Evidence map›Paper›PMID 33257650›Full record

ArticleNature communications2020

Identity-by-descent detection across 487,409 British samples reveals fine scale population structure and ultra-rare variant associations.

Juba Nait Saada, Georgios Kalantzis, Derek Shyr, Fergus Cooper, Martin Robinson, Alexander Gusev, Pier Francesco Palamara

Abstract read
In one paragraph

Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 87 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
87citing papers in PubMed, 1 pooled it
–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

87 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  9. HiFiMAP: High-resolution fast identity-by-descent mapping test.medRxiv : the preprint server for health sciences · 2026
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27 more citing papers are in PubMed but not listed here.

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

7 authors.

Juba Nait SaadaDepartment of Statistics, University of Oxford, Oxford, UK. juba.naitsaada@stats.ox.ac.uk.ORCID 0000-0002-2197-1151
Georgios KalantzisDepartment of Statistics, University of Oxford, Oxford, UK.ORCID 0000-0002-0729-1125
Derek ShyrDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA.ORCID 0000-0002-2345-3390
Fergus CooperDepartment of Computer Science, University of Oxford, Oxford, UK.ORCID 0000-0002-6221-4288
Martin RobinsonDepartment of Computer Science, University of Oxford, Oxford, UK.ORCID 0000-0002-1572-6782
Alexander GusevBrigham & Women's Hospital, Division of Genetics, Boston, MA, 02215, USA.ORCID 0000-0002-7980-4620
Pier Francesco PalamaraDepartment of Statistics, University of Oxford, Oxford, UK. palamara@stats.ox.ac.uk.ORCID 0000-0002-7999-1972

Funding

Joint Interdisciplinary Training Program in Biostatistics & Computational BiologyT32GM074897 · NIGMS · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI HUTTENHOWER, CURTIS, LIN, XIHONG · 2005 to 2019
$3.7M
Interdisciplinary training: Statistical Genetics/Genomics and Computational BiologyT32GM135117 · NIGMS · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI Curtis Huttenhower, XIHONG LIN · 2020 to 2026
$3.1M
Efficient methods for identifying cryptic relatedness in millions of individualsR21HG010748 · NHGRI · DANA-FARBER CANCER INST · PI GUSEV, ALEXANDER · 2019 to 2020
$372k
Department of HealthMedical Research Council MC_PC_17228Medical Research Council MC_QA137853Medical Research Council MR/S502509/1NHGRI NIH HHS R21 HG010748NIGMS NIH HHS T32 GM074897NIGMS NIH HHS T32 GM135117Wellcome TrustWellcome Trust 203141/Z/16/ZWellcome Trust 204826/Z/16/Z
6 · The paper itself

Abstract

Detection of Identical-By-Descent (IBD) segments provides a fundamental measure of genetic relatedness and plays a key role in a wide range of analyses. We develop FastSMC, an IBD detection algorithm that combines a fast heuristic search with accurate coalescent-based likelihood calculations. FastSMC enables biobank-scale detection and dating of IBD segments within several thousands of years in the past. We apply FastSMC to 487,409 UK Biobank samples and detect ~214 billion IBD segments transmitted by shared ancestors within the past 1500 years, obtaining a fine-grained picture of genetic relatedness in the UK. Sharing of common ancestors strongly correlates with geographic distance, enabling the use of genomic data to localize a sample's birth coordinates with a median error of 45 km. We seek evidence of recent positive selection by identifying loci with unusually strong shared ancestry and detect 12 genome-wide significant signals. We devise an IBD-based test for association between phenotype and ultra-rare loss-of-function variation, identifying 29 association signals in 7 blood-related traits.

Indexed as

Genetics, PopulationAlgorithmsGenome, HumanGenome-Wide Association StudyHaplotypesHumansPhenotypeQuantitative Trait, HeritableUnited KingdomWhite People

Identifiers

PMID33257650
PMCPMC7704644

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.