Cargando…
EXPLoRA-web: linkage analysis of quantitative trait loci using bulk segregant analysis
Identification of genomic regions associated with a phenotype of interest is a fundamental step toward solving questions in biology and improving industrial research. Bulk segregant analysis (BSA) combined with high-throughput sequencing is a technique to efficiently identify these genomic regions a...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4987886/ https://www.ncbi.nlm.nih.gov/pubmed/27105844 http://dx.doi.org/10.1093/nar/gkw298 |
_version_ | 1782448362207838208 |
---|---|
author | Pulido-Tamayo, Sergio Duitama, Jorge Marchal, Kathleen |
author_facet | Pulido-Tamayo, Sergio Duitama, Jorge Marchal, Kathleen |
author_sort | Pulido-Tamayo, Sergio |
collection | PubMed |
description | Identification of genomic regions associated with a phenotype of interest is a fundamental step toward solving questions in biology and improving industrial research. Bulk segregant analysis (BSA) combined with high-throughput sequencing is a technique to efficiently identify these genomic regions associated with a trait of interest. However, distinguishing true from spuriously linked genomic regions and accurately delineating the genomic positions of these truly linked regions requires the use of complex statistical models currently implemented in software tools that are generally difficult to operate for non-expert users. To facilitate the exploration and analysis of data generated by bulked segregant analysis, we present EXPLoRA-web, a web service wrapped around our previously published algorithm EXPLoRA, which exploits linkage disequilibrium to increase the power and accuracy of quantitative trait loci identification in BSA analysis. EXPLoRA-web provides a user friendly interface that enables easy data upload and parallel processing of different parameter configurations. Results are provided graphically and as BED file and/or text file and the input is expected in widely used formats, enabling straightforward BSA data analysis. The web server is available at http://bioinformatics.intec.ugent.be/explora-web/. |
format | Online Article Text |
id | pubmed-4987886 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-49878862016-08-22 EXPLoRA-web: linkage analysis of quantitative trait loci using bulk segregant analysis Pulido-Tamayo, Sergio Duitama, Jorge Marchal, Kathleen Nucleic Acids Res Web Server issue Identification of genomic regions associated with a phenotype of interest is a fundamental step toward solving questions in biology and improving industrial research. Bulk segregant analysis (BSA) combined with high-throughput sequencing is a technique to efficiently identify these genomic regions associated with a trait of interest. However, distinguishing true from spuriously linked genomic regions and accurately delineating the genomic positions of these truly linked regions requires the use of complex statistical models currently implemented in software tools that are generally difficult to operate for non-expert users. To facilitate the exploration and analysis of data generated by bulked segregant analysis, we present EXPLoRA-web, a web service wrapped around our previously published algorithm EXPLoRA, which exploits linkage disequilibrium to increase the power and accuracy of quantitative trait loci identification in BSA analysis. EXPLoRA-web provides a user friendly interface that enables easy data upload and parallel processing of different parameter configurations. Results are provided graphically and as BED file and/or text file and the input is expected in widely used formats, enabling straightforward BSA data analysis. The web server is available at http://bioinformatics.intec.ugent.be/explora-web/. Oxford University Press 2016-07-08 2016-04-21 /pmc/articles/PMC4987886/ /pubmed/27105844 http://dx.doi.org/10.1093/nar/gkw298 Text en © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Web Server issue Pulido-Tamayo, Sergio Duitama, Jorge Marchal, Kathleen EXPLoRA-web: linkage analysis of quantitative trait loci using bulk segregant analysis |
title | EXPLoRA-web: linkage analysis of quantitative trait loci using bulk segregant analysis |
title_full | EXPLoRA-web: linkage analysis of quantitative trait loci using bulk segregant analysis |
title_fullStr | EXPLoRA-web: linkage analysis of quantitative trait loci using bulk segregant analysis |
title_full_unstemmed | EXPLoRA-web: linkage analysis of quantitative trait loci using bulk segregant analysis |
title_short | EXPLoRA-web: linkage analysis of quantitative trait loci using bulk segregant analysis |
title_sort | explora-web: linkage analysis of quantitative trait loci using bulk segregant analysis |
topic | Web Server issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4987886/ https://www.ncbi.nlm.nih.gov/pubmed/27105844 http://dx.doi.org/10.1093/nar/gkw298 |
work_keys_str_mv | AT pulidotamayosergio exploraweblinkageanalysisofquantitativetraitlociusingbulksegregantanalysis AT duitamajorge exploraweblinkageanalysisofquantitativetraitlociusingbulksegregantanalysis AT marchalkathleen exploraweblinkageanalysisofquantitativetraitlociusingbulksegregantanalysis |