Bayesian correlation is a robust gene similarity measure for single-cell RNA-seq data.

ABSTRACT: Assessing similarity is highly important for bioinformatics algorithms to determine correlations between biological information. A common problem is that similarity can appear by chance, particularly for low expressed entities. This is especially relevant in single-cell RNA-seq (scRNA-seq) data because read counts are much lower compared to bulk RNA-seq. Recently, a Bayesian correlation scheme that assigns low similarity to genes that have low confidence expression estimates has been proposed to assess similarity for bulk RNA-seq. Our goal is to extend the properties of the Bayesian correlation in scRNA-seq data by considering three ways to compute similarity. First, we compute the similarity of pairs of genes over all cells. Second, we identify specific cell populations and compute the co

SUBMITTER: Sanchez-Taltavull D 

PROVIDER: S-EPMC7671344 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature