Evidence map›Paper›PMID 29937093›Full record

ArticleAmerican journal of human genetics2018

Inferring Identical-by-Descent Sharing of Sample Ancestors Promotes High-Resolution Relative Detection.

Monica D Ramstetter, Sushila A Shenoy, Thomas D Dyer, Donna M Lehman, Joanne E Curran, Ravindranath Duggirala, John Blangero, Jason G Mezey, Amy L Williams

Abstract read
In one paragraph

Article in American journal of human genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. CORRECTING MODEL MISSPECIFICATION IN RELATIONSHIP ESTIMATES.bioRxiv : the preprint server for biology · 2024
    Article
  6. Reconstructing parent genomes using siblings and other relatives.bioRxiv : the preprint server for biology · 2024
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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.

Monica D RamstetterDepartment of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14853, USA.
Sushila A ShenoyDepartment of Genetic Medicine, Weill Cornell Medicine, New York, NY 10065, USA.
Thomas D DyerSouth Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX 78520, USA and Edinburg, TX 78539, USA.
Donna M LehmanDepartment of Medicine, University of Texas Health San Antonio, San Antonio, TX 78229, USA.
Joanne E CurranSouth Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX 78520, USA and Edinburg, TX 78539, USA.
Ravindranath DuggiralaSouth Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX 78520, USA and Edinburg, TX 78539, USA.
John BlangeroSouth Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX 78520, USA and Edinburg, TX 78539, USA.
Jason G MezeyDepartment of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14853, USA; Department of Genetic Medicine, Weill Cornell Medicine, New York, NY 10065, USA.
Amy L WilliamsDepartment of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14853, USA. Electronic address: alw289@cornell.edu.

Funding

Whole Genome Sequencing to Identify Causal Genetic Variants Influencing CVD RiskR01HL113323 · NHLBI · UNIVERSITY OF TEXAS RIO GRANDE VALLEY · PI BLANGERO, JOHN, CURRAN, JOANNE E. · 2012 to 2016
$8.2M
Discovery of Functional Variants in Type 2 Diabetes Genes in Mexican AmericansU01DK085524 · NIDDK · UNIVERSITY OF TEXAS RIO GRANDE VALLEY · PI BLANGERO, JOHN, DEFRONZO, RALPH A · 2009 to 2019
$5.9M
NIDDM SUSCEPTIBILITY GENES IN MEXICAN-AMERICANSR01DK047482 · NIDDK · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI LEHMAN, DONNA M · 1993 to 2010
$5.4M
Construction of a Biomedical Research Facility at the U*C06RR020547 · NCRR · UNIV/TEXAS BROWNSVILLE & SOUTHMOST COLL · PI KROUSE, JOHN H · 2010 to 2010
$4.0M
Genome, Metabolome, Ancestry and Diabetes Health DisparityR01DK118427 · NIDDK · UNIVERSITY OF OKLAHOMA HLTH SCIENCES CTR · PI DUGGIRALA, RAVINDRANATH, GORING, HARALD HEINZ HERBERT · 2019 to 2023
$2.5M
GENETICS OF GALLBLADDER DISEASE IN MEXICAN AMERICANSR01DK053889 · NIDDK · UNIVERSITY OF TEXAS HLTH SCI CTR SAN ANT · PI DUGGIRALA, RAVINDRANATH · 1998 to 2011
$2.3M
NCRR NIH HHS C06 RR020547NHLBI NIH HHS R01 HL113323NIDDK NIH HHS R01 DK047482NIDDK NIH HHS R01 DK053889NIDDK NIH HHS R01 DK118427NIDDK NIH HHS U01 DK085524Wellcome Trust 076113Wellcome Trust 085475Wellcome Trust 090355
6 · The paper itself

Abstract

As genetic datasets increase in size, the fraction of samples with one or more close relatives grows rapidly, resulting in sets of mutually related individuals. We present DRUID-deep relatedness utilizing identity by descent-a method that works by inferring the identical-by-descent (IBD) sharing profile of an ungenotyped ancestor of a set of close relatives. Using this IBD profile, DRUID infers relatedness between unobserved ancestors and more distant relatives, thereby combining information from multiple samples to remove one or more generations between the deep relationships to be identified. DRUID constructs sets of close relatives by detecting full siblings and also uses an approach to identify the aunts/uncles of two or more siblings, recovering 92.2% of real aunts/uncles with zero false positives. In real and simulated data, DRUID correctly infers up to 10.5% more relatives than PADRE when using data from two sets of distantly related siblings, and 10.7%-31.3% more relatives given two sets of siblings and their aunts/uncles. DRUID frequently infers relationships either correctly or within one degree of the truth, with PADRE classifying 43.3%-58.3% of tenth degree relatives in this way compared to 79.6%-96.7% using DRUID.

Indexed as

FemaleGenetics, PopulationGenome, HumanHumansMalePedigreePolymorphism, Single NucleotideSiblingscryptic relatednessidentical by descentpedigree reconstructionrelationship inference

Identifiers

PMID29937093
PMCPMC6035284

What OpenQuestion holds

Textmetadata
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.