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GenRank

Methods for ranking genes based on convergent evidence obtained from multiple independent evidence layers. Integration of data at gene-level from multiple evidence layers has been shown to be an effective approach to identify and prioritize candidate genes in complex genetic traits. This package implements three methods to integrate gene-level data generated from multiple independent lines of investigation:

  • Convergent Evidence (CE) method, which is a variant of the famous PageRank algorithm
  • Rank Product (RP) method, which was earlier proposed to perform differential expression and meta-analysis of microarray-based gene expression data, and
  • The traditional methods to combine p-values.

For detailed information and tutorials, see the package vignette.

Installation

library(devtools)
# if you don't have the package, run install.packages("devtools")
install_github("chakri9/GenRank", build_vignettes = TRUE)

Note about vignettes

The above installation instructions will build the vignette, which can be viewed by the command browseVignettes(package="GenRank"). However, these instructions seem to work only with Rstudio at the moment because of the Pandoc intgration. If you are not using Rstudio, you can still follow the above instructions except for build_vignettes = FALSE.


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Candidate gene prioritization based on convergent evidence

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