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DIVIS: Integrated and Customizable Pipeline for Cancer Genome Sequencing Analysis and Interpretation

Authors :
Xiaoyu He
Yu Zhang
Danyang Yuan
Xinyin Han
Jiayin He
Xiaohong Duan
Siyao Liu
Xintong Wang
Beifang Niu
Source :
Frontiers in Oncology, Vol 11 (2021)
Publication Year :
2021
Publisher :
Frontiers Media S.A., 2021.

Abstract

Next-generation sequencing (NGS) has drastically enhanced human cancer research, but diverse sequencing strategies, complicated open-source software, and the identification of massive numbers of mutations have limited the clinical application of NGS. Here, we first presented GPyFlow, a lightweight tool that flexibly customizes, executes, and shares workflows. We then introduced DIVIS, a customizable pipeline based on GPyFlow that integrates read preprocessing, alignment, variant detection, and annotation of whole-genome sequencing, whole-exome sequencing, and gene-panel sequencing. By default, DIVIS screens variants from multiple callers and generates a standard variant-detection format list containing caller evidence for each sample, which is compatible with advanced analyses. Lastly, DIVIS generates a statistical report, including command lines, parameters, quality-control indicators, and mutation summary. DIVIS substantially facilitates complex cancer genome sequencing analyses by means of a single powerful and easy-to-use command. The DIVIS code is freely available at https://github.com/niu-lab/DIVIS, and the docker image can be downloaded from https://hub.docker.com/repository/docker/sunshinerain/divis.

Details

Language :
English
ISSN :
2234943X
Volume :
11
Database :
Directory of Open Access Journals
Journal :
Frontiers in Oncology
Publication Type :
Academic Journal
Accession number :
edsdoj.b01c63cf9d604ba1b8cc01d80990d07f
Document Type :
article
Full Text :
https://doi.org/10.3389/fonc.2021.672597