BASiCS is an integrated Bayesian model that deals with technical noise in single-cell mRNA sequencing experiments. BASiCS simultaneously performs data normalization, technical noise quantification and two types of supervised downstream analyses:

• To identify highly and lowly variable genes within a single group of cells
• To perform differential expression analyses between two groups of cells. Beyond traditional differential expression tools, BASiCS highlights changes in cell-to-cell variability of gene expression.

In both cases, a probabilistic output is provided, with posterior probability thresholds calibrated through the expected false discovery rate.

BASiCS is now part of Bioconductor

An experimental (sometimes unstable) version of BASiCS is available at: github.com/catavallejos/BASiCS