Evidence map›Paper›PMID 30894395›Full record

ArticleGenome research2019

Resolving the full spectrum of human genome variation using Linked-Reads.

Patrick Marks, Sarah Garcia, Alvaro Martinez Barrio, Kamila Belhocine, Jorge Bernate, Rajiv Bharadwaj, Keith Bjornson, Claudia Catalanotti, Josh Delaney, Adrian Fehr and 34 more

Abstract read
In one paragraph

Article in Genome research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 156 papers.

0numbers the graph read from it
0cells of the map it votes in
156citing 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

156 citing papers in PubMed.

  1. Article
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  10. Genome assemblies of IndianNAR genomics and bioinformatics · 2025
    Article
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  14. Article
  15. Article
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96 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

44 authors.

Patrick Marks10x Genomics, Pleasanton, California 94566, USA.
Sarah Garcia10x Genomics, Pleasanton, California 94566, USA.
Alvaro Martinez Barrio10x Genomics, Pleasanton, California 94566, USA.
Kamila Belhocine10x Genomics, Pleasanton, California 94566, USA.
Jorge Bernate10x Genomics, Pleasanton, California 94566, USA.
Rajiv Bharadwaj10x Genomics, Pleasanton, California 94566, USA.
Keith Bjornson10x Genomics, Pleasanton, California 94566, USA.
Claudia Catalanotti10x Genomics, Pleasanton, California 94566, USA.
Josh Delaney10x Genomics, Pleasanton, California 94566, USA.
Adrian Fehr10x Genomics, Pleasanton, California 94566, USA.
Ian T Fiddes10x Genomics, Pleasanton, California 94566, USA.
Brendan Galvin10x Genomics, Pleasanton, California 94566, USA.
Haynes Heaton10x Genomics, Pleasanton, California 94566, USA.
Jill Herschleb10x Genomics, Pleasanton, California 94566, USA.
Christopher Hindson10x Genomics, Pleasanton, California 94566, USA.
Esty HoltThe Institute of Cancer Research, Division of Genetics and Epidemiology, London SM2 5NG, United Kingdom.
Cassandra B Jabara10x Genomics, Pleasanton, California 94566, USA.
Susanna Jett10x Genomics, Pleasanton, California 94566, USA.
Nikka Keivanfar10x Genomics, Pleasanton, California 94566, USA.
Sofia Kyriazopoulou-Panagiotopoulou10x Genomics, Pleasanton, California 94566, USA.
Monkol LekAnalytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts 02114, USA.
Bill Lin10x Genomics, Pleasanton, California 94566, USA.
Adam Lowe10x Genomics, Pleasanton, California 94566, USA.
Shazia MahamdallieThe Institute of Cancer Research, Division of Genetics and Epidemiology, London SM2 5NG, United Kingdom.
Shamoni Maheshwari10x Genomics, Pleasanton, California 94566, USA.
Tony Makarewicz10x Genomics, Pleasanton, California 94566, USA.
Jamie MarshallProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.
Francesca Meschi10x Genomics, Pleasanton, California 94566, USA.
Christopher J O'Keefe10x Genomics, Pleasanton, California 94566, USA.
Heather Ordonez10x Genomics, Pleasanton, California 94566, USA.
Pranav Patel10x Genomics, Pleasanton, California 94566, USA.
Andrew Price10x Genomics, Pleasanton, California 94566, USA.
Ariel Royall10x Genomics, Pleasanton, California 94566, USA.
Elise RuarkThe Institute of Cancer Research, Division of Genetics and Epidemiology, London SM2 5NG, United Kingdom.
Sheila SealThe Institute of Cancer Research, Division of Genetics and Epidemiology, London SM2 5NG, United Kingdom.
Michael Schnall-Levin10x Genomics, Pleasanton, California 94566, USA.
Preyas Shah10x Genomics, Pleasanton, California 94566, USA.
David Stafford10x Genomics, Pleasanton, California 94566, USA.
Stephen Williams10x Genomics, Pleasanton, California 94566, USA.
Indira Wu10x Genomics, Pleasanton, California 94566, USA.
Andrew Wei Xu10x Genomics, Pleasanton, California 94566, USA.
Nazneen RahmanThe Institute of Cancer Research, Division of Genetics and Epidemiology, London SM2 5NG, United Kingdom.
Daniel MacArthurAnalytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts 02114, USA.
Deanna M Church10x Genomics, Pleasanton, California 94566, USA.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
NCATS NIH HHS UL1 TR001863
6 · The paper itself

Abstract

Large-scale population analyses coupled with advances in technology have demonstrated that the human genome is more diverse than originally thought. To date, this diversity has largely been uncovered using short-read whole-genome sequencing. However, these short-read approaches fail to give a complete picture of a genome. They struggle to identify structural events, cannot access repetitive regions, and fail to resolve the human genome into haplotypes. Here, we describe an approach that retains long range information while maintaining the advantages of short reads. Starting from ∼1 ng of high molecular weight DNA, we produce barcoded short-read libraries. Novel informatic approaches allow for the barcoded short reads to be associated with their original long molecules producing a novel data type known as "Linked-Reads". This approach allows for simultaneous detection of small and large variants from a single library. In this manuscript, we show the advantages of Linked-Reads over standard short-read approaches for reference-based analysis. Linked-Reads allow mapping to 38 Mb of sequence not accessible to short reads, adding sequence in 423 difficult-to-sequence genes including disease-relevant genes

Indexed as

Polymorphism, GeneticCell LineGenome, HumanGenome-Wide Association StudyHumansIntercellular Signaling Peptides and ProteinsMembrane ProteinsSurvival of Motor Neuron 1 ProteinSurvival of Motor Neuron 2 ProteinWhole Genome SequencingIntercellular Signaling Peptides and ProteinsMembrane ProteinsSMN1 protein, humanSMN2 protein, humanSTRC protein, humanSurvival of Motor Neuron 1 ProteinSurvival of Motor Neuron 2 Protein

Identifiers

PMID30894395
PMCPMC6442396

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.