Praveen Krishna Chitneedi, Frieder Hadlich, Gabriel C M Moreira, Jose Espinosa-Carrasco, Changxi Li, Graham Plastow, Daniel Fischer, Carole Charlier, Dominique Rocha, Amanda J Chamberlain, Christa Kuehn
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Abstract
Bioinformatic pipelines are becoming increasingly complex with the ever-accumulating amount of Next-generation sequencing (NGS) data. Their orchestration is difficult with a simple Bash script, but bioinformatics workflow managers such as Nextflow provide a framework to overcome respective problems. This study used Nextflow to develop a bioinformatic pipeline for detecting expression quantitative trait loci (eQTL) using a DSL2 Nextflow modular syntax, to enable sharing the huge demand for computing power as well as data access limitation across different partners often associated with eQTL studies. Based on the results from a test run with pilot data by measuring the required runtime and computational resources, the new pipeline should be suitable for eQTL studies in large scale analyses.
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