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• W2803775797 abstract "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), IMPUTE2 or PLINK 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; covariates in the model are first fit without the SNP, and those parameter estimates are used as initial points. We benchmarked gwasurvivr with other software capable of conducting genome wide survival analysis (genipe, SurvivalGWAS_SV, and GWASTools). gwasurvivr is significantly faster and shows better scalability as sample size, number of SNPs and number of covariates increases. Availability and implementation gwasurvivr, including source code, documentation, and vignette are available at: http://bioconductor.org/packages/gwasurvivr Contact Abbas Rizvi, rizvi.33@osu.edu ; Lara E Sucheston-Campbell, suchestoncampbell.1@osu.edu Supplementary information: Supplementary data are available at https://github.com/suchestoncampbelllab/gwasurvivr_manuscript" @default.
• W2803775797 created "2018-06-01" @default.
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• W2803775797 date "2018-05-18" @default.
• W2803775797 modified "2023-10-16" @default.
• W2803775797 title "gwasurvivr: an R package for genome wide survival analysis" @default.
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• W2803775797 doi "https://doi.org/10.1101/326033" @default.
• W2803775797 hasPublicationYear "2018" @default.
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