3.73412;HWE=-0;LEN=1;MEANALT=1;MQM=37;MQMR=37;NS=1;NUMALT=1;ODDS=2.99336;PAIRED=0;PAIREDR=0;RO=3;RPP=5.18177;RPPR=3.73412;RUN=1;SAP=5.18177;SRP=9.52472;TYPE=snp;XAI=0;XAM=0.79;XAS=0.79;XRI=0;XRM=0.276667;XRS=0.276667;BVAR GT:DP:RO:QR:AO:QA:GL 0/1:4:3:133:1:33:-3.3,-0.60206,-12.4133
Y 3044169 . T G 13.2124 . AB=0.25;ABP=5.18177;AC=1;AF=0.5;AN=2;AO=1;CIGAR=1X;DP=4;DPRA=0;EPP=5.18177;EPPR=3.73412;HWE=-0;LEN=1;MEANALT=1;MQM=37;MQMR=37;NS=1;NUMALT=1;ODDS=2.99336;PAIRED=0;PAIREDR=0;RO=3;RPP=5.18177;RPPR=3.73412;RUN=1;SAP=5.18177;SRP=9.52472;TYPE=snp;XAI=0;XAM=0.79;XAS=0.79;XRI=0;XRM=0.276667;XRS=0.276667;BVAR GT:DP:RO:QR:AO:QA:GL 0/1:4:3:135:1:33:-3.3,-0.60206,-12.6
Y 3044170 . A T 13.2124 . AB=0.25;ABP=5.18177;AC=1;AF=0.5;AN=2;AO=1;CIGAR=1X;DP=4;DPRA=0;EPP=5.18177;EPPR=3.73412;HWE=-0;LEN=1;MEANALT=1;MQM=37;MQMR=37;NS=1;NUMALT=1;ODDS=2.99336;PAIRED=0;PAIREDR=0;RO=3;RPP=5.18177;RPPR=3.73412;RUN=1;SAP=5.18177;SRP=9.52472;TYPE=snp;XAI=0;XAM=0.81;XAS=0.81;XRI=0;XRM=0.27;XRS=0.27;BVAR GT:DP:RO:QR:AO:QA:GL 0/1:4:3:162:1:33:-3.3,-0.60206,-15.12
and final file result like > 100 GB (my BAM file is 8 GB). Any advice?
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Jirapong •
Your alignments are generating a very large number of changes see:
MD:Z:0T1T1T0T1C2C0A0G0A1C0T0T0T0T0G0C0A0A0A0T0C1G2T1A0T2A0A0C0T0T0A0A0C...
For each of these variations in the CIGAR string you may end up with a separate line in your output. So a single line of your SAM file may generate dozens of lines of SNP calls. Now it is very likely that either your alignment or the way you invoke freebayes is not correct. Right now I am only trying to come up with an explanation of why the resulting file size is so large.
Also note that a BAM file is both binary and compressed, whereas your VCF file is text format and not compressed.
Thank you for the answer, well, you're right that if more SNP then VCF file is expect to be large. BUT when i do analysis with samtools (mpileup), we have only 151K SNP.
I would guess that the tool that you are running is not working properly and calls every single sequencing error a SNP
A basic way of resolving the problem you've experienced is to set the --min-alternate-count (-C) to 2, as this requires two supporting observations to call a variant. The most recent version in github sets this by default to avoid exactly the problem you're experiencing (low coverage and a lot of errors).
Also, what happens when you just run with the default parameters? FreeBayes uses putative complex alleles to filter clusters of errors from reads, so if you remove them you don't get this performance benefit.
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turn out if i use with ploidy more than one it will generate alot result, to at this point i limited to use only Haploid.