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NGS-pipe: a flexible, easily extendable, and highly configurable framework for NGS analysis


Abstract

Motivation: 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.
Results: 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.

Abstract

Motivation: 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.
Results: 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.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Clinic for Hematology
04 Faculty of Medicine > University Hospital Zurich > Institute of Pathology and Molecular Pathology
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:28 August 2017
Deposited On:16 Oct 2017 14:03
Last Modified:21 Nov 2017 19:42
Publisher:Oxford University Press
ISSN:1367-4803
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1093/bioinformatics/btx540
PubMed ID:28968639

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