Abstract:
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.
