Inferring and analyzing gene regulatory networks from multi-factorial expression data: a complete and interactive suite.

ABSTRACT:

Background

High-throughput transcriptomic datasets are often examined to discover new actors and regulators of a biological response. To this end, graphical interfaces have been developed and allow a broad range of users to conduct standard analyses from RNA-seq data, even with little programming experience. Although existing solutions usually provide adequate procedures for normalization, exploration or differential expression, more advanced features, such as gene clustering or regulatory network inference, often miss or do not reflect current state of the art methodologies.

Results

We developed here a user interface called DIANE (Dashboard for the Inference and Analysis of Networks from Expression data) designed to harness the potential of multi-factorial expression datase

SUBMITTER: Cassan O 

PROVIDER: S-EPMC8152307 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature