HGCA2.0: An RNA-Seq Based Webtool for Gene Coexpression Analysis in Homo sapiens

Author:

Zogopoulos Vasileios L.12ORCID,Malatras Apostolos3ORCID,Kyriakidis Konstantinos14ORCID,Charalampous Chrysanthi5,Makrygianni Evanthia A.6,Duguez Stéphanie7ORCID,Koutsi Marianna A.5ORCID,Pouliou Marialena5,Vasileiou Christos18,Duddy William J.7ORCID,Agelopoulos Marios5,Chrousos George P.6ORCID,Iconomidou Vassiliki A.2ORCID,Michalopoulos Ioannis1ORCID

Affiliation:

1. Centre of Systems Biology, Biomedical Research Foundation, Academy of Athens, 11527 Athens, Greece

2. Section of Cell Biology and Biophysics, Department of Biology, National and Kapodistrian University of Athens, 15701 Athens, Greece

3. Biobank.cy Center of Excellence in Biobanking and Biomedical Research, University of Cyprus, 2029 Nicosia, Cyprus

4. School of Pharmacy, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece

5. Centre of Basic Research, Biomedical Research Foundation, Academy of Athens, 11527 Athens, Greece

6. University Research Institute of Maternal and Child Health and Precision Medicine, National and Kapodistrian University of Athens, 11527 Athens, Greece

7. Personalised Medicine Centre, School of Medicine, Ulster University, Derry-Londonderry BT47 6SB, UK

8. Engineering Design and Computing Laboratory, ETH Zurich, 8092 Zurich, Switzerland

Abstract

Genes with similar expression patterns in a set of diverse samples may be considered coexpressed. Human Gene Coexpression Analysis 2.0 (HGCA2.0) is a webtool which studies the global coexpression landscape of human genes. The website is based on the hierarchical clustering of 55,431 Homo sapiens genes based on a large-scale coexpression analysis of 3500 GTEx bulk RNA-Seq samples of healthy individuals, which were selected as the best representative samples of each tissue type. HGCA2.0 presents subclades of coexpressed genes to a gene of interest, and performs various built-in gene term enrichment analyses on the coexpressed genes, including gene ontologies, biological pathways, protein families, and diseases, while also being unique in revealing enriched transcription factors driving coexpression. HGCA2.0 has been successful in identifying not only genes with ubiquitous expression patterns, but also tissue-specific genes. Benchmarking showed that HGCA2.0 belongs to the top performing coexpression webtools, as shown by STRING analysis. HGCA2.0 creates working hypotheses for the discovery of gene partners or common biological processes that can be experimentally validated. It offers a simple and intuitive website design and user interface, as well as an API endpoint.

Funder

ELIXIR-GR

Publisher

MDPI AG

Subject

General Medicine

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3