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...
| Main Authors: | , , |
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| Format: | Journal Article |
| Language: | Inglés |
| Published: |
Oxford University Press
2016
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/73215 |
| _version_ | 1855542023239499776 |
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| author | Pulido Tamayo, Sergio Duitama, Jorge Marchal, Kathleen |
| author_browse | Duitama, Jorge Marchal, Kathleen Pulido Tamayo, Sergio |
| author_facet | Pulido Tamayo, Sergio Duitama, Jorge Marchal, Kathleen |
| author_sort | Pulido Tamayo, Sergio |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| 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 | Journal Article |
| id | CGSpace73215 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2016 |
| publishDateRange | 2016 |
| publishDateSort | 2016 |
| publisher | Oxford University Press |
| publisherStr | Oxford University Press |
| record_format | dspace |
| spelling | CGSpace732152025-03-13T09:45:48Z EXPLoRA-web: linkage analysis of quantitative trait loci using bulk segregant analysis Pulido Tamayo, Sergio Duitama, Jorge Marchal, Kathleen quantitative trait loci genetic markers segregation computer applications data analysis bioinformatics statistical methods database phenotypes loci de rasgos cuantitativos marcadores genéticos segregación aplicaciones del ordenador análisis de datos bioinformática métodos estadísticos fenotipos 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/. 2016-07-08 2016-04-26T13:33:20Z 2016-04-26T13:33:20Z Journal Article https://hdl.handle.net/10568/73215 en Open Access Oxford University Press Pulido Tamayo, Sergio; Duitama, Jorge; Marchal, Kathleen. 2016. EXPLoRA-web: linkage analysis of quantitative trait loci using bulk segregant analysis . Nucleic Acids Research 44(w1):w142-w146. |
| spellingShingle | quantitative trait loci genetic markers segregation computer applications data analysis bioinformatics statistical methods database phenotypes loci de rasgos cuantitativos marcadores genéticos segregación aplicaciones del ordenador análisis de datos bioinformática métodos estadísticos fenotipos 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 | quantitative trait loci genetic markers segregation computer applications data analysis bioinformatics statistical methods database phenotypes loci de rasgos cuantitativos marcadores genéticos segregación aplicaciones del ordenador análisis de datos bioinformática métodos estadísticos fenotipos |
| url | https://hdl.handle.net/10568/73215 |
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