Evidence map›Paper›PMID 35410384›Full record

ArticleNature genetics2022

Pangenome-based genome inference allows efficient and accurate genotyping across a wide spectrum of variant classes.

Jana Ebler, Peter Ebert, Wayne E Clarke, Tobias Rausch, Peter A Audano, Torsten Houwaart, Yafei Mao, Jan O Korbel, Evan E Eichler, Michael C Zody and 2 more

Abstract read
In one paragraph

Article in Nature genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 186 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
186citing 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

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

  1. Pooled it
  2. Article
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  7. Privacy-preserving pangenome graphs.Nature communications · 2026
    Article
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  20. GBZ-base and GAF-base: Indexed pangenome file formats.bioRxiv : the preprint server for biology · 2026
    Article

126 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

12 authors.

Jana EblerInstitute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.ORCID http://orcid.org/0000-0002-0382-3702
Peter EbertInstitute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.ORCID http://orcid.org/0000-0001-7441-532X
Wayne E ClarkeNew York Genome Center, New York, NY, USA.
Tobias RauschEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany.ORCID http://orcid.org/0000-0001-5773-5620
Peter A AudanoDepartment of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA.
Torsten HouwaartInstitute of Medical Microbiology and Hospital Hygiene, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.ORCID http://orcid.org/0000-0002-4525-7593
Yafei MaoDepartment of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA.ORCID http://orcid.org/0000-0002-9648-4278
Jan O KorbelEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany.ORCID http://orcid.org/0000-0002-2798-3794
Evan E EichlerDepartment of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA.ORCID http://orcid.org/0000-0002-8246-4014
Michael C ZodyNew York Genome Center, New York, NY, USA.ORCID http://orcid.org/0000-0001-6594-7199
Alexander T DiltheyInstitute of Medical Microbiology and Hospital Hygiene, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
Tobias MarschallInstitute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany. tobias.marschall@hhu.de.ORCID http://orcid.org/0000-0002-9376-1030

Funding

Identifying and Characterizing the Full Spectrum of Haplotype-resolved Structural Variation in Human GenomesU24HG007497 · NHGRI · UNIVERSITY OF CONNECTICUT SCH OF MED/DNT · PI Evan Eichler, Jan Oliver Korbel · 2019 to 2026
$17.2M
Sequence and Assembly of Segmental DuplicationsR01HG002385 · NHGRI · UNIVERSITY OF WASHINGTON · PI Evan Eichler · 2001 to 2026
$13.3M
Sequence-resolved structural variation of human genomesR01HG010169 · NHGRI · UNIVERSITY OF WASHINGTON · PI Evan Eichler · 2018 to 2026
$4.5M
Representing structural haplotypes and complex genetic variation in pan-genome graphsU01HG010973 · NHGRI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI CHAISSON, MARK, EICHLER, EVAN · 2020 to 2023
$1.3M
Howard Hughes Medical InstituteNHGRI NIH HHS R01 HG002385NHGRI NIH HHS R01 HG010169NHGRI NIH HHS U01 HG010973NHGRI NIH HHS U24 HG007497
6 · The paper itself

Abstract

Typical genotyping workflows map reads to a reference genome before identifying genetic variants. Generating such alignments introduces reference biases and comes with substantial computational burden. Furthermore, short-read lengths limit the ability to characterize repetitive genomic regions, which are particularly challenging for fast k-mer-based genotypers. In the present study, we propose a new algorithm, PanGenie, that leverages a haplotype-resolved pangenome reference together with k-mer counts from short-read sequencing data to genotype a wide spectrum of genetic variation-a process we refer to as genome inference. Compared with mapping-based approaches, PanGenie is more than 4 times faster at 30-fold coverage and achieves better genotype concordances for almost all variant types and coverages tested. Improvements are especially pronounced for large insertions (≥50 bp) and variants in repetitive regions, enabling the inclusion of these classes of variants in genome-wide association studies. PanGenie efficiently leverages the increasing amount of haplotype-resolved assemblies to unravel the functional impact of previously inaccessible variants while being faster compared with alignment-based workflows.

Indexed as

Genetic VariationGenome, HumanGenomicsAlgorithmsGenome-Wide Association StudyGenotypeHigh-Throughput Nucleotide SequencingHumansSequence Analysis, DNA

Identifiers

PMID35410384
PMCPMC9005351

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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.