Two-Way Gene Interaction From Microarray Data Based on Correlation Methods.
BACKGROUND
Gene networks have generated a massive explosion in the development of high-throughput techniques for monitoring various aspects of gene activity. Networks offer a natural way to model interactions between genes, and extracting gene network information from high-throughput genomic data is an important and difficult task.


OBJECTIVE
The purpose of this study is to construct a two-way gene network based on parametric and nonparametric correlation coefficients. The first step in constructing a Gene Co-expression Network is to score all pairs of gene vectors. The second step is to select a score threshold and connect all gene pairs whose scores exceed this value.


METHODS
In the foundation-application study, we constructed two-way gene networks using nonparametric methods, such as Spearman's rank correlation coefficient and Blomqvist's measure, and compared them with Pearson's correlation coefficient. We surveyed six genes of venous thrombosis disease, made a matrix entry representing the score for the corresponding gene pair, and obtained two-way interactions using Pearson's correlation, Spearman's rank correlation, and Blomqvist's coefficient. Finally, these methods were compared with Cytoscape, based on BIND, and Gene Ontology, based on molecular function visual methods; R software version 3.2 and Bioconductor were used to perform these methods.


RESULTS
Based on the Pearson and Spearman correlations, the results were the same and were confirmed by Cytoscape and GO visual methods; however, Blomqvist's coefficient was not confirmed by visual methods.


CONCLUSIONS
Some results of the correlation coefficients are not the same with visualization. The reason may be due to the small number of data.
Department of Biostatistics, School of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, IR Iran.
Hamid
H
Alavi Majd
Department of Biostatistics, School of Paramedial Sciences, Students' Research Committee, Shahid Beheshti University of Medical Sciences, Tehran, IR Iran.
Atefeh
A
Talebi
Reproductive Biotechnology Research Center, Avicenna Research Institute, ACECR, Tehran, IR Iran.
Kambiz
K
Gilany
Proteomics Research Center, Shahid Beheshti University of Medical Sciences, Tehran, IR Iran.
Nasibeh
N
Khayyer
Gene Expression; Gene Ontology; Gene Regulatory Networks; Molecular Structure; Nonparametric