I followed the samtools/bcfutils/vcfutils pathway followed [here][1] to convert a set of human Hg19-aligned BAM files into a set of raw VCF files. I then got vcftools to filter down to just autosomal SNPs. These are really, really, really low-coverage genomes (they were enriched for NRY and/or mtDNA, and I am just trying to make use of the "leftovers")

Now I have the data I want, but I am trying to found out what of it is actually usable. I was wondering what are good filtering parameters for tossing/keeping human SNPs (or where can I find said parameters)? Thanks!

-Deven

 [1]: http://ged.msu.edu/angus/tutorials-2012/snp_tutorial.html
This is what I use. I generally change them depending on the study. But more or less this is close to what everyone uses.

 - MinDP (Minimum read depth): 5 (Indels) and 3 (SNPs)
 - MaxDP (Maximum read depth): You have a low coverage data, so I would set it to 100. Normally it is 3 times the average coverage.
 - BaseQualBias (Minimum p-value for baseQ bias): 0
 - MinMQ (Minimum RMS mapping quality for SNPs): 20 or 30 (to be more stringent)
 - Qual (Minimum value of QUAL field): 15 or 20

 - StrandBias (Minimum p-value for strand bias): 0.0001
 - EndDistBias (Minimum p-value for end distance bias): 0.0001
 - MapQualBias (Minimum p-value for mapQ bias): 0
 - VBD (Minimum Variant Distance Bias): 0 (More relevant to RNA-seq reads)

 - GapWin (Window size for filtering adjacent gaps): 30 bp
 - SnpGap (SNP within INT bp around a gap to be filtered): 20 bp

 - SNPcluster (number of snps within a region): I usually drop all the snps if there are more than 3 snps within 10 bp.