AUTHOR=He Xiaoyu , Zhang Yu , Yuan Danyang , Han Xinyin , He Jiayin , Duan Xiaohong , Liu Siyao , Wang Xintong , Niu Beifang 

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

JOURNAL=Frontiers in Oncology

VOLUME=11

YEAR=2021

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2021.672597

DOI=10.3389/fonc.2021.672597

ISSN=2234-943X

ABSTRACT=<p>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 <uri xlink:href="https://github.com/niu-lab/DIVIS" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/niu-lab/DIVIS</uri>, and the docker image can be downloaded from <uri xlink:href="https://hub.docker.com/repository/docker/sunshinerain/divis" xmlns:xlink="http://www.w3.org/1999/xlink">https://hub.docker.com/repository/docker/sunshinerain/divis</uri>.</p>