Hope to find some summary materials for the comparison among PLink, SNPRelate, SNPassoc et.al. Any suggestion? I will add more materials after I master these tools:
1, SNPRelate: Multiprocessing, Support more variation (SNP, CNV, SNV)
2, PLink: hard to do advance analysis
3, SNPassoc: support traditional association study
4, Gemma: Genome-wide efficient mixed-model association (GEMMA)
1 answer
Some more:
GAPIT: Nice R-package based on EMMA, does everything including the plotting in one box, a bit hard to customise intermediate steps, in my experience much more conservative than PLINK (i.e., fewer associated SNPs)
TASSEL: Easy to use, point-and-click interface, doesn't seem to support correcting for multiple testing? Lots of tutorials out there are for older versions, have to be careful. Can do MLM and GLM associations.
pySEER: Supports SNP, PAV, indel, and k-mer association, wonderful documentation: http://pyseer.readthedocs.io/en/master/
(Personally I believe k-mer based association studies will eat SNP based association studies soon, less bias from reference genomes)
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Gemma might be added
Nice Nature Genetics paper: Gemma: genome-wide efficient mixed-model association (GEMMA)
I'm looking for a association package/suite that can help with disproportionate numbers of case-control. Something weighted. I'd data that with one-tenth number of cases of controls, results were of course messy. Any suggestions?