Nanopype: a modular and scalable nanopore data processing pipeline

Bioinformatics. 2019 Nov 1;35(22):4770-4772. doi: 10.1093/bioinformatics/btz461.

Abstract

Summary: Long-read third-generation nanopore sequencing enables researchers to now address a range of questions that are difficult to tackle with short read approaches. The rapidly expanding user base and continuously increasing throughput have sparked the development of a growing number of specialized analysis tools. However, streamlined processing of nanopore datasets using reproducible and transparent workflows is still lacking. Here we present Nanopype, a nanopore data processing pipeline that integrates a diverse set of established bioinformatics software while maintaining consistent and standardized output formats. Seamless integration into compute cluster environments makes the framework suitable for high-throughput applications. As a result, Nanopype facilitates comparability of nanopore data analysis workflows and thereby should enhance the reproducibility of biological insights.

Availability and implementation: https://github.com/giesselmann/nanopype, https://nanopype.readthedocs.io.

Supplementary information: Supplementary data are available at Bioinformatics online.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • High-Throughput Nucleotide Sequencing
  • Nanopores*
  • Reproducibility of Results
  • Software
  • Workflow