eQTL weighted GWAS

Increasing evidence suggests that single nucleotide polymorphisms (SNPs) associated with complex traits are likely to be expression quantitative trait loci (eQTLs). Incorporating eQTL information hence has potential to increase power of genome-wide association studies (GWAS). This website provides R functions on how to incorporate eQTL information from eQTL databases into analysis of GWAS data.

eQTL databases:

Three databases, derived from a cross-platform eQTL catalog and based on cis (within 1M bp) signals only, are available at the moment. Databases based on other signals (e.g. trans) will be made available in near future.

  • Derived from MRCA: eqtldb_mrca_cis1m.Rdata
  • Derived from MRCE: eqtldb_mrce_cis1m.Rdata
  • Derived from Meta-Analysis : eqtldb_meta_cis1m.Rdata

R functions:

ewgwas.R is the main R script that contains important R functions to incorporate eQTL information into GWAS.

R examples:

Examples are provided on how to use the R functions.

  • R script: ewgwas_example.R
  • GWAS example data: sma_example.txt


This compressed file (R-functions-ewgwas-04212013.zip) contains the databases, R functions and examples listed above.


Lin Li, Michael Kabesch, Emmanuelle Bouzigon, Florence Demenais, Martin Farrall, Miriam F. Moffatt, Xihong Lin, Liming Liang. (2013) Using eQTL weights to improve power for genome-wide association studies: a genetic study of childhood asthma. Frontiers in Statistical Genetics and Methodology (under revision)

Any questions and comments please email Lin Li <linli@hsph.harvard.edu> and Liming Liang <lliang@hsph.harvard.edu>.