The revolution in genomics has enabled large-scale population genetic investigations of a wide range of organisms, but there has been a relatively limited focus on improving analytical pipelines. To efficiently analyse large data sets, highly integrated and automated software pipelines, which are easy to use, efficient, reliable, reproducible and run in multiple computational environments, are required. A number of software workflows have been developed to handle and process such data sets for population genetic analyses, but effective, specialized pipelines for genetic and statistical analyses of nonmodel organisms are lacking. For most species, resources for variomes (sets of genetic variations found in populations of species) are not available, and/or genome assemblies are often incomplete and fragmented, complicating the selection of the most suitable reference genome when multiple assemblies are available. Additionally, the biological samples used often contain extraneous DNA from sources other than the species under investigation (e.g., microbial contamination), which needs to be removed prior to genetic analyses. For these reasons, we established a new pipeline, called Escalibur, which includes: functionalities, such as data trimming and mapping; selection of a suitable reference genome; removal of contaminating read data; recalibration of base calls; and variant-calling. Escalibur uses a proven gatk variant caller and workflow description language (WDL), and is, therefore, a highly efficient and scalable pipeline for the genome-wide identification of nucleotide variation in eukaryotes. This pipeline is available at https://gitlab.unimelb.edu.au/bioscience/escalibur (version 0.3-beta) and is essentially applicable to any prokaryote or eukaryote.
Keywords: bioinfomatics/workflows; molecular evolution; parasitology; population genetics.
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