BioConductor

ALDEx2 1.11.1

Analysis Of Differential Abundance Taking Sample Variation Into Account

Released Oct 11, 2017 by Greg Gloor

This package cannot yet be used with Renjin it depends on other packages which are not available: IRanges 2.13.10, S4Vectors 0.17.22, GenomicRanges 1.31.6, SummarizedExperiment 1.9.7, BiocParallel 1.13.1, and multtest 2.35.0 An older version of this package is more compatible with Renjin.

Dependencies

S4Vectors 0.17.22 IRanges 2.13.10 SummarizedExperiment 1.9.7 BiocParallel 1.13.1 multtest 2.35.0 GenomicRanges 1.31.6

A differential abundance analysis for the comparison of two or more conditions. Useful for analyzing data from standard RNA-seq or meta-RNA-seq assays as well as selected and unselected values from in-vitro sequence selections. Uses a Dirichlet-multinomial model to infer abundance from counts, optimized for three or more experimental replicates. The method infers biological and sampling variation to calculate the expected false discovery rate, given the variation, based on a Wilcox rank test or Welch t-test (via aldex.ttest), or a glm and Kruskal-Wallis test (via aldex.glm). Reports p-values and Benjamini-Hochberg corrected p-values.

Source

R

Release History