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Hi, I start working with IGV, but I have some doubts in how to identify a good SPN in this program. First I download the new Soybean Genome on Phytozome (Gmax_275_v2.0.fa and Gmax_275_Wm82.a2.v1.gene.gff3 files), and then I upload my files (sample.vcf, sample.bam and sample.bam.bai) into the program. I indexed which files that program needed, so that's OK! But my doubt is which parameters should I consider for a good SNP? For example, what I need to see on Alleles, Genotypes and Variant Attributes? See the example below.

Chr: Chr06 Position: 35170948 ID: . Reference: C* Alternate: T Qual: 160 Type: SNP Is Filtered Out: No

Alleles: No Call: 0 Allele Num: 2 Allele Count: 4 Allele Frequency: 1

Minor Allele Fraction: 1

Genotypes: Non Variant: 0 - No Call: 0 - Hom Ref: 0 Variant: 1 - Het: 0 - Hom Var: 1

Variant Attributes AF1: 1 RPB: 5.557190e-01 VDB: 1.587578e-01 Depth: 18 FQ: -54 DP4: [1, 1, 6, 8] AC1: 2 Mapping Quality: 25 PV4: [1, 0.22, 1, 0.24]

Comments (5)


First of all, thank you for a truly great toolkit! It is no doubt the best one out there.

Now, I have a question regarding visualization of a SNP that is not called by UG but looks convincing in IGV. Yes, I've looked at the FAQ page gatkforums.broadinstitute.org/discussion/1235/why-didnt-the-unified-genotyper-call-my-snp-i-can-see-it-right-there-in-igv but I'm still not completely convinced that this is a false positive.

The BAM files have gone through the Best Practices workflow prior to SNP calling. Calling was done using UG with subsequent recalibration steps, where I followed the guidelines under gatkforums.broadinstitute.org/discussion/1259/what-vqsr-training-sets-arguments-should-i-use-for-my-specific-project. SNP calling was done using GATK 2.4-9.

Below is a screenshot from IGV showing the SNP call:

Fullsize here: s24.postimg.org/sepow851v/igv_snp.png

The average mapping quality for the reads that include the SNP is 50 and the average base quality at the locus of the SNP is 28.7 (not including 4 positions where base quality is below 10). These values are calculated from the values shown by IGV

Are these values really too low to not confidently call this SNP? I mean a base quality of 28.7 means a probability of 99.87% that the base call is correct. Isn't that good enough?

Please help me understand this, and let me know if you need more information. :)

Comments (16)

Hi. I am getting VERY odd results with some Streptococcus equi sequence. The BAM files from BWA align well in IGV, but when I run them through your pipeline there are many local errors where it seems that a single indel has been incorrectly multiplied up - somehow. You need to see the IGV screenshot.!

The bottom is a BAM file from BWA and the top is the final one from the GATK pipeline.