In:
Bioinformatics, Oxford University Press (OUP), Vol. 35, No. 22 ( 2019-11-01), p. 4770-4772
Kurzfassung:
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.
Materialart:
Online-Ressource
ISSN:
1367-4803
,
1367-4811
DOI:
10.1093/bioinformatics/btz461
Sprache:
Englisch
Verlag:
Oxford University Press (OUP)
Publikationsdatum:
2019
ZDB Id:
1468345-3
SSG:
12
