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COGENT: evaluating the consistency of gene co-expression networks
SUMMARY: Gene co-expression networks can be constructed in multiple different ways, both in the use of different measures of co-expression, and in the thresholds applied to the calculated co-expression values, from any given dataset. It is often not clear which co-expression network construction met...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8317122/ https://www.ncbi.nlm.nih.gov/pubmed/32931579 http://dx.doi.org/10.1093/bioinformatics/btaa787 |
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author | Bozhilova, Lyuba V. Pardo-Diaz, Javier Reinert, Gesine Deane, Charlotte M. |
author_facet | Bozhilova, Lyuba V. Pardo-Diaz, Javier Reinert, Gesine Deane, Charlotte M. |
author_sort | Bozhilova, Lyuba V. |
collection | PubMed |
description | SUMMARY: Gene co-expression networks can be constructed in multiple different ways, both in the use of different measures of co-expression, and in the thresholds applied to the calculated co-expression values, from any given dataset. It is often not clear which co-expression network construction method should be preferred. COGENT provides a set of tools designed to aid the choice of network construction method without the need for any external validation data. AVAILABILITY AND IMPLEMENTATION: https://github.com/lbozhilova/COGENT. SUPPLEMENTARY INFORMATION: Supplementary information is available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-8317122 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-83171222021-07-29 COGENT: evaluating the consistency of gene co-expression networks Bozhilova, Lyuba V. Pardo-Diaz, Javier Reinert, Gesine Deane, Charlotte M. Bioinformatics Applications Notes SUMMARY: Gene co-expression networks can be constructed in multiple different ways, both in the use of different measures of co-expression, and in the thresholds applied to the calculated co-expression values, from any given dataset. It is often not clear which co-expression network construction method should be preferred. COGENT provides a set of tools designed to aid the choice of network construction method without the need for any external validation data. AVAILABILITY AND IMPLEMENTATION: https://github.com/lbozhilova/COGENT. SUPPLEMENTARY INFORMATION: Supplementary information is available at Bioinformatics online. Oxford University Press 2020-09-15 /pmc/articles/PMC8317122/ /pubmed/32931579 http://dx.doi.org/10.1093/bioinformatics/btaa787 Text en © The Author(s) 2020. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Notes Bozhilova, Lyuba V. Pardo-Diaz, Javier Reinert, Gesine Deane, Charlotte M. COGENT: evaluating the consistency of gene co-expression networks |
title | COGENT: evaluating the consistency of gene co-expression networks |
title_full | COGENT: evaluating the consistency of gene co-expression networks |
title_fullStr | COGENT: evaluating the consistency of gene co-expression networks |
title_full_unstemmed | COGENT: evaluating the consistency of gene co-expression networks |
title_short | COGENT: evaluating the consistency of gene co-expression networks |
title_sort | cogent: evaluating the consistency of gene co-expression networks |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8317122/ https://www.ncbi.nlm.nih.gov/pubmed/32931579 http://dx.doi.org/10.1093/bioinformatics/btaa787 |
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