DataRemix: a universal data transformation for optimal inference from gene expression datasets.

ABSTRACT:

Motivation

RNA-seq technology provides unprecedented power in the assessment of the transcription abundance and can be used to perform a variety of downstream tasks such as inference of gene-correlation network and eQTL discovery. However, raw gene expression values have to be normalized for nuisance biological variation and technical covariates, and different normalization strategies can lead to dramatically different results in the downstream study.

Results

We describe a generalization of singular value decomposition-based reconstruction for which the common techniques of whitening, rank-k approximation and removing the top k principal components are special cases. Our simple three-parameter transformation, DataRemix, can be tuned to reweigh the contribution of hidden fact

SUBMITTER: Mao W 

PROVIDER: S-EPMC8128479 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature