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Assessment of statistical methods from single cell, bulk RNA-seq, and metagenomics applied to microbiome data
2020
Genome Biology
The correct identification of differentially abundant microbial taxa between experimental conditions is a methodological and computational challenge. Recent work has produced methods to deal with the high sparsity and compositionality characteristic of microbiome data, but independent benchmarks comparing these to alternatives developed for RNA-seq data analysis are lacking. We compare methods developed for single-cell and bulk RNA-seq, and specifically for microbiome data, in terms of
doi:10.1186/s13059-020-02104-1
pmid:32746888
fatcat:yxxh5ogdzjcovc7jmzfeceidqe