ScKWARN: Kernel-weighted-average robust normalization for single-cell RNA-seq data.

ABSTRACT:

Motivation

Single-cell RNA-seq normalization is an essential step to correct unwanted biases caused by sequencing depth, capture efficiency, dropout, and other technical factors. Existing normalization methods primarily reduce biases arising from sequencing depth by modeling count-depth relationship and/or assuming a specific distribution for read counts. However, these methods may lead to over or under-correction due to presence of technical biases beyond sequencing depth and the restrictive assumption on models and distributions.

Results

We present scKWARN, a Kernel Weighted Average Robust Normalization designed to correct known or hidden technical confounders without assuming specific data distributions or count-depth relationships. scKWARN generates a pseudo expression p

SUBMITTER: Hsu CY 

PROVIDER: S-EPMC10868328 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature