HGCA2.0: An RNA-Seq Based Webtool for Gene Coexpression Analysis in <i>Homo sapiens</i>
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 <i>Homo sa...
| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-01-01
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| Series: | Cells |
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| Online Access: | https://www.mdpi.com/2073-4409/12/3/388 |
| _version_ | 1797624885889990656 |
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| author | Vasileios L. Zogopoulos Apostolos Malatras Konstantinos Kyriakidis Chrysanthi Charalampous Evanthia A. Makrygianni Stéphanie Duguez Marianna A. Koutsi Marialena Pouliou Christos Vasileiou William J. Duddy Marios Agelopoulos George P. Chrousos Vassiliki A. Iconomidou Ioannis Michalopoulos |
| author_facet | Vasileios L. Zogopoulos Apostolos Malatras Konstantinos Kyriakidis Chrysanthi Charalampous Evanthia A. Makrygianni Stéphanie Duguez Marianna A. Koutsi Marialena Pouliou Christos Vasileiou William J. Duddy Marios Agelopoulos George P. Chrousos Vassiliki A. Iconomidou Ioannis Michalopoulos |
| author_sort | Vasileios L. Zogopoulos |
| collection | DOAJ |
| description | 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 <i>Homo sapiens</i> 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. |
| first_indexed | 2024-03-11T09:49:03Z |
| format | Article |
| id | doaj.art-5baa97564d3b4d308b3a022df8935b6e |
| institution | Directory Open Access Journal |
| issn | 2073-4409 |
| language | English |
| last_indexed | 2024-03-11T09:49:03Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Cells |
| spelling | doaj.art-5baa97564d3b4d308b3a022df8935b6e2023-11-16T16:20:55ZengMDPI AGCells2073-44092023-01-0112338810.3390/cells12030388HGCA2.0: An RNA-Seq Based Webtool for Gene Coexpression Analysis in <i>Homo sapiens</i>Vasileios L. Zogopoulos0Apostolos Malatras1Konstantinos Kyriakidis2Chrysanthi Charalampous3Evanthia A. Makrygianni4Stéphanie Duguez5Marianna A. Koutsi6Marialena Pouliou7Christos Vasileiou8William J. Duddy9Marios Agelopoulos10George P. Chrousos11Vassiliki A. Iconomidou12Ioannis Michalopoulos13Centre of Systems Biology, Biomedical Research Foundation, Academy of Athens, 11527 Athens, GreeceBiobank.cy Center of Excellence in Biobanking and Biomedical Research, University of Cyprus, 2029 Nicosia, CyprusCentre of Systems Biology, Biomedical Research Foundation, Academy of Athens, 11527 Athens, GreeceCentre of Basic Research, Biomedical Research Foundation, Academy of Athens, 11527 Athens, GreeceUniversity Research Institute of Maternal and Child Health and Precision Medicine, National and Kapodistrian University of Athens, 11527 Athens, GreecePersonalised Medicine Centre, School of Medicine, Ulster University, Derry-Londonderry BT47 6SB, UKCentre of Basic Research, Biomedical Research Foundation, Academy of Athens, 11527 Athens, GreeceCentre of Basic Research, Biomedical Research Foundation, Academy of Athens, 11527 Athens, GreeceCentre of Systems Biology, Biomedical Research Foundation, Academy of Athens, 11527 Athens, GreecePersonalised Medicine Centre, School of Medicine, Ulster University, Derry-Londonderry BT47 6SB, UKCentre of Basic Research, Biomedical Research Foundation, Academy of Athens, 11527 Athens, GreeceUniversity Research Institute of Maternal and Child Health and Precision Medicine, National and Kapodistrian University of Athens, 11527 Athens, GreeceSection of Cell Biology and Biophysics, Department of Biology, National and Kapodistrian University of Athens, 15701 Athens, GreeceCentre of Systems Biology, Biomedical Research Foundation, Academy of Athens, 11527 Athens, GreeceGenes 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 <i>Homo sapiens</i> 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.https://www.mdpi.com/2073-4409/12/3/388gene coexpression analysisgene coexpression networkco-expressionRNA-Seqtranscriptomicsbioinformatics |
| spellingShingle | Vasileios L. Zogopoulos Apostolos Malatras Konstantinos Kyriakidis Chrysanthi Charalampous Evanthia A. Makrygianni Stéphanie Duguez Marianna A. Koutsi Marialena Pouliou Christos Vasileiou William J. Duddy Marios Agelopoulos George P. Chrousos Vassiliki A. Iconomidou Ioannis Michalopoulos HGCA2.0: An RNA-Seq Based Webtool for Gene Coexpression Analysis in <i>Homo sapiens</i> Cells gene coexpression analysis gene coexpression network co-expression RNA-Seq transcriptomics bioinformatics |
| title | HGCA2.0: An RNA-Seq Based Webtool for Gene Coexpression Analysis in <i>Homo sapiens</i> |
| title_full | HGCA2.0: An RNA-Seq Based Webtool for Gene Coexpression Analysis in <i>Homo sapiens</i> |
| title_fullStr | HGCA2.0: An RNA-Seq Based Webtool for Gene Coexpression Analysis in <i>Homo sapiens</i> |
| title_full_unstemmed | HGCA2.0: An RNA-Seq Based Webtool for Gene Coexpression Analysis in <i>Homo sapiens</i> |
| title_short | HGCA2.0: An RNA-Seq Based Webtool for Gene Coexpression Analysis in <i>Homo sapiens</i> |
| title_sort | hgca2 0 an rna seq based webtool for gene coexpression analysis in i homo sapiens i |
| topic | gene coexpression analysis gene coexpression network co-expression RNA-Seq transcriptomics bioinformatics |
| url | https://www.mdpi.com/2073-4409/12/3/388 |
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