##Note: you should be using the ALDEx_bioc repository instead!
To install this development version:
Install the release version at bioconductor [https://bioconductor.org/packages/release/bioc/html/ALDEx2.html]
Download the ALDEx2_n.n.n.tar.gz file to your computer
Inside an R session type:
install.packages("path/to/install.packages("ALDEx2_n.n.n.tar.gz", repos=NULL, type="source")
You should be good to go. The only issue may be missing dependencies. These may have to be installed from Bioconductor directly if the development and release versions are wildely out of sync.
ALDEx tool to examine compositional high-throughput sequence data.
A differential relative count abundance analysis for the comparison of two conditions. For example, single-organism and meta-rna-seq high-throughput sequencing assays, or of selected and unselected values from in-vitro sequence selections. Uses a Dirichlet-multinomial model to infer abundance from counts, that has been optimized for three or more experimental replicates. Infers sampling variation and calculates the expected Benjamini-Hochberg false discovery rate given the biological and sampling variation using several parametric and non-parametric tests. Can to glm and Kruskal-Wallace tests on one-way ANOVA style designs.
Note on versioning: ALDEx2_2.0.7.2 was the base for adding the package to Bioconductor, and the Bioconductor rules indicate that the initial version must be 0.99.?. Therefore, the current version is ALDEx2_0.99.1.tar.gz. This version contains bug fixes and formatting changes that make it compatible with the Bioconductor rules. This version also has parallel execution turned ##OFF# by default. To enable parallel execution for aldex.clr, aldex.glm and aldex.effect set useMC=TRUE when invoking the functions. This version of ALDEx2 is able to accept a set of custom features for centering all features against. Use ?aldex.clr for more information.
Current version: ALDEx2_1.1.5.tar.gz Current manual: manual/ALDE2_manual.pdf Current vinette: ALDEx2_vignette.pdf
ALDEx 1.0.4 from Fernandes et al, 2013 PLoS ONE for historical reasons.