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README.md
# rqt: utilities for gene-level meta-analysis ## Installation ### Release version ```rqt``` is currently accepted into Bioconductor: https://bioconductor.org/packages/rqt/ and hence requires the version of R >=3.5 and the version of Bioconductor of 3.6. If you have these installed, then ```rqt``` can be installed from Github using BiocManager: ``` if (!requireNamespace("BiocManager", quietly=TRUE)) install.packages("BiocManager") BiocManager::install("rqt") ``` ### Development version The lastest version of `rqt` can be downloaded using Bioc-devel: ``` if (!requireNamespace("BiocManager", quietly=TRUE)) install.packages("BiocManager") BiocManager::install(version = "devel") BiocManager::install("rqt") ``` OR from GitHub: ``` devtools::install_github("izhbannikov/rqt@devel", buildVignette=TRUE) ``` ## Usage ###Single dataset ``` library(rqt) # Loading data and constructing the objects # data <- data.matrix(read.table(system.file("extdata/test.bin1.dat", package="rqt"), header=TRUE)) pheno <- data[,1] geno <- data[, 2:dim(data)[2]] colnames(geno) <- paste(seq(1, dim(geno)[2])) geno.obj <- SummarizedExperiment(geno) obj <- rqt(phenotype=pheno, genotype=geno.obj) # Analysis # res <- geneTest(obj, method="pca", out.type = "D") print(res) ``` ### Multiple datasets (meta analysis) ``` library(rqt) data1 <- data.matrix(read.table(system.file("extdata/phengen2.dat", package="rqt"), skip=1)) pheno <- data1[,1] geno <- data1[, 2:dim(data1)[2]] colnames(geno) <- paste(seq(1, dim(geno)[2])) geno.obj <- SummarizedExperiment(geno) obj1 <- rqt(phenotype=pheno, genotype=geno.obj) data2 <- data.matrix(read.table(system.file("extdata/phengen3.dat", package="rqt"), skip=1)) pheno <- data2[,1] geno <- data2[, 2:dim(data2)[2]] colnames(geno) <- paste(seq(1, dim(geno)[2])) geno.obj <- SummarizedExperiment(geno) obj2 <- rqt(phenotype=pheno, genotype=geno.obj) data3 <- data.matrix(read.table(system.file("extdata/phengen.dat", package="rqt"), skip=1)) pheno <- data3[,1] geno <- data3[, 2:dim(data3)[2]] colnames(geno) <- paste(seq(1, dim(geno)[2])) geno.obj <- SummarizedExperiment(geno) obj3 <- rqt(phenotype=pheno, genotype=geno.obj) res.meta <- geneTestMeta(list(obj1, obj2, obj3)) print(res.meta) ```