GSminer, an R package that can automatically select gold standard including positive and negative genes pairs based on the Gene Ontology information of a specific species.
# The easiest way to get GSminer is to install with devtools: library(devtools) devtools::install_github("ShadowFiendSF/GSminer")
There are two classes in the GSminer package: GeneGOMapping class and GSminer class. You can get the detailed information by:
The GSminer package provides a very simple and friendly API. GSminer needs a gene and GO term mapping file as the input(the default delimiter is tab).
# the example data in GSminer package miner1 <- GSminer() outputPosNeg(miner1, u = 0.5, l = 0.25, multicores = 3, verbose = TRUE, seed = 100, posFilename = "positiveGene.txt", negFilename = "negativeGene.txt") # for your data miner2 <- GSminer(inputFile = "yourData", sep = "\t") outputPosNeg(miner2, u = 0.5, l = 0.25, multicores = 3, verbose = TRUE, seed = 100, posFilename = "positiveGene.txt", negFilename = "negativeGene.txt") # the relationship between the GeneGOMapping class and GSminer class in the GSminer package miner3 <- GSminer() ggmap <- new("GeneGOMapping", inputFile = "inst/extdata/TAIR.GO", sep = "\t") miner3@ggmapping <- ggmap
Zefeng Wu, Zhaohong Li and Ruolin Yang: GSminer: An R package for generating gold standard applied in gene functional network predictions.2018
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