A tool for normalization, true count recovery, and imputation of single-cell RNA data. The bayNorm algorithm uses a new Bayesian approach for scaling and inference of counts. The likelihood approach uses a binomial model, and it estimates the priors using empirical Bayesian estimates of values across cells.
Gene expression; RNA-seq
Wenhao Tang, François Bertaux, Philipp Thomas, Claire Stefanelli, Malika Saint, Samuel Marguerat, Vahid Shahrezaei "bayNorm: Bayesian gene expression recovery, imputation and normalization for single-cell RNA-sequencing data" Bioinformatics. 2019 Oct 4. pii: btz726. https://doi.org/10.1093/bioinformatics/btz726
PMID: 31584606
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