Thirty biologically interpretable clusters of transcription factors distinguish cancer type.

ABSTRACT:

Background

Transcription factors are essential regulators of gene expression and play critical roles in development, differentiation, and in many cancers. To carry out their regulatory programs, they must cooperate in networks and bind simultaneously to sites in promoter or enhancer regions of genes. We hypothesize that the mRNA co-expression patterns of transcription factors can be used both to learn how they cooperate in networks and to distinguish between cancer types.

Results

We recently developed a new algorithm, Thresher, that combines principal component analysis, outlier filtering, and von Mises-Fisher mixture models to cluster genes (in this case, transcription factors) based on expression, determining the optimal number of clusters in the process. We applied Thresh

SUBMITTER: Abrams ZB 

PROVIDER: S-EPMC6180590 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature