The Poisson distribution model fits UMI-based single-cell RNA-sequencing data.

ABSTRACT:

Background

Modeling of single cell RNA-sequencing (scRNA-seq) data remains challenging due to a high percentage of zeros and data heterogeneity, so improved modeling has strong potential to benefit many downstream data analyses. The existing zero-inflated or over-dispersed models are based on aggregations at either the gene or the cell level. However, they typically lose accuracy due to a too crude aggregation at those two levels.

Results

We avoid the crude approximations entailed by such aggregation through proposing an independent Poisson distribution (IPD) particularly at each individual entry in the scRNA-seq data matrix. This approach naturally and intuitively models the large number of zeros as matrix entries with a very small Poisson parameter. The critical challenge

SUBMITTER: Pan Y 

PROVIDER: S-EPMC10276395 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature