Evidence map›Paper›PMID 34168993›Full record

ArticleFrontiers in oncology2021

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

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

Abstract read
In one paragraph

Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Xiaoyu HeComputer Network Information Center, Chinese Academy of Sciences, Beijing, China.
Yu ZhangComputer Network Information Center, Chinese Academy of Sciences, Beijing, China.
Danyang YuanComputer Network Information Center, Chinese Academy of Sciences, Beijing, China.
Xinyin HanComputer Network Information Center, Chinese Academy of Sciences, Beijing, China.
Jiayin HeComputer Network Information Center, Chinese Academy of Sciences, Beijing, China.
Xiaohong DuanChosenMed Technology (Beijing) Co., Ltd., Beijing, China.
Siyao LiuChosenMed Technology (Beijing) Co., Ltd., Beijing, China.
Xintong WangChosenMed Technology (Beijing) Co., Ltd., Beijing, China.
Beifang NiuComputer Network Information Center, Chinese Academy of Sciences, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

cancercustomizationnext-generation sequencingvariants detectionworkflow

Identifiers

PMID34168993
PMCPMC8217664

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.