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GeneDistiller—Distilling Candidate Genes from Linkage Intervals
BACKGROUND: Linkage studies often yield intervals containing several hundred positional candidate genes. Different manual or automatic approaches exist for the determination of the gene most likely to cause the disease. While the manual search is very flexible and takes advantage of the researchers&...
Autores principales: | , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2587712/ https://www.ncbi.nlm.nih.gov/pubmed/19057649 http://dx.doi.org/10.1371/journal.pone.0003874 |
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author | Seelow, Dominik Schwarz, Jana Marie Schuelke, Markus |
author_facet | Seelow, Dominik Schwarz, Jana Marie Schuelke, Markus |
author_sort | Seelow, Dominik |
collection | PubMed |
description | BACKGROUND: Linkage studies often yield intervals containing several hundred positional candidate genes. Different manual or automatic approaches exist for the determination of the gene most likely to cause the disease. While the manual search is very flexible and takes advantage of the researchers' background knowledge and intuition, it may be very cumbersome to collect and study the relevant data. Automatic solutions on the other hand usually focus on certain models, remain “black boxes” and do not offer the same degree of flexibility. METHODOLOGY: We have developed a web-based application that combines the advantages of both approaches. Information from various data sources such as gene-phenotype associations, gene expression patterns and protein-protein interactions was integrated into a central database. Researchers can select which information for the genes within a candidate interval or for single genes shall be displayed. Genes can also interactively be filtered, sorted and prioritised according to criteria derived from the background knowledge and preconception of the disease under scrutiny. CONCLUSIONS: GeneDistiller provides knowledge-driven, fully interactive and intuitive access to multiple data sources. It displays maximum relevant information, while saving the user from drowning in the flood of data. A typical query takes less than two seconds, thus allowing an interactive and explorative approach to the hunt for the candidate gene. ACCESS: GeneDistiller can be freely accessed at http://www.genedistiller.org |
format | Text |
id | pubmed-2587712 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-25877122008-12-05 GeneDistiller—Distilling Candidate Genes from Linkage Intervals Seelow, Dominik Schwarz, Jana Marie Schuelke, Markus PLoS One Research Article BACKGROUND: Linkage studies often yield intervals containing several hundred positional candidate genes. Different manual or automatic approaches exist for the determination of the gene most likely to cause the disease. While the manual search is very flexible and takes advantage of the researchers' background knowledge and intuition, it may be very cumbersome to collect and study the relevant data. Automatic solutions on the other hand usually focus on certain models, remain “black boxes” and do not offer the same degree of flexibility. METHODOLOGY: We have developed a web-based application that combines the advantages of both approaches. Information from various data sources such as gene-phenotype associations, gene expression patterns and protein-protein interactions was integrated into a central database. Researchers can select which information for the genes within a candidate interval or for single genes shall be displayed. Genes can also interactively be filtered, sorted and prioritised according to criteria derived from the background knowledge and preconception of the disease under scrutiny. CONCLUSIONS: GeneDistiller provides knowledge-driven, fully interactive and intuitive access to multiple data sources. It displays maximum relevant information, while saving the user from drowning in the flood of data. A typical query takes less than two seconds, thus allowing an interactive and explorative approach to the hunt for the candidate gene. ACCESS: GeneDistiller can be freely accessed at http://www.genedistiller.org Public Library of Science 2008-12-05 /pmc/articles/PMC2587712/ /pubmed/19057649 http://dx.doi.org/10.1371/journal.pone.0003874 Text en Seelow et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Seelow, Dominik Schwarz, Jana Marie Schuelke, Markus GeneDistiller—Distilling Candidate Genes from Linkage Intervals |
title | GeneDistiller—Distilling Candidate Genes from Linkage Intervals |
title_full | GeneDistiller—Distilling Candidate Genes from Linkage Intervals |
title_fullStr | GeneDistiller—Distilling Candidate Genes from Linkage Intervals |
title_full_unstemmed | GeneDistiller—Distilling Candidate Genes from Linkage Intervals |
title_short | GeneDistiller—Distilling Candidate Genes from Linkage Intervals |
title_sort | genedistiller—distilling candidate genes from linkage intervals |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2587712/ https://www.ncbi.nlm.nih.gov/pubmed/19057649 http://dx.doi.org/10.1371/journal.pone.0003874 |
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