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NGS-pipe: a flexible, easily extendable, and highly configurable framework for NGS analysis
JournalArticle (Originalarbeit in einer wissenschaftlichen Zeitschrift)
 
ID 3932028
Author(s) Singer, Jochen; Ruscheweyh, Hans-Joachim; Hofmann, Ariane L.; Thurnherr, Thomas; Singer, Franziska; Toussaint, Nora C.; Ng, Charlotte K. Y.; Piscuoglio, Salvatore; Beisel, Christian; Christofori, Gerhard; Dummer, Reinhard; Hall, Michael N.; Krek, Wilhelm; Levesque, Mitchell; Manz, Markus G.; Moch, Holger; Papassotiropoulos, Andreas; Stekhoven, Daniel J.; Wild, Peter; Wüst, Thomas; Rinn, Bernd; Beerenwinkel, Niko
Author(s) at UniBasel Hall, Michael N.
Christofori, Gerhard M.
Papassotiropoulos, Andreas
Piscuoglio, Salvatore
Year 2018
Title NGS-pipe: a flexible, easily extendable, and highly configurable framework for NGS analysis
Journal Bioinformatics
Volume 34
Number 1
Pages / Article-Number 107-108
Mesh terms Gene Expression Profiling, standards; Genomics, methods; High-Throughput Nucleotide Sequencing, standards; Humans; Neoplasms, genetics; Reproducibility of Results; Sequence Analysis, DNA, standards; Sequence Analysis, RNA, standards; Software
Abstract Next-generation sequencing is now an established method in genomics, and massive amounts of sequencing data are being generated on a regular basis. Analysis of the sequencing data is typically performed by lab-specific in-house solutions, but the agreement of results from different facilities is often small. General standards for quality control, reproducibility, and documentation are missing.; We developed NGS-pipe, a flexible, transparent, and easy-to-use framework for the design of pipelines to analyze whole-exome, whole-genome, and transcriptome sequencing data. NGS-pipe facilitates the harmonization of genomic data analysis by supporting quality control, documentation, reproducibility, parallelization, and easy adaptation to other NGS experiments. https://github.com/cbg-ethz/NGS-pipe niko.beerenwinkel@bsse.ethz.ch
Publisher Oxford University Press
ISSN/ISBN 1367-4803 ; 1367-4811
edoc-URL http://edoc.unibas.ch/56308/
Full Text on edoc Available
Digital Object Identifier DOI 10.1093/bioinformatics/btx540
PubMed ID http://www.ncbi.nlm.nih.gov/pubmed/28968639
ISI-Number 000419591100015
Document type (ISI) Journal Article
 
   

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