I'm a graduate student just starting to work with Maq for calling SNPs from Illumina resequencing of the Giardia genome. I'm a bit unsure about appropriate interpretation of Maq's output (which columns - read depth, quality, log likelihood, etc - might be best for evaluating a list of possible SNPs). Thoughts? I'm a newbie to this stuff...
Additionally, I'm interested in trying to utilize different cutoffs for calling SNPs for various purposes. I'm both looking for regions of high variability for genotyping, which might be best to require at least 40% SNP coverage, and evaluating heterozygosity, where we might want to require much less (10% SNP penetrance? lower)?. A visual alignment tool, MapView, makes that very easy with a sliding scale for SNP strigency, but can only look at one contig at a time. It seems impossible for whole-genome analysis, and I'd rather just use MAQ to calculate lists of SNPs for various conditions.
Any and all advice, no matter how small, would be really appreciated....
Additionally, I'm interested in trying to utilize different cutoffs for calling SNPs for various purposes. I'm both looking for regions of high variability for genotyping, which might be best to require at least 40% SNP coverage, and evaluating heterozygosity, where we might want to require much less (10% SNP penetrance? lower)?. A visual alignment tool, MapView, makes that very easy with a sliding scale for SNP strigency, but can only look at one contig at a time. It seems impossible for whole-genome analysis, and I'd rather just use MAQ to calculate lists of SNPs for various conditions.
Any and all advice, no matter how small, would be really appreciated....