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Causal analysis approaches in Ingenuity Pathway Analysis
Motivation: Prior biological knowledge greatly facilitates the meaningful interpretation of gene-expression data. Causal networks constructed from individual relationships curated from the literature are particularly suited for this task, since they create mechanistic hypotheses that explain the exp...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3928520/ https://www.ncbi.nlm.nih.gov/pubmed/24336805 http://dx.doi.org/10.1093/bioinformatics/btt703 |
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author | Krämer, Andreas Green, Jeff Pollard, Jack Tugendreich, Stuart |
author_facet | Krämer, Andreas Green, Jeff Pollard, Jack Tugendreich, Stuart |
author_sort | Krämer, Andreas |
collection | PubMed |
description | Motivation: Prior biological knowledge greatly facilitates the meaningful interpretation of gene-expression data. Causal networks constructed from individual relationships curated from the literature are particularly suited for this task, since they create mechanistic hypotheses that explain the expression changes observed in datasets. Results: We present and discuss a suite of algorithms and tools for inferring and scoring regulator networks upstream of gene-expression data based on a large-scale causal network derived from the Ingenuity Knowledge Base. We extend the method to predict downstream effects on biological functions and diseases and demonstrate the validity of our approach by applying it to example datasets. Availability: The causal analytics tools ‘Upstream Regulator Analysis', ‘Mechanistic Networks', ‘Causal Network Analysis' and ‘Downstream Effects Analysis' are implemented and available within Ingenuity Pathway Analysis (IPA, http://www.ingenuity.com). Supplementary information: Supplementary material is available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-3928520 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-39285202014-02-24 Causal analysis approaches in Ingenuity Pathway Analysis Krämer, Andreas Green, Jeff Pollard, Jack Tugendreich, Stuart Bioinformatics Original Papers Motivation: Prior biological knowledge greatly facilitates the meaningful interpretation of gene-expression data. Causal networks constructed from individual relationships curated from the literature are particularly suited for this task, since they create mechanistic hypotheses that explain the expression changes observed in datasets. Results: We present and discuss a suite of algorithms and tools for inferring and scoring regulator networks upstream of gene-expression data based on a large-scale causal network derived from the Ingenuity Knowledge Base. We extend the method to predict downstream effects on biological functions and diseases and demonstrate the validity of our approach by applying it to example datasets. Availability: The causal analytics tools ‘Upstream Regulator Analysis', ‘Mechanistic Networks', ‘Causal Network Analysis' and ‘Downstream Effects Analysis' are implemented and available within Ingenuity Pathway Analysis (IPA, http://www.ingenuity.com). Supplementary information: Supplementary material is available at Bioinformatics online. Oxford University Press 2014-02-15 2013-12-13 /pmc/articles/PMC3928520/ /pubmed/24336805 http://dx.doi.org/10.1093/bioinformatics/btt703 Text en © The Author 2013. Published by Oxford University Press. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Papers Krämer, Andreas Green, Jeff Pollard, Jack Tugendreich, Stuart Causal analysis approaches in Ingenuity Pathway Analysis |
title | Causal analysis approaches in Ingenuity Pathway Analysis |
title_full | Causal analysis approaches in Ingenuity Pathway Analysis |
title_fullStr | Causal analysis approaches in Ingenuity Pathway Analysis |
title_full_unstemmed | Causal analysis approaches in Ingenuity Pathway Analysis |
title_short | Causal analysis approaches in Ingenuity Pathway Analysis |
title_sort | causal analysis approaches in ingenuity pathway analysis |
topic | Original Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3928520/ https://www.ncbi.nlm.nih.gov/pubmed/24336805 http://dx.doi.org/10.1093/bioinformatics/btt703 |
work_keys_str_mv | AT kramerandreas causalanalysisapproachesiningenuitypathwayanalysis AT greenjeff causalanalysisapproachesiningenuitypathwayanalysis AT pollardjack causalanalysisapproachesiningenuitypathwayanalysis AT tugendreichstuart causalanalysisapproachesiningenuitypathwayanalysis |