Evidence map›Paper›PMID 29717215›Full record

ArticleScientific reports2018

DNAp: A Pipeline for DNA-seq Data Analysis.

Jason L Causey, Cody Ashby, Karl Walker, Zhiping Paul Wang, Mary Yang, Yuanfang Guan, Jason H Moore, Xiuzhen Huang

Abstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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  11. Semantic workflows for benchmark challenges: Enhancing comparability, reusability and reproducibility.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2019
    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

8 authors.

Jason L CauseyDepartment of Computer Science, Arkansas State University, Jonesboro, Arkansas, 72467, United States of America.
Cody AshbyDepartment of Biomedical Informatics and the Myeloma Institute, University of Arkansas for Medical Sciences, Little Rock, Arkansas, 72205, United States of America.
Karl WalkerDepartment of Mathematics and Computer Science, University of Arkansas at Pine Bluff, Pine Bluff, Arkansas, 55455, United States of America.
Zhiping Paul WangInstitute for Biomedical Informatics, University of Pennsylvania, Philadelphia, Pennsylvania, 19104, United States of America.
Mary YangDepartment of Information Science, University of Arkansas at Little Rock, Little Rock, Arkansas, 72204, United States of America.
Yuanfang GuanDepartment of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, Michigan, 48109, United States of America.
Jason H MooreInstitute for Biomedical Informatics, University of Pennsylvania, Philadelphia, Pennsylvania, 19104, United States of America.
Xiuzhen HuangDepartment of Computer Science, Arkansas State University, Jonesboro, Arkansas, 72467, United States of America. xhuang@astate.edu.ORCID 0000-0003-0498-3131

Funding

Understanding Hesitant AdoptersP20GM103429 · NIGMS · UNIV OF ARKANSAS FOR MED SCIS · PI Lawrence E Cornett, JERRY WARE · 2012 to 2026
$60.9M
Translational Research Support CoreP30ES013508 · NIEHS · UNIVERSITY OF PENNSYLVANIA · PI Rebecca A Simmons · 2006 to 2026
$35.3M
Biomedical Computing and Informatics Strategies for Precision MedicineR01LM012601 · NLM · UNIVERSITY OF PENNSYLVANIA · PI HUANG, XIUZHEN, MOORE, JASON H. · 2017 to 2020
$1.8M
Developing integrative approaches for identifying disease-causing genes and dysfunctional networksR15GM114739 · NIGMS · UNIVERSITY OF ARKANSAS AT LITTLE ROCK · PI YANG, MARY · 2015 to 2015
$374k
FDA HHS HHSF223201510172CNIEHS NIH HHS P30 ES013508NIGMS NIH HHS P20 GM103429NIGMS NIH HHS R15 GM114739NLM NIH HHS R01 LM012601
6 · The paper itself

Abstract

Next-generation sequencing is empowering genetic disease research. However, it also brings significant challenges for efficient and effective sequencing data analysis. We built a pipeline, called DNAp, for analyzing whole exome sequencing (WES) and whole genome sequencing (WGS) data, to detect mutations from disease samples. The pipeline is containerized, convenient to use and can run under any system, since it is a fully automatic process in Docker container form. It is also open, and can be easily customized with user intervention points, such as for updating reference files and different software or versions. The pipeline has been tested with both human and mouse sequencing datasets, and it has generated mutations results, comparable to published results from these datasets, and reproducible across heterogeneous hardware platforms. The pipeline DNAp, funded by the US Food and Drug Administration (FDA), was developed for analyzing DNA sequencing data of FDA. Here we make DNAp an open source, with the software and documentation available to the public at http://bioinformatics.astate.edu/dna-pipeline/ .

Indexed as

GenomeSoftwareAnimalsComputational BiologyDatasets as TopicExome SequencingHigh-Throughput Nucleotide SequencingHumansInformation DisseminationInternetMiceMutationSequence Analysis, DNA

Identifiers

PMID29717215
PMCPMC5931599

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.