SAMtools and SNP calling

[Jan]

I'm a biologist by training and not a bioinformatics person so I'm hoping someone can help me understand the SNP calling parameters with SAMtools. We are aligning with BFAST and using SAMtools for our SNP caller. What I'm trying to understand is what the default settings for the SNP caller are (e.g. the minor allele must present X% for the call to be counted as a heterozygote) and how I can modify how the SNPs are called (I've studied the MAQ manual, but it hasn't helped me). We ran a SNP chip for validation - the majority of the discordant calls we observed between the SNP chip and our sequencing were hets not called by the SNP caller and when I go into IGV or our in-house visualization program I see the minor alleles present in a high enough percentages that I would have called them as heterozygotes - agreeing with the SNP chip. I'm working in tumor samples which can be "contaminated" with normal cells so I expect to see less than "textbook" heterozygotes presenting themselves and want to make sure I capture them, but not overly elevate my false positive rate either.

[lh3]

Samtools/maq are not designed for very deep coverage. In that case, please take the pileup output and design your own algorithm. For the SNP calling algorithm, it is not as simple as merely setting a threshold. You should read the maq/soapsnp paper for more details.

[plnagy]

Even in samples where the variations are expected to be present in every cell , we experience that the program does not make the appropriate calls. We would like to verify what its settings are for calling heterozygousity and adjust them to have greater sensitivity while maintaining specificity. Is there a way to do that?