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bioc
dar:Differential Abundance Analysis by Consensus
Differential abundance testing in microbiome data challenges both parametric and non-parametric statistical methods, due to its sparsity, high variability and compositional nature. Microbiome-specific statistical methods often assume classical distribution models or take into account compositional specifics. These produce results that range within the specificity vs sensitivity space in such a way that type I and type II error that are difficult to ascertain in real microbiome data when a single method is used. Recently, a consensus approach based on multiple differential abundance (DA) methods was recently suggested in order to increase robustness. With dar, you can use dplyr-like pipeable sequences of DA methods and then apply different consensus strategies. In this way we can obtain more reliable results in a fast, consistent and reproducible way.
Maintained by Francesc Catala-Moll. Last updated 18 days ago.
softwaresequencingmicrobiomemetagenomicsmultiplecomparisonnormalizationbioconductorbiomarker-discoverydifferential-abundance-analysisfeature-selectionmicrobiologyphyloseq
2 stars 5.98 score 8 scripts
eddelbuettel
rfoaas:R Interface to 'FOAAS'
R access to the 'FOAAS' (F... Off As A Service) web service is provided.
Maintained by Dirk Eddelbuettel. Last updated 5 months ago.
28 stars 5.23 score 6 scripts