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MAGMA

I applied MAGMA1 to the Million Veterans2 GWAS of Chronic Fatigue Syndrome using bulk RNAseq GTEx data3 as a reference. Results are plotted below.

Results of applying MAGMA to the Million Veterans GWAS of CFS. y-axis is negative log of p value. x-axis corresponds to GTEx tissue type.

There are no significant tissues. This is perhaps to be expected, given the relatively low case count and noisy phenotype definition used here.

  1. Christiaan A De Leeuw, Joris M Mooij, Tom Heskes, and Danielle Posthuma. MAGMA: generalized gene-set analysis of GWAS data. PLoS Computational Biology, 11(4):e1004219, 2015. URL: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004219. ↩

  2. Anurag Verma, Jennifer E Huffman, Alex Rodriguez, Mitchell Conery, Molei Liu, Yuk-Lam Ho, Youngdae Kim, David A Heise, Lindsay Guare, Vidul Ayakulangara Panickan, and others. Diversity and scale: Genetic architecture of 2068 traits in the VA Million Veteran Program. Science, 385(6706):eadj1182, 2024. URL: https://www.science.org/doi/10.1126/science.adj1182. ↩

  3. GTEx Consortium. The GTEx consortium atlas of genetic regulatory effects across human tissues. Science, 369(6509):1318–1330, 2020. URL: https://www.science.org/doi/full/10.1126/science.aaz1776. ↩