Browsing by Subject "statistical significance"

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  • Kanduri, C.; Järvelä, I. (2017)
    Modern high-throughput studies often yield long lists of genes, a fraction of which are of high relevance to the phenotype of interest. To prioritize the candidate genes of complex genetic traits, our R/Bioconductor package GenRank ranks genes based on convergent evidence obtained from multiple layers of independent evidence. We implemented three methods to rank genes that integrate gene-level data generated from multiple layers of evidence: (a) the convergent evidence (CE) method aggregates evidence based on a weighted vote counting method; (b) the rank product (RP) method performs a meta-analysis of microarray-based gene expression data, and (c) the traditional method combines p-values. The methods are implemented in R and are available as a package in the Bioconductor repository. ( © 2017 Kanduri C and Järvelä I.