MultiDCoX: Multi-factor Analysis of Differential Co-expression

Overview

Journal BMC Bioinformatics

Publisher Biomed Central

Specialty Biology

Date 2018 Jan 4

PMID 29297310

Citations 2

Authors

Herty Liany

Jagath C Rajapakse

R Krishna Murthy Karuturi

Affiliations

Soon will be listed here.

Abstract

Background: Differential co-expression (DCX) signifies change in degree of co-expression of a set of genes among different biological conditions. It has been used to identify differential co-expression networks or interactomes. Many algorithms have been developed for single-factor differential co-expression analysis and applied in a variety of studies. However, in many studies, the samples are characterized by multiple factors such as genetic markers, clinical variables and treatments. No algorithm or methodology is available for multi-factor analysis of differential co-expression.

Results: We developed a novel formulation and a computationally efficient greedy search algorithm called MultiDCoX to perform multi-factor differential co-expression analysis. Simulated data analysis demonstrates that the algorithm can effectively elicit differentially co-expressed (DCX) gene sets and quantify the influence of each factor on co-expression. MultiDCoX analysis of a breast cancer dataset identified interesting biologically meaningful differentially co-expressed (DCX) gene sets along with genetic and clinical factors that influenced the respective differential co-expression.

Conclusions: MultiDCoX is a space and time efficient procedure to identify differentially co-expressed gene sets and successfully identify influence of individual factors on differential co-expression.

Citing Articles

Differential Co-Expression Analyses Allow the Identification of Critical Signalling Pathways Altered during Tumour Transformation and Progression.

Savino A, Provero P, Poli V Int J Mol Sci. 2020; 21(24).

PMID: 33322692 PMC: 7764314. DOI: 10.3390/ijms21249461.

A bioinformatics potpourri.

Schonbach C, Li J, Ma L, Horton P, Sjaugi M, Ranganathan S BMC Genomics. 2018; 19(Suppl 1):920.

PMID: 29363432 PMC: 5780851. DOI: 10.1186/s12864-017-4326-x.

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