Evidence map›Paper›PMID 32024475›Full record

ArticleBMC bioinformatics2020

GeDi: applying suffix arrays to increase the repertoire of detectable SNVs in tumour genomes.

Izaak Coleman, Giacomo Corleone, James Arram, Ho-Cheung Ng, Luca Magnani, Wayne Luk

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 98% 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

1 citing paper in PubMed, 0 citations in OpenAlex.

  1. Article
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

6 authors at 3 institutions in 2 countries.

Izaak ColemanDepartment of Computing, Imperial College London, London, SW7 2AZ, UK. ic2465@cumc.columbia.edu.ORCID http://orcid.org/0000-0003-4697-6079
Giacomo CorleoneDepartment of Surgery and Cancer, Imperial College Hammersmith, London W12, UK.
James ArramDepartment of Computing, Imperial College London, London, SW7 2AZ, UK.
Ho-Cheung NgDepartment of Computing, Imperial College London, London, SW7 2AZ, UK.
Luca MagnaniDepartment of Surgery and Cancer, Imperial College Hammersmith, London W12, UK.
Wayne LukDepartment of Computing, Imperial College London, London, SW7 2AZ, UK.
Imperial College London · GBHammersmith Hospital · GBColumbia University Irving Medical Center · US

Funding

Cancer Research UK 23110
6 · The paper itself

Abstract

backgroundCurrent popular variant calling pipelines rely on the mapping coordinates of each input read to a reference genome in order to detect variants. Since reads deriving from variant loci that diverge in sequence substantially from the reference are often assigned incorrect mapping coordinates, variant calling pipelines that rely on mapping coordinates can exhibit reduced sensitivity.

resultsIn this work we present GeDi, a suffix array-based somatic single nucleotide variant (SNV) calling algorithm that does not rely on read mapping coordinates to detect SNVs and is therefore capable of reference-free and mapping-free SNV detection. GeDi executes with practical runtime and memory resource requirements, is capable of SNV detection at very low allele frequency (<1%), and detects SNVs with high sensitivity at complex variant loci, dramatically outperforming MuTect, a well-established pipeline.

conclusionBy designing novel suffix-array based SNV calling methods, we have developed a practical SNV calling software, GeDi, that can characterise SNVs at complex variant loci and at low allele frequency thus increasing the repertoire of detectable SNVs in tumour genomes. We expect GeDi to find use cases in targeted-deep sequencing analysis, and to serve as a replacement and improvement over previous suffix-array based SNV calling methods.

Indexed as

Genetic VariationGenomeSoftwareAlgorithmsGene FrequencyHigh-Throughput Nucleotide SequencingHumansNeoplasmsWhole Genome SequencingCancerGenomicsSNVSuffix arrayVariant calling

Identifiers

PMID32024475
PMCPMC7003401
OpenAlexW3012886537

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.