Interpreting transcriptional changes using causal graphs: new methods and their practical utility on public networks.

ABSTRACT:

Background

Inference of active regulatory cascades under specific molecular and environmental perturbations is a recurring task in transcriptional data analysis. Commercial tools based on large, manually curated networks of causal relationships offering such functionality have been used in thousands of articles in the biomedical literature. The adoption and extension of such methods in the academic community has been hampered by the lack of freely available, efficient algorithms and an accompanying demonstration of their applicability using current public networks.

Results

In this article, we propose a new statistical method that will infer likely upstream regulators based on observed patterns of up- and down-regulated transcripts. The method is suitable for use with public

SUBMITTER: Fakhry CT 

PROVIDER: S-EPMC4995651 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature