ABSTRACT
Summary To address the limited software options for performing survival analyses with millions of SNPs, we developed gwasurvivr, an R/Bioconductor package with a simple interface for conducting genome wide survival analyses using VCF (outputted from Michigan or Sanger imputation servers) and IMPUTE2 files. To decrease the number of iterations needed for convergence when optimizing the parameter estimates in the Cox model we modified the R package survival such that the covariates in the model are first fit without the SNP, and those parameter estimates are used as initial points. We benchmarked gwasurvivr with other GWAS software capable of conducting genome wide survival analysis (genipe, SurvivalGWAS_SV, and GWASTools). gwasurvivr is significantly faster and shows better scalability as sample size and number of SNPs increase.
Availability and implementation gwasurvivr, including source code, documentation, and vignette are available at: https://github.com/suchestoncampbelllab/gwasurvivr
Contact Abbas Rizvi, Rizvi.33{at}osu.edu; Lara E Sucheston-Campbell, sucheston-campbell.1{at}osu.edu