Gene-Set Local Hierarchical Clustering (GSLHC)--A Gene Set-Based Approach for Characterizing Bioactive Compounds in Terms of Biological Functional Groups.
Gene-set-based analysis (GSA), which uses the relative importance of functional gene-sets, or molecular signatures, as units for analysis of genome-wide gene expression data, has exhibited major advantages with respect to greater accuracy, robustness, and biological relevance, over individual gene a...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2015-01-01
|
| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC4652590?pdf=render |
| _version_ | 1828387971941793792 |
|---|---|
| author | Feng-Hsiang Chung Zhen-Hua Jin Tzu-Ting Hsu Chueh-Lin Hsu Hsueh-Chuan Liu Hoong-Chien Lee |
| author_facet | Feng-Hsiang Chung Zhen-Hua Jin Tzu-Ting Hsu Chueh-Lin Hsu Hsueh-Chuan Liu Hoong-Chien Lee |
| author_sort | Feng-Hsiang Chung |
| collection | DOAJ |
| description | Gene-set-based analysis (GSA), which uses the relative importance of functional gene-sets, or molecular signatures, as units for analysis of genome-wide gene expression data, has exhibited major advantages with respect to greater accuracy, robustness, and biological relevance, over individual gene analysis (IGA), which uses log-ratios of individual genes for analysis. Yet IGA remains the dominant mode of analysis of gene expression data. The Connectivity Map (CMap), an extensive database on genomic profiles of effects of drugs and small molecules and widely used for studies related to repurposed drug discovery, has been mostly employed in IGA mode. Here, we constructed a GSA-based version of CMap, Gene-Set Connectivity Map (GSCMap), in which all the genomic profiles in CMap are converted, using gene-sets from the Molecular Signatures Database, to functional profiles. We showed that GSCMap essentially eliminated cell-type dependence, a weakness of CMap in IGA mode, and yielded significantly better performance on sample clustering and drug-target association. As a first application of GSCMap we constructed the platform Gene-Set Local Hierarchical Clustering (GSLHC) for discovering insights on coordinated actions of biological functions and facilitating classification of heterogeneous subtypes on drug-driven responses. GSLHC was shown to tightly clustered drugs of known similar properties. We used GSLHC to identify the therapeutic properties and putative targets of 18 compounds of previously unknown characteristics listed in CMap, eight of which suggest anti-cancer activities. The GSLHC website http://cloudr.ncu.edu.tw/gslhc/ contains 1,857 local hierarchical clusters accessible by querying 555 of the 1,309 drugs and small molecules listed in CMap. We expect GSCMap and GSLHC to be widely useful in providing new insights in the biological effect of bioactive compounds, in drug repurposing, and in function-based classification of complex diseases. |
| first_indexed | 2024-12-10T06:04:38Z |
| format | Article |
| id | doaj.art-d0993b994044402798f59621e1dcd8b7 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-10T06:04:38Z |
| publishDate | 2015-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-d0993b994044402798f59621e1dcd8b72022-12-22T01:59:44ZengPublic Library of Science (PLoS)PLoS ONE1932-62032015-01-011010e013988910.1371/journal.pone.0139889Gene-Set Local Hierarchical Clustering (GSLHC)--A Gene Set-Based Approach for Characterizing Bioactive Compounds in Terms of Biological Functional Groups.Feng-Hsiang ChungZhen-Hua JinTzu-Ting HsuChueh-Lin HsuHsueh-Chuan LiuHoong-Chien LeeGene-set-based analysis (GSA), which uses the relative importance of functional gene-sets, or molecular signatures, as units for analysis of genome-wide gene expression data, has exhibited major advantages with respect to greater accuracy, robustness, and biological relevance, over individual gene analysis (IGA), which uses log-ratios of individual genes for analysis. Yet IGA remains the dominant mode of analysis of gene expression data. The Connectivity Map (CMap), an extensive database on genomic profiles of effects of drugs and small molecules and widely used for studies related to repurposed drug discovery, has been mostly employed in IGA mode. Here, we constructed a GSA-based version of CMap, Gene-Set Connectivity Map (GSCMap), in which all the genomic profiles in CMap are converted, using gene-sets from the Molecular Signatures Database, to functional profiles. We showed that GSCMap essentially eliminated cell-type dependence, a weakness of CMap in IGA mode, and yielded significantly better performance on sample clustering and drug-target association. As a first application of GSCMap we constructed the platform Gene-Set Local Hierarchical Clustering (GSLHC) for discovering insights on coordinated actions of biological functions and facilitating classification of heterogeneous subtypes on drug-driven responses. GSLHC was shown to tightly clustered drugs of known similar properties. We used GSLHC to identify the therapeutic properties and putative targets of 18 compounds of previously unknown characteristics listed in CMap, eight of which suggest anti-cancer activities. The GSLHC website http://cloudr.ncu.edu.tw/gslhc/ contains 1,857 local hierarchical clusters accessible by querying 555 of the 1,309 drugs and small molecules listed in CMap. We expect GSCMap and GSLHC to be widely useful in providing new insights in the biological effect of bioactive compounds, in drug repurposing, and in function-based classification of complex diseases.http://europepmc.org/articles/PMC4652590?pdf=render |
| spellingShingle | Feng-Hsiang Chung Zhen-Hua Jin Tzu-Ting Hsu Chueh-Lin Hsu Hsueh-Chuan Liu Hoong-Chien Lee Gene-Set Local Hierarchical Clustering (GSLHC)--A Gene Set-Based Approach for Characterizing Bioactive Compounds in Terms of Biological Functional Groups. PLoS ONE |
| title | Gene-Set Local Hierarchical Clustering (GSLHC)--A Gene Set-Based Approach for Characterizing Bioactive Compounds in Terms of Biological Functional Groups. |
| title_full | Gene-Set Local Hierarchical Clustering (GSLHC)--A Gene Set-Based Approach for Characterizing Bioactive Compounds in Terms of Biological Functional Groups. |
| title_fullStr | Gene-Set Local Hierarchical Clustering (GSLHC)--A Gene Set-Based Approach for Characterizing Bioactive Compounds in Terms of Biological Functional Groups. |
| title_full_unstemmed | Gene-Set Local Hierarchical Clustering (GSLHC)--A Gene Set-Based Approach for Characterizing Bioactive Compounds in Terms of Biological Functional Groups. |
| title_short | Gene-Set Local Hierarchical Clustering (GSLHC)--A Gene Set-Based Approach for Characterizing Bioactive Compounds in Terms of Biological Functional Groups. |
| title_sort | gene set local hierarchical clustering gslhc a gene set based approach for characterizing bioactive compounds in terms of biological functional groups |
| url | http://europepmc.org/articles/PMC4652590?pdf=render |
| work_keys_str_mv | AT fenghsiangchung genesetlocalhierarchicalclusteringgslhcagenesetbasedapproachforcharacterizingbioactivecompoundsintermsofbiologicalfunctionalgroups AT zhenhuajin genesetlocalhierarchicalclusteringgslhcagenesetbasedapproachforcharacterizingbioactivecompoundsintermsofbiologicalfunctionalgroups AT tzutinghsu genesetlocalhierarchicalclusteringgslhcagenesetbasedapproachforcharacterizingbioactivecompoundsintermsofbiologicalfunctionalgroups AT chuehlinhsu genesetlocalhierarchicalclusteringgslhcagenesetbasedapproachforcharacterizingbioactivecompoundsintermsofbiologicalfunctionalgroups AT hsuehchuanliu genesetlocalhierarchicalclusteringgslhcagenesetbasedapproachforcharacterizingbioactivecompoundsintermsofbiologicalfunctionalgroups AT hoongchienlee genesetlocalhierarchicalclusteringgslhcagenesetbasedapproachforcharacterizingbioactivecompoundsintermsofbiologicalfunctionalgroups |