Evidence map›Paper›PMID 25587064›Full record

ArticleJournal of medical genetics2015

SeqHBase: a big data toolset for family based sequencing data analysis.

Min He, Thomas N Person, Scott J Hebbring, Ethan Heinzen, Zhan Ye, Steven J Schrodi, Elizabeth W McPherson, Simon M Lin, Peggy L Peissig, Murray H Brilliant and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of medical genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Big Data Analytics for Genomic Medicine.International journal of molecular sciences · 2017
    Review
  5. KBG syndrome involving a single-nucleotide duplication inCold Spring Harbor molecular case studies · 2016
    Article
  6. Single-cell Transcriptome Study as Big Data.Genomics, proteomics & bioinformatics · 2016
    Review
  7. Article
  8. Review
  9. 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

14 authors.

Min HeCenter for Human Genetics, Marshfield Clinic Research Foundation, Marshfield, Wisconsin, USA Biomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, Wisconsin, USA Department of Computation and Informatics in Biology and Medicine, University of Wisconsin-Madison, Madison, Wisconsin, USA.
Thomas N PersonCenter for Human Genetics, Marshfield Clinic Research Foundation, Marshfield, Wisconsin, USA.
Scott J HebbringCenter for Human Genetics, Marshfield Clinic Research Foundation, Marshfield, Wisconsin, USA Department of Computation and Informatics in Biology and Medicine, University of Wisconsin-Madison, Madison, Wisconsin, USA.
Ethan HeinzenCollege of Science and Engineering, University of Minnesota-Twin Cities, Minnesota, Minnesota, USA.
Zhan YeBiomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, Wisconsin, USA.
Steven J SchrodiCenter for Human Genetics, Marshfield Clinic Research Foundation, Marshfield, Wisconsin, USA Department of Computation and Informatics in Biology and Medicine, University of Wisconsin-Madison, Madison, Wisconsin, USA.
Elizabeth W McPhersonDepartment of Medical Genetics Services, Marshfield Clinic, Marshfield, Wisconsin, USA.
Simon M LinThe Research Institute at Nationwide Children's Hospital, Columbus, Ohio, USA.
Peggy L PeissigBiomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, Wisconsin, USA.
Murray H BrilliantCenter for Human Genetics, Marshfield Clinic Research Foundation, Marshfield, Wisconsin, USA Department of Computation and Informatics in Biology and Medicine, University of Wisconsin-Madison, Madison, Wisconsin, USA.
Jason O'RaweCold Spring Harbor Laboratory, Stanley Institute for Cognitive Genomics, Cold Spring Harbor, New York, USA.
Reid J RobisonUtah Foundation for Biomedical Research, Provo, Utah, USA.
Gholson J LyonCold Spring Harbor Laboratory, Stanley Institute for Cognitive Genomics, Cold Spring Harbor, New York, USA Utah Foundation for Biomedical Research, Provo, Utah, USA.
Kai WangUtah Foundation for Biomedical Research, Provo, Utah, USA Zilkha Neurogenetic Institute, University of Southern California, Los Angeles, California, USA Department of Psychiatry, University of Southern California, Los Angeles, California, USA.

Funding

Institutional Clinical and Translational Science AwardUL1TR000427 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI DREZNER, MARC KENNETH · 2012 to 2016
$32.2M
Integrated variation detection annotation and analysis for high-throughout sequeR01HG006465 · NHGRI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI WANG, KAI · 2012 to 2016
$1.8M
NCATS NIH HHS UL1 TR000427NCATS NIH HHS UL1TR000427NHGRI NIH HHS HG006465NHGRI NIH HHS R01 HG006465
6 · The paper itself

Abstract

backgroundWhole-genome sequencing (WGS) and whole-exome sequencing (WES) technologies are increasingly used to identify disease-contributing mutations in human genomic studies. It can be a significant challenge to process such data, especially when a large family or cohort is sequenced. Our objective was to develop a big data toolset to efficiently manipulate genome-wide variants, functional annotations and coverage, together with conducting family based sequencing data analysis.

methodsHadoop is a framework for reliable, scalable, distributed processing of large data sets using MapReduce programming models. Based on Hadoop and HBase, we developed SeqHBase, a big data-based toolset for analysing family based sequencing data to detect de novo, inherited homozygous, or compound heterozygous mutations that may contribute to disease manifestations. SeqHBase takes as input BAM files (for coverage at every site), variant call format (VCF) files (for variant calls) and functional annotations (for variant prioritisation).

resultsWe applied SeqHBase to a 5-member nuclear family and a 10-member 3-generation family with WGS data, as well as a 4-member nuclear family with WES data. Analysis times were almost linearly scalable with number of data nodes. With 20 data nodes, SeqHBase took about 5 secs to analyse WES familial data and approximately 1 min to analyse WGS familial data.

conclusionsThese results demonstrate SeqHBase's high efficiency and scalability, which is necessary as WGS and WES are rapidly becoming standard methods to study the genetics of familial disorders.

Indexed as

SoftwareDatasets as TopicExomeGenome, HumanGenomicsHumansMutationSequence Analysis, DNAbig datade novo mutationsinherited homozygous or compound heterozygous mutationswhole-exome sequencingwhole-genome sequencing

Identifiers

PMID25587064
PMCPMC4382803

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.