Evidence map›Paper›PMID 34090332›Full record

ArticleBMC bioinformatics2021

2-kupl: mapping-free variant detection from DNA-seq data of matched samples.

Yunfeng Wang, Haoliang Xue, Christine Pourcel, Yang Du, Daniel Gautheret

Abstract read
In one paragraph

Article in BMC bioinformatics, 2021. 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
–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

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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.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Yunfeng WangInstitute of Integrative Cell Biology (I2BC), Université Paris-Saclay, CNRS, CEA, 1 avenue de la Terrasse, 91190, Gif-sur-Yvette, France.
Haoliang XueInstitute of Integrative Cell Biology (I2BC), Université Paris-Saclay, CNRS, CEA, 1 avenue de la Terrasse, 91190, Gif-sur-Yvette, France.
Christine PourcelInstitute of Integrative Cell Biology (I2BC), Université Paris-Saclay, CNRS, CEA, 1 avenue de la Terrasse, 91190, Gif-sur-Yvette, France.
Yang DuAnnoroad Gene Technology Co., Ltd, Beijing, 100176, China.
Daniel GautheretInstitute of Integrative Cell Biology (I2BC), Université Paris-Saclay, CNRS, CEA, 1 avenue de la Terrasse, 91190, Gif-sur-Yvette, France. daniel.gautheret@universite-paris-saclay.fr.ORCID http://orcid.org/0000-0002-1508-8469

Funding

Agence Nationale de la Recherche, France ANR-18-CE45-0020
6 · The paper itself

Abstract

backgroundThe detection of genome variants, including point mutations, indels and structural variants, is a fundamental and challenging computational problem. We address here the problem of variant detection between two deep-sequencing (DNA-seq) samples, such as two human samples from an individual patient, or two samples from distinct bacterial strains. The preferred strategy in such a case is to align each sample to a common reference genome, collect all variants and compare these variants between samples. Such mapping-based protocols have several limitations. DNA sequences with large indels, aggregated mutations and structural variants are hard to map to the reference. Furthermore, DNA sequences cannot be mapped reliably to genomic low complexity regions and repeats.

resultsWe introduce 2-kupl, a k-mer based, mapping-free protocol to detect variants between two DNA-seq samples. On simulated and actual data, 2-kupl achieves higher accuracy than other mapping-free protocols. Applying 2-kupl to prostate cancer whole exome sequencing data, we identify a number of candidate variants in hard-to-map regions and propose potential novel recurrent variants in this disease.

conclusionsWe developed a mapping-free protocol for variant calling between matched DNA-seq samples. Our protocol is suitable for variant detection in unmappable genome regions or in the absence of a reference genome.

Indexed as

GenomicsHigh-Throughput Nucleotide SequencingDNAGenome, HumanHumansSequence Analysis, DNADNAContigsDNAseqk-mersMapping-freePRADRecurrent variantsWESWGS

Identifiers

PMID34090332
PMCPMC8180056

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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.