PrediXcan is a gene-based association test that prioritizes genes that are likely to be causal for the phenotype.

Do you have only summary results? Try MetaXcan, a new extension of PrediXcan that uses only summary statistics. No individual level data necessary.

Please join this Google Group for news on releases, features, etc. For support and feature requests, you can use this repository's issue tracker.

• Gamazon ER†, Wheeler HE†, Shah KP†, Mozaffari SV, Aquino-Michaels K, Carroll RJ, Eyler AE, Denny JC, Nicolae DL, Cox NJ, Im HK. (2015) A gene-based association method for mapping traits using reference transcriptome data. Nat Genet. doi:10.1038/ng.3367. (Link to paper, Link to Preprint on BioRxiv)

  †:equal contribution

  *:correspondence haky at uchicago dot edu

• Alvaro Barbeira, Kaanan P Shah, Jason M Torres, Heather E Wheeler, Eric S Torstenson, Todd Edwards, Tzintzuni Garcia, Graeme I Bell, Dan Nicolae, Nancy J Cox, Hae Kyung Im. (2016) MetaXcan: Summary Statistics Based Gene-Level Association Method Infers Accurate PrediXcan Results link to preprint

• Heather E Wheeler, Kaanan P Shah, Jonathon Brenner, Tzintzuni Garcia, Keston Aquino-Michaels, GTEx Consortium, Nancy J Cox, Dan L Nicolae, Hae Kyung Im. (2016) Survey of the Heritability and Sparsity of Gene Expression Traits Across Human Tissues. link to preprint

• Download software from this link

PredictDB hosts genetic prediction models of transcriptome levels to be used with PrediXcan. See our wiki for a report of a recent update of the prediction models.

G2Pdb, Gene to Phenotype database, hosts the results of PrediXcan applied to a variety of phenotypes. Link to prototype.

• Heather E Wheeler, Kaanan P Shah, Jonathon Brenner, Tzintzuni Garcia, Keston Aquino-Michaels, GTEx Consortium, Nancy J Cox, Dan L Nicolae, and Hae Kyung Im (2016) Survey of the Heritability and Sparsity of Gene Expression Traits Across Human Tissues Link to Preprint; correspondence hwheeler at luc dot edu and haky at uchicago dot edu
• Database of heritability estimates link older link or older link

Data downloaded from dbGaP link

Data downloaded from NIMH Repository and Genomics Resource

Battle, A., Mostafavi, S., Zhu, X., Potash, J.B., Weissman, M.M., McCormick, C., Haudenschild, C.D., Beckman, K.B., Shi, J., Mei, R., et al. (2014). Characterizing the genetic basis of transcriptome diversity through RNA-sequencing of 922 individuals. Genome Research 24, 14–24.