BaredSC: Bayesian approach to retrieve expression distribution of single-cell data.

ABSTRACT:

Background

The number of studies using single-cell RNA sequencing (scRNA-seq) is constantly growing. This powerful technique provides a sampling of the whole transcriptome of a cell. However, sparsity of the data can be a major hurdle when studying the distribution of the expression of a specific gene or the correlation between the expressions of two genes.

Results

We show that the main technical noise associated with these scRNA-seq experiments is due to the sampling, i.e., Poisson noise. We present a new tool named baredSC, for Bayesian Approach to Retrieve Expression Distribution of Single-Cell data, which infers the intrinsic expression distribution in scRNA-seq data using a Gaussian mixture model. baredSC can be used to obtain the distribution in one dimension for indiv

SUBMITTER: Lopez-Delisle L 

PROVIDER: S-EPMC8756634 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature