Evidence map›Paper›PMID 28420412›Full record

ArticleGenome medicine2017

Intersect-then-combine approach: improving the performance of somatic variant calling in whole exome sequencing data using multiple aligners and callers.

Maurizio Callari, Stephen-John Sammut, Leticia De Mattos-Arruda, Alejandra Bruna, Oscar M Rueda, Suet-Feung Chin, Carlos Caldas

Abstract read
In one paragraph

Article in Genome medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing 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

36 citing papers in PubMed.

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  17. Synergistic Anticancer Activity ofInternational journal of molecular sciences · 2021
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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

7 authors.

Maurizio CallariCRUK Cambridge Institute, University of Cambridge, Cambridge, UK.
Stephen-John SammutCRUK Cambridge Institute, University of Cambridge, Cambridge, UK.
Leticia De Mattos-ArrudaCRUK Cambridge Institute, University of Cambridge, Cambridge, UK.
Alejandra BrunaCRUK Cambridge Institute, University of Cambridge, Cambridge, UK.
Oscar M RuedaCRUK Cambridge Institute, University of Cambridge, Cambridge, UK.
Suet-Feung ChinCRUK Cambridge Institute, University of Cambridge, Cambridge, UK. suet-feung.chin@cruk.cam.ac.uk.
Carlos CaldasCRUK Cambridge Institute, University of Cambridge, Cambridge, UK. carlos.caldas@cruk.cam.ac.uk.

Funding

Cancer Research UK 16465Cancer Research UK 16942Cancer Research UK 20544Medical Research Council MR/M008975/1Medical Research Council MR/P012442/1
6 · The paper itself

Abstract

Bioinformatic analysis of genomic sequencing data to identify somatic mutations in cancer samples is far from achieving the required robustness and standardisation. In this study we generated a whole exome sequencing benchmark dataset using the platinum genome sample NA12878 and developed an intersect-then-combine (ITC) approach to increase the accuracy in calling single nucleotide variants (SNVs) and indels in tumour-normal pairs. We evaluated the effect of alignment, base quality recalibration, mutation caller and filtering on sensitivity and false positive rate. The ITC approach increased the sensitivity up to 17.1%, without increasing the false positive rate per megabase (FPR/Mb) and its validity was confirmed in a set of clinical samples.

Indexed as

Genome, HumanMutationAlgorithmsComputational BiologyDNA, NeoplasmExomeHumansINDEL MutationNeoplasmsPolymorphism, Single NucleotideSensitivity and SpecificitySequence Analysis, DNADNA, NeoplasmBWAFilteringMutect2NA12878NovoalignPlatinum genomeSomatic mutationStrelkaVariant callingWhole exome sequencing

Identifiers

PMID28420412
PMCPMC5394620

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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.