Investigating the effect of dependence between conditions with Bayesian Linear Mixed Models for motif activity analysis.

ABSTRACT: MOTIVATION:Cellular identity and behavior is controlled by complex gene regulatory networks. Transcription factors (TFs) bind to specific DNA sequences to regulate the transcription of their target genes. On the basis of these TF motifs in cis-regulatory elements we can model the influence of TFs on gene expression. In such models of TF motif activity the data is usually modeled assuming a linear relationship between the motif activity and the gene expression level. A commonly used method to model motif influence is based on Ridge Regression. One important assumption of linear regression is the independence between samples. However, if samples are generated from the same cell line, tissue, or other biological source, this assumption may be invalid. This same assumption of independence is a

SUBMITTER: Lederer S 

PROVIDER: S-EPMC7194367 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature