PT  - JOURNAL ARTICLE
AU  - Herty Liany
AU  - Jagath C. Rajapakse
AU  - R. Krishna Murthy Karuturi
TI  - MultiDCoX: Multi-factor Analysis of Differential Coexpression
AID  - 10.1101/114397
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 114397
4099  - http://biorxiv.org/content/early/2017/03/06/114397.short
4100  - http://biorxiv.org/content/early/2017/03/06/114397.full
AB  - Background Differential co-expression 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 of transcriptomic data. 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 coexpressed (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.Software R function will be available upon request.AbbreviationsDCXDifferential Co-expression/Differentially Co-expressedDEDifferential ExpressionGOGene OntologyKEGGKyoto Encyclopaedia of Genes and GenomesFPsFalse PositivesFNsFalse NegativesFNRFalse Negative RateFDRFalse Discovery RateFPRFalse Positive RateOROdds RatioHPCHi Performance ComputingEROestrogen Receptor