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xiaolei-lab / rMVP

:postbox: A Memory-efficient, Visualization-enhanced, and Parallel-accelerated Tool For Genome-Wide Association Study
Apache License 2.0
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How to use of FDR adjusted Pvalues for threshold at 0.05 and 0.01 level of significance #58

Open sakhale2 opened 3 years ago

sakhale2 commented 3 years ago

Hi, first of all thank you for such a great package. I am trying to use the rMVP for visualization of GAPIT GWAS results. particularly I am interested in multiple trait Manhattan plots. Bonferroni correction is too stringent for my data (#SNP = 1.5 million) and I would like to use FDR correction as threshold. I am not sure how to include this in existing code for creating Manhattan plots (multiple traits). I do have FDR adjusted p value estimates for same set of marker for each trait.

Thank you in advance.

YinLiLin commented 3 years ago

Please refer to our developed package CMplot at https://github.com/YinLiLin/CMplot

jeremysutherland commented 2 years ago

I'd like to bump this comment. Is there a way to use FDR when determining significant SNPs, instead of Bonferroni, within rMVP? This is a great package by the way!

YinLiLin commented 2 years ago

@jeremysutherland Thank you for using rMVP. As the Bonferroni adjustment is the most commonly used method in GWAS, thus we didn't integrate other methods in rMVP. However, no matter which method is used, it only affect the visualization of results, but not change the association results, users can adjust the output p-values by using the base function p.adjust() in R with various methods, then manually visualize the adjusted outcome by either MVP.Report() or CMplot().