A Web Tool for Consensus Gene Regulatory Network Construction.

PHP consensus approach fisher’s weighted method gene regulatory network web tool

Journal

Frontiers in genetics
ISSN: 1664-8021
Titre abrégé: Front Genet
Pays: Switzerland
ID NLM: 101560621

Informations de publication

Date de publication:
2021
Historique:
received: 22 07 2021
accepted: 19 10 2021
entrez: 13 12 2021
pubmed: 14 12 2021
medline: 14 12 2021
Statut: epublish

Résumé

Gene regulatory network (GRN) construction involves various steps of complex computational steps. This step-by-step procedure requires prior knowledge of programming languages such as R. Development of a web tool may reduce this complexity in the analysis steps which can be easy accessible for the user. In this study, a web tool for constructing consensus GRN by combining the outcomes obtained from four methods, namely, correlation, principal component regression, partial least square, and ridge regression, has been developed. We have designed the web tool with an interactive and user-friendly web page using the php programming language. We have used R script for the analysis steps which run in the background of the user interface. Users can upload gene expression data for constructing consensus GRN. The output obtained from analysis will be available in downloadable form in the result window of the web tool.

Identifiants

pubmed: 34899837
doi: 10.3389/fgene.2021.745827
pii: 745827
pmc: PMC8652126
doi:

Types de publication

Journal Article

Langues

eng

Pagination

745827

Informations de copyright

Copyright © 2021 Sarkar, Parsad, Mishra and Rai.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Chiranjib Sarkar (C)

ICAR-Indian Agricultural Research Institute, New Delhi, India.

Rajender Parsad (R)

ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India.

Dwijesh C Mishra (DC)

ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India.

Anil Rai (A)

ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India.

Classifications MeSH