I have couple of queries regarding QTL (Enzyme activity) association with genotypes which I did and I am a novice in this field
First one is regarding the Plink output file generated using --qassoc command for quantitative trait for unphased genotypes. (--qassoc gives allelic association (I presume)?). Is there a program by which I can check genotypic association with a quantitative trait?(there is genotypic means in plink but it doesn't give a Pvalue). I was able to get significant P values but was not able to find what is the significance of Beta, SE, R2 and T values. Would any of these parameters help to say the percentage of variance in the quantitative trait explained due to the presence of a particular variant?
I have also generated sliding window haplotypes for association with quantitative trait(4 marker & 6 marker)? What is the basis for window size determination(I have a total of 64 markers spanning 22kb)? and what does BETA, R2, STAT and PS in the output format signify. Is there a method by which we can estimate the haplotypic means for quantitative trait for the associated haplotypes?
Would you please help me with this queries
One note: generally for QTL analysis plink is not very good, especially slow and doesnt correct properly for multiple testing. Nowadays its more common to use programs like http://www.bios.unc.edu/research/genomic_software/Matrix_eQTL/ incredible fast, easy and proper FDR correction
I second this recommendation: plink is not designed to work with a very large number of different phenotypes. The plink 1.9 documentation explicitly recommends Matrix eQTL for that case.
With that said; Floris, can you elaborate on the problem with plink's multiple testing correction? If the v1.07 math was actually wrong, rather than just slow, I need to correct it.
I'm not a statistics expert, but the calculations of FDR in plink in the eQTL analysis (as far as I know) are done per phenotype (so per expression value) and not genome wide. I strongly recommend using matrix eqtl for this where the FDR is designed for this purpose.
The
--adjustvalues should be genome-wide. But yes, PLINK never performs multiple-phenotype corrections.Hi, Just curious his original query is for quantitative phenotypes (enzymatic activity), and matrix eQTL is an application for gene expression data containing thousands of transcripts. Do u think it is still applicable. Also, can u point where in plink 1.9 documentation is recommended the use of Matrix eQTL.
BETA, R2 are explained in the PLINK documentation for PLINK 1.7: http://pngu.mgh.harvard.edu/~purcell/plink/anal.shtml#qt
The default model is allelic association, but other models are possible using
--model: http://pngu.mgh.harvard.edu/~purcell/plink/anal.shtml#model