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Gene Set Analysis: Challenges, Opportunities, and Future Research
Gene set analysis methods are widely used to provide insight into high-throughput gene expression data. There are many gene set analysis methods available. These methods rely on various assumptions and have different requirements, strengths and weaknesses. In this paper, we classify gene set analysi...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7339292/ https://www.ncbi.nlm.nih.gov/pubmed/32695141 http://dx.doi.org/10.3389/fgene.2020.00654 |
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author | Maleki, Farhad Ovens, Katie Hogan, Daniel J. Kusalik, Anthony J. |
author_facet | Maleki, Farhad Ovens, Katie Hogan, Daniel J. Kusalik, Anthony J. |
author_sort | Maleki, Farhad |
collection | PubMed |
description | Gene set analysis methods are widely used to provide insight into high-throughput gene expression data. There are many gene set analysis methods available. These methods rely on various assumptions and have different requirements, strengths and weaknesses. In this paper, we classify gene set analysis methods based on their components, describe the underlying requirements and assumptions for each class, and provide directions for future research in developing and evaluating gene set analysis methods. |
format | Online Article Text |
id | pubmed-7339292 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-73392922020-07-20 Gene Set Analysis: Challenges, Opportunities, and Future Research Maleki, Farhad Ovens, Katie Hogan, Daniel J. Kusalik, Anthony J. Front Genet Genetics Gene set analysis methods are widely used to provide insight into high-throughput gene expression data. There are many gene set analysis methods available. These methods rely on various assumptions and have different requirements, strengths and weaknesses. In this paper, we classify gene set analysis methods based on their components, describe the underlying requirements and assumptions for each class, and provide directions for future research in developing and evaluating gene set analysis methods. Frontiers Media S.A. 2020-06-30 /pmc/articles/PMC7339292/ /pubmed/32695141 http://dx.doi.org/10.3389/fgene.2020.00654 Text en Copyright © 2020 Maleki, Ovens, Hogan and Kusalik. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Maleki, Farhad Ovens, Katie Hogan, Daniel J. Kusalik, Anthony J. Gene Set Analysis: Challenges, Opportunities, and Future Research |
title | Gene Set Analysis: Challenges, Opportunities, and Future Research |
title_full | Gene Set Analysis: Challenges, Opportunities, and Future Research |
title_fullStr | Gene Set Analysis: Challenges, Opportunities, and Future Research |
title_full_unstemmed | Gene Set Analysis: Challenges, Opportunities, and Future Research |
title_short | Gene Set Analysis: Challenges, Opportunities, and Future Research |
title_sort | gene set analysis: challenges, opportunities, and future research |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7339292/ https://www.ncbi.nlm.nih.gov/pubmed/32695141 http://dx.doi.org/10.3389/fgene.2020.00654 |
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