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eQTL Viewer: visualizing how sequence variation affects genome-wide transcription
BACKGROUND: Expression Quantitative Trait Locus (eQTL) mapping methods have been used to identify the genetic basis of gene expression variations. To map eQTL, thousands of expression profiles are related with sequence polymorphisms across the genome through their correlated variations. These eQTL d...
Autores principales: | , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2007
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1780060/ https://www.ncbi.nlm.nih.gov/pubmed/17212828 http://dx.doi.org/10.1186/1471-2105-8-7 |
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author | Zou, Wei Aylor, David L Zeng, Zhao-Bang |
author_facet | Zou, Wei Aylor, David L Zeng, Zhao-Bang |
author_sort | Zou, Wei |
collection | PubMed |
description | BACKGROUND: Expression Quantitative Trait Locus (eQTL) mapping methods have been used to identify the genetic basis of gene expression variations. To map eQTL, thousands of expression profiles are related with sequence polymorphisms across the genome through their correlated variations. These eQTL distribute in many chromosomal regions, each of which can include many genes. The large number of mapping results produced makes it difficult to consider simultaneously the relationships between multiple genomic regions and multiple expressional profiles. There is a need for informative bioinformatics tools to assist the visualization and interpretation of these mapping results. RESULTS: We have developed a web-based tool, called eQTL Viewer, to visualize the relationships between the expression trait genes and the candidate genes in the eQTL regions using Scalable Vector Graphics. The plot generated by eQTL Viewer has the capacity to display mapping results with high resolutions at a variety of scales, and superimpose biological annotations onto the mapping results dynamically. CONCLUSION: Our tool provides an efficient and intuitive way for biologists to explore transcriptional regulation patterns, and to generate hypotheses on the genetic basis of transcriptional regulations. |
format | Text |
id | pubmed-1780060 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-17800602007-01-23 eQTL Viewer: visualizing how sequence variation affects genome-wide transcription Zou, Wei Aylor, David L Zeng, Zhao-Bang BMC Bioinformatics Software BACKGROUND: Expression Quantitative Trait Locus (eQTL) mapping methods have been used to identify the genetic basis of gene expression variations. To map eQTL, thousands of expression profiles are related with sequence polymorphisms across the genome through their correlated variations. These eQTL distribute in many chromosomal regions, each of which can include many genes. The large number of mapping results produced makes it difficult to consider simultaneously the relationships between multiple genomic regions and multiple expressional profiles. There is a need for informative bioinformatics tools to assist the visualization and interpretation of these mapping results. RESULTS: We have developed a web-based tool, called eQTL Viewer, to visualize the relationships between the expression trait genes and the candidate genes in the eQTL regions using Scalable Vector Graphics. The plot generated by eQTL Viewer has the capacity to display mapping results with high resolutions at a variety of scales, and superimpose biological annotations onto the mapping results dynamically. CONCLUSION: Our tool provides an efficient and intuitive way for biologists to explore transcriptional regulation patterns, and to generate hypotheses on the genetic basis of transcriptional regulations. BioMed Central 2007-01-09 /pmc/articles/PMC1780060/ /pubmed/17212828 http://dx.doi.org/10.1186/1471-2105-8-7 Text en Copyright © 2007 Zou et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Software Zou, Wei Aylor, David L Zeng, Zhao-Bang eQTL Viewer: visualizing how sequence variation affects genome-wide transcription |
title | eQTL Viewer: visualizing how sequence variation affects genome-wide transcription |
title_full | eQTL Viewer: visualizing how sequence variation affects genome-wide transcription |
title_fullStr | eQTL Viewer: visualizing how sequence variation affects genome-wide transcription |
title_full_unstemmed | eQTL Viewer: visualizing how sequence variation affects genome-wide transcription |
title_short | eQTL Viewer: visualizing how sequence variation affects genome-wide transcription |
title_sort | eqtl viewer: visualizing how sequence variation affects genome-wide transcription |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1780060/ https://www.ncbi.nlm.nih.gov/pubmed/17212828 http://dx.doi.org/10.1186/1471-2105-8-7 |
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