TascCODA: Bayesian Tree-Aggregated Analysis of Compositional Amplicon and Single-Cell Data.

ABSTRACT: Accurate generative statistical modeling of count data is of critical relevance for the analysis of biological datasets from high-throughput sequencing technologies. Important instances include the modeling of microbiome compositions from amplicon sequencing surveys and the analysis of cell type compositions derived from single-cell RNA sequencing. Microbial and cell type abundance data share remarkably similar statistical features, including their inherent compositionality and a natural hierarchical ordering of the individual components from taxonomic or cell lineage tree information, respectively. To this end, we introduce a Bayesian model for tree-aggregated amplicon and single-cell compositional data analysis (tascCODA) that seamlessly i

SUBMITTER: Ostner J 

PROVIDER: S-EPMC8689185 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature