Clust: automatic extraction of optimal co-expressed gene clusters from gene expression data
Abstract Identifying co-expressed gene clusters can provide evidence for genetic or physical interactions. Thus, co-expression clustering is a routine step in large-scale analyses of gene expression data. We show that commonly used clustering methods produce results that substantially disagree and t...
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| Format: | Article |
| Language: | English |
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BMC
2018-10-01
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| Series: | Genome Biology |
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| Online Access: | http://link.springer.com/article/10.1186/s13059-018-1536-8 |
| _version_ | 1819042395012988928 |
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| author | Basel Abu-Jamous Steven Kelly |
| author_facet | Basel Abu-Jamous Steven Kelly |
| author_sort | Basel Abu-Jamous |
| collection | DOAJ |
| description | Abstract Identifying co-expressed gene clusters can provide evidence for genetic or physical interactions. Thus, co-expression clustering is a routine step in large-scale analyses of gene expression data. We show that commonly used clustering methods produce results that substantially disagree and that do not match the biological expectations of co-expressed gene clusters. We present clust, a method that solves these problems by extracting clusters matching the biological expectations of co-expressed genes and outperforms widely used methods. Additionally, clust can simultaneously cluster multiple datasets, enabling users to leverage the large quantity of public expression data for novel comparative analysis. Clust is available at https://github.com/BaselAbujamous/clust. |
| first_indexed | 2024-12-21T09:40:12Z |
| format | Article |
| id | doaj.art-30a34cf733ac4e7ab9cf834faa809434 |
| institution | Directory Open Access Journal |
| issn | 1474-760X |
| language | English |
| last_indexed | 2024-12-21T09:40:12Z |
| publishDate | 2018-10-01 |
| publisher | BMC |
| record_format | Article |
| series | Genome Biology |
| spelling | doaj.art-30a34cf733ac4e7ab9cf834faa8094342022-12-21T19:08:29ZengBMCGenome Biology1474-760X2018-10-0119111110.1186/s13059-018-1536-8Clust: automatic extraction of optimal co-expressed gene clusters from gene expression dataBasel Abu-Jamous0Steven Kelly1Department of Plant Sciences, University of OxfordDepartment of Plant Sciences, University of OxfordAbstract Identifying co-expressed gene clusters can provide evidence for genetic or physical interactions. Thus, co-expression clustering is a routine step in large-scale analyses of gene expression data. We show that commonly used clustering methods produce results that substantially disagree and that do not match the biological expectations of co-expressed gene clusters. We present clust, a method that solves these problems by extracting clusters matching the biological expectations of co-expressed genes and outperforms widely used methods. Additionally, clust can simultaneously cluster multiple datasets, enabling users to leverage the large quantity of public expression data for novel comparative analysis. Clust is available at https://github.com/BaselAbujamous/clust.http://link.springer.com/article/10.1186/s13059-018-1536-8ClusteringGene expression dataClustK-meansCross-clusteringClick |
| spellingShingle | Basel Abu-Jamous Steven Kelly Clust: automatic extraction of optimal co-expressed gene clusters from gene expression data Genome Biology Clustering Gene expression data Clust K-means Cross-clustering Click |
| title | Clust: automatic extraction of optimal co-expressed gene clusters from gene expression data |
| title_full | Clust: automatic extraction of optimal co-expressed gene clusters from gene expression data |
| title_fullStr | Clust: automatic extraction of optimal co-expressed gene clusters from gene expression data |
| title_full_unstemmed | Clust: automatic extraction of optimal co-expressed gene clusters from gene expression data |
| title_short | Clust: automatic extraction of optimal co-expressed gene clusters from gene expression data |
| title_sort | clust automatic extraction of optimal co expressed gene clusters from gene expression data |
| topic | Clustering Gene expression data Clust K-means Cross-clustering Click |
| url | http://link.springer.com/article/10.1186/s13059-018-1536-8 |
| work_keys_str_mv | AT baselabujamous clustautomaticextractionofoptimalcoexpressedgeneclustersfromgeneexpressiondata AT stevenkelly clustautomaticextractionofoptimalcoexpressedgeneclustersfromgeneexpressiondata |