Evidence map›Paper›PMID 30500888›Full record

ArticleBioinformatics (Oxford, England)2019

Detection of rare disease variants in extended pedigrees using RVS.

Thomas Sherman, Jack Fu, Robert B Scharpf, Alexandre Bureau, Ingo Ruczinski

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

5 authors.

Thomas ShermanDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health.
Jack FuDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health.
Robert B ScharpfDepartment of Oncology, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Alexandre BureauDépartement de Médecine Sociale et Préventive, Université Laval, Québec, QC, Canada.
Ingo RuczinskiDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health.

Funding

Methods, software, and analyses of genomic data in multiplex oral cleft familiesR03DE025279 · NIDCR · JOHNS HOPKINS UNIVERSITY · PI RUCZINSKI, INGO · 2015 to 2016
$486k
NIDCR NIH HHS R03 DE025279
6 · The paper itself

Abstract

summaryFamily-based sequencing studies enable researchers to identify highly penetrant genetic variants too rare to be tested in conventional case-control studies, by studying co-segregation of variant and disease phenotypes. When multiple affected subjects in a family are sequenced, the probability that a variant or a set of variants is shared identical-by-descent by some or all affected relatives provides evidence against the null hypothesis of complete absence of linkage and association. The Rare Variant Sharing software package RVS implements a suite of tools to assess association and linkage between rare genetic variants and a dichotomous disease indicator in family pedigrees. AVAILABILITY AND IMPLEMENTATION: RVS is available as open source software from the Bioconductor webpage at https://bioconductor.org/packages/release/bioc/html/RVS.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

Rare DiseasesSoftwareGenetic LinkageHumansPedigreePhenotype

Identifiers

PMID30500888
PMCPMC6612888

What OpenQuestion holds

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Registered trials

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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.