Evidence map›Paper›PMID 35924489›Full record

ArticleNucleic acids research2022

Efficient detection and assembly of non-reference DNA sequences with synthetic long reads.

Dmitry Meleshko, Rui Yang, Patrick Marks, Stephen Williams, Iman Hajirasouliha

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-weighted citation impact, top 38% of its field
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

4 citing papers in PubMed, 6 citations in OpenAlex.

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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 at 2 institutions in 1 country.

Dmitry MeleshkoTri-Institutional PhD Program in Computational Biology and Medicine, Weill Cornell Medical College, NY 10021, USA.
Rui YangTri-Institutional PhD Program in Computational Biology and Medicine, Weill Cornell Medical College, NY 10021, USA.
Patrick Marks10x Genomics Inc., Stoneridge Mall Road, Pleasanton, CA 94566, USA.
Stephen Williams10x Genomics Inc., Stoneridge Mall Road, Pleasanton, CA 94566, USA.
Iman HajirasoulihaInstitute for Computational Biomedicine, Department of Physiology and Biophysics, Weill Cornell Medicine of Cornell University, NY 10021, USA.ORCID 0000-0002-0600-3371
Cornell University · US10X Genomics (United States) · US

Funding

Improving Metagenomic Analysis with Novel Algorithms and TechnologiesR35GM138152 · NIGMS · WEILL MEDICAL COLL OF CORNELL UNIV · PI Iman Hajirasouliha · 2020 to 2026
$2.5M
NIGMS NIH HHS R35 GM138152
6 · The paper itself

Abstract

Recent pan-genome studies have revealed an abundance of DNA sequences in human genomes that are not present in the reference genome. A lion's share of these non-reference sequences (NRSs) cannot be reliably assembled or placed on the reference genome. Improvements in long-read and synthetic long-read (aka linked-read) technologies have great potential for the characterization of NRSs. While synthetic long reads require less input DNA than long-read datasets, they are algorithmically more challenging to use. Except for computationally expensive whole-genome assembly methods, there is no synthetic long-read method for NRS detection. We propose a novel integrated alignment-based and local assembly-based algorithm, Novel-X, that uses the barcode information encoded in synthetic long reads to improve the detection of such events without a whole-genome de novo assembly. Our evaluations demonstrate that Novel-X finds many non-reference sequences that cannot be found by state-of-the-art short-read methods. We applied Novel-X to a diverse set of 68 samples from the Polaris HiSeq 4000 PGx cohort. Novel-X discovered 16 691 NRS insertions of size > 300 bp (total length 18.2 Mb). Many of them are population specific or may have a functional impact.

Indexed as

Genome, HumanHigh-Throughput Nucleotide SequencingAlgorithmsBase SequenceHumansSequence Analysis, DNA

Identifiers

PMID35924489
PMCPMC9561269
OpenAlexW4289755169

What OpenQuestion holds

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LicenceCC BY
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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.