# eQTL-Detect: nextflow-based pipeline for eQTL detection in modular format with sharable and parallelizable scripts

## TL;DR

This paper introduces eQTL-Detect, a Nextflow-based pipeline for efficiently detecting eQTLs in large-scale studies.

## Contribution

The novelty lies in using Nextflow's DSL2 to create a modular, shareable, and parallelizable eQTL detection pipeline.

## Key findings

- The pipeline was tested with pilot data and showed suitable performance for large-scale eQTL studies.
- It addresses computational and data-sharing challenges common in eQTL research.
- Modular design allows for easy adaptation and collaboration across research partners.

## 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.

Graphical Abstract