MatchRanges: generating null hypothesis genomic ranges via covariate-matched sampling.

ABSTRACT:

Motivation

Deriving biological insights from genomic data commonly requires comparing attributes of selected genomic loci to a null set of loci. The selection of this null set is non-trivial, as it requires careful consideration of potential covariates, a problem that is exacerbated by the non-uniform distribution of genomic features including genes, enhancers, and transcription factor binding sites. Propensity score-based covariate matching methods allow the selection of null sets from a pool of possible items while controlling for multiple covariates; however, existing packages do not operate on genomic data classes and can be slow for large data sets making them difficult to integrate into genomic workflows.

Results

To address this, we developed matchRanges, a propensity

SUBMITTER: Davis ES 

PROVIDER: S-EPMC10168584 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature