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Data on chemical-gene interactions and biological categories enriched with genes sensitive to chemical exposures
A dataset of chemical-gene interactions was created by extracting data from the Comparative Toxicogenomics Database (CTD) with the following filtering criteria: data was extracted only from experiments that used human, rat, or mouse cells/tissues and used high-throughput approaches for gene expressi...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7578666/ https://www.ncbi.nlm.nih.gov/pubmed/33102660 http://dx.doi.org/10.1016/j.dib.2020.106398 |
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author | Suvorov, Alexander Salemme, Victoria McGaunn, Joseph Poluyanoff, Anthony Amir, Saira |
author_facet | Suvorov, Alexander Salemme, Victoria McGaunn, Joseph Poluyanoff, Anthony Amir, Saira |
author_sort | Suvorov, Alexander |
collection | PubMed |
description | A dataset of chemical-gene interactions was created by extracting data from the Comparative Toxicogenomics Database (CTD) with the following filtering criteria: data was extracted only from experiments that used human, rat, or mouse cells/tissues and used high-throughput approaches for gene expression analysis. Genes not present in genomes of all three species were filtered out. The resulting dataset included 591,084 chemical-gene interaction. All chemical compounds in the database were annotated for their major uses. For every gene in the database number of chemical-gene interactions was calculated and used as a metric of gene sensitivity to a variety of chemical exposures. The lists of genes with corresponding numbers of chemical-gene interactions were used in gene-set enrichment analysis (GSEA) to identify potential sensitivity to chemical exposures of molecular pathways in Hallmark, KEGG and Reactome collections. Thus, data presented here represent unbiased and searchable datasets of sensitivity of genes and molecular pathways to a broad range of chemical exposures. As such the data can be used for a diverse range of toxicological and regulatory applications. Approach for the identification of molecular mechanisms sensitive to chemical exposures may inform regulatory toxicology about best toxicity testing strategies. Analysis of sensitivity of genes and molecular pathways to chemical exposures based on these datasets was published in Chemosphere (Suvorov et al., 2021) [1]. |
format | Online Article Text |
id | pubmed-7578666 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-75786662020-10-23 Data on chemical-gene interactions and biological categories enriched with genes sensitive to chemical exposures Suvorov, Alexander Salemme, Victoria McGaunn, Joseph Poluyanoff, Anthony Amir, Saira Data Brief Data Article A dataset of chemical-gene interactions was created by extracting data from the Comparative Toxicogenomics Database (CTD) with the following filtering criteria: data was extracted only from experiments that used human, rat, or mouse cells/tissues and used high-throughput approaches for gene expression analysis. Genes not present in genomes of all three species were filtered out. The resulting dataset included 591,084 chemical-gene interaction. All chemical compounds in the database were annotated for their major uses. For every gene in the database number of chemical-gene interactions was calculated and used as a metric of gene sensitivity to a variety of chemical exposures. The lists of genes with corresponding numbers of chemical-gene interactions were used in gene-set enrichment analysis (GSEA) to identify potential sensitivity to chemical exposures of molecular pathways in Hallmark, KEGG and Reactome collections. Thus, data presented here represent unbiased and searchable datasets of sensitivity of genes and molecular pathways to a broad range of chemical exposures. As such the data can be used for a diverse range of toxicological and regulatory applications. Approach for the identification of molecular mechanisms sensitive to chemical exposures may inform regulatory toxicology about best toxicity testing strategies. Analysis of sensitivity of genes and molecular pathways to chemical exposures based on these datasets was published in Chemosphere (Suvorov et al., 2021) [1]. Elsevier 2020-10-09 /pmc/articles/PMC7578666/ /pubmed/33102660 http://dx.doi.org/10.1016/j.dib.2020.106398 Text en © 2020 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Suvorov, Alexander Salemme, Victoria McGaunn, Joseph Poluyanoff, Anthony Amir, Saira Data on chemical-gene interactions and biological categories enriched with genes sensitive to chemical exposures |
title | Data on chemical-gene interactions and biological categories enriched with genes sensitive to chemical exposures |
title_full | Data on chemical-gene interactions and biological categories enriched with genes sensitive to chemical exposures |
title_fullStr | Data on chemical-gene interactions and biological categories enriched with genes sensitive to chemical exposures |
title_full_unstemmed | Data on chemical-gene interactions and biological categories enriched with genes sensitive to chemical exposures |
title_short | Data on chemical-gene interactions and biological categories enriched with genes sensitive to chemical exposures |
title_sort | data on chemical-gene interactions and biological categories enriched with genes sensitive to chemical exposures |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7578666/ https://www.ncbi.nlm.nih.gov/pubmed/33102660 http://dx.doi.org/10.1016/j.dib.2020.106398 |
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