BROCKMAN: deciphering variance in epigenomic regulators by k-mer factorization.

ABSTRACT:

Background

Variation in chromatin organization across single cells can help shed important light on the mechanisms controlling gene expression, but scale, noise, and sparsity pose significant challenges for interpretation of single cell chromatin data. Here, we develop BROCKMAN (Brockman Representation Of Chromatin by K-mers in Mark-Associated Nucleotides), an approach to infer variation in transcription factor (TF) activity across samples through unsupervised analysis of the variation in DNA sequences associated with an epigenomic mark.

Results

BROCKMAN represents each sample as a vector of epigenomic-mark-associated DNA word frequencies, and decomposes the resulting matrix to find hidden structure in the data, followed by unsupervised grouping of samples and identification

SUBMITTER: de Boer CG 

PROVIDER: S-EPMC6029352 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature