This repository contains the original reference implementation of the PrediXcan method. It is now considered deprecated and exists only for reference purposes.
Active development is now conducted at the MetaXcan repository. Tutorial for this new version is here
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
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.
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.