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  • Update in the gage RNA-seq pathway analysis joint workflow

    There were some typos in page 11 of the “RNA-seq Data Pathway and Gene-set Analysis Workflows” vignette (gage 2.12.1, December 20, 2013). This only occurred with the joint workflow details (with DESeq/DESeq2, edgeR, Limma or Cufflinks). RNA-Seq pathway analyses following the native workflow or the Quick Start are not affected.

    Original code was:
    ..
    sel.l <- cnts.kegg.p$less[, "q.val"] < 0.1 & !is.na(cnts.kegg.p$less[,"q.val"])
    path.ids.l <- rownames(cnts.kegg.p$less)[sel.l]
    ..
    The typos resulted in “Error: object 'cnts.kegg.p' not found”. Here cnts.kegg.p should be fc.kegg.p instead. The typos have been corrected in the updated package (gage 2.12.2):
    GAGE is a published method for gene set (enrichment or GSEA) or pathway analysis. GAGE is generally applicable independent of microarray or RNA-Seq data attributes including sample sizes, experimental designs, assay platforms, and other types of heterogeneity, and consistently achieves superior performance over other frequently used methods. In gage package, we provide functions for basic GAGE analysis, result processing and presentation. We have also built pipeline routines for of multiple GAGE analyses in a batch, comparison between parallel analyses, and combined analysis of heterogeneous data from different sources/studies. In addition, we provide demo microarray data and commonly used gene set data based on KEGG pathways and GO terms. These funtions and data are also useful for gene set analysis using other methods.

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