Comparison of methods for transcriptome imputation through application to two common complex diseases.
Ontology highlight
ABSTRACT: Transcriptome imputation has become a popular method for integrating genotype data with publicly available expression data to investigate the potentially causal role of genes in complex traits. Here, we compare three approaches (PrediXcan, MetaXcan and FUSION) via application to genome-wide association study (GWAS) data for Crohn's disease and type 1 diabetes from the Wellcome Trust Case Control Consortium. We investigate: (i) how the results of each approach compare with each other and with those of standard GWAS analysis; and (ii) how variants in the models used by the prediction tools compare with variants previously reported as eQTLs. We find that all approaches produce highly correlated results when applied to the same GWAS data, although for a subset of genes, mostly in the major his
SUBMITTER: Fryett JJ
PROVIDER: S-EPMC6189136 | biostudies-literature | 2018 Nov
REPOSITORIES: biostudies-literature
ACCESS DATA