Frontiers in GeneticsBioinformaticsPeer-reviewed journal article
Pipeliner: A Nextflow-based framework for the definition of sequencing data processing pipelines
Anthony N. FedericoiD, Tanya T. KaragiannisiD, Kritika Karri, Dileep KishoreiD, Yusuke KogaiD, Joshua David CampbelliD, Stefano MontiiD
- Citations
- 18
- FWCI
- 3.55
- Field percentile
- top 6%
Abstract
The advent of high-throughput sequencing technologies has led to the need for flexible and user-friendly data pre-processing platforms. The Pipeliner framework provides an out-of-the-box solution for processing various types of sequencing data. It combines the Nextflow scripting language and Anaconda package manager to generate modular computational workflows. We have used Pipeliner to create several pipelines for sequencing data processing including bulk RNA-seq, single-cell RNA-seq (scRNA-seq), as well as Digital Gene Expression (DGE) data. This report highlights the design methodology behind Pipeliner which enables the development of highly flexible and reproducible pipelines that are easy to extend and maintain on multiple computing environments. We also provide a quick start user guide demonstrating how to setup and execute available pipelines with toy datasets.
- assay: bulk RNA-seq
- assay: scRNA-seq
- assay: DNA methylation
- research focus: software / tool
- research focus: benchmarking
- approach: experimental assay
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