EXPLoRA-web: linkage analysis of quantitative trait loci using bulk segregant analysis
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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.
Permanent link to cite or share this item: https://hdl.handle.net/10568/73215
External link to download this item: http://bioinformatics.intec.ugent.be/explora-web/
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/.
CGIAR Author ORCID iDs
Sergio Pulido Tamayohttps://orcid.org/0000-0002-3567-7009
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