S3V2-IDEAS: a package for normalizing, denoising and integrating epigenomic datasets across different cell types.

ABSTRACT:

Summary

Epigenetic modifications reflect key aspects of transcriptional regulation, and many epigenomic datasets have been generated under different biological contexts to provide insights into regulatory processes. However, the technical noise in epigenomic datasets and the many dimensions (features) examined make it challenging to effectively extract biologically meaningful inferences from these datasets. We developed a package that reduces noise while normalizing the epigenomic data by a novel normalization method, followed by integrative dimensional reduction by learning and assigning epigenetic states. This package, called S3V2-IDEAS, can be used to identify epigenetic states for multiple features, or identify discretized signal intensity levels and a master peak list across d

SUBMITTER: Xiang G 

PROVIDER: S-EPMC8479670 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature