Differential co-expression network analysis with DCoNA reveals isomiR targeting aberrations in prostate cancer.

ABSTRACT:

Motivation

One of the standard methods of high-throughput RNA sequencing analysis is differential expression. However, it does not detect changes in molecular regulation. In contrast to the standard differential expression analysis, differential co-expression one aims to detect pairs or clusters whose mutual expression changes between two conditions.

Results

We developed Differential Co-expression Network Analysis (DCoNA)-an open-source statistical tool that allows one to identify pair interactions, which correlation significantly changes between two conditions. Comparing DCoNA with the state-of-the-art analog, we showed that DCoNA is a faster, more accurate and less memory-consuming tool. We applied DCoNA to prostate mRNA/miRNA-seq data collected from The Cancer Genome Atla

SUBMITTER: Zhiyanov A 

PROVIDER: S-EPMC9901399 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature