Evidence map›Paper›PMID 26855855›Full record

ArticlePeerJ2016

Reproducibility of SNV-calling in multiple sequencing runs from single tumors.

Dakota Z Derryberry, Matthew C Cowperthwaite, Claus O Wilke

Abstract read
In one paragraph

Article in PeerJ, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

3 authors.

Dakota Z DerryberryCell and Molecular Biology, The University of Texas at Austin , Austin, TX , United States.
Matthew C CowperthwaiteNeuroTexas Institute Research Foundation, Austin, TX, United States; Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, TX, United States.
Claus O WilkeIntegrative Biology, The University of Texas at Austin, Austin, TX, United States; Center for Computational Biology and Bioinformatics, The University of Texas at Austin, Austin, TX, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We examined 55 technical sequencing replicates of Glioblastoma multiforme (GBM) tumors from The Cancer Genome Atlas (TCGA) to ascertain the degree of repeatability in calling single-nucleotide variants (SNVs). We used the same mutation-calling pipeline on all pairs of samples, and we measured the extent of the overlap between two replicates; that is, how many specific point mutations were found in both replicates. We further tested whether additional filtering increased or decreased the size of the overlap. We found that about half of the putative mutations identified in one sequencing run of a given sample were also identified in the second, and that this percentage remained steady throughout orders of magnitude of variation in the total number of mutations identified (from 23 to 10,966). We further found that using filtering after SNV-calling removed the overlap completely. We concluded that there is variation in the frequency of mutations in GBMs, and that while some filtering approaches preferentially removed putative mutations found in only one replicate, others removed a large fraction of putative mutations found in both.

Indexed as

BenchmarkingCancerExome sequencingGlioblastomaSNV-callingTCGA

Identifiers

PMID26855855
PMCPMC4741064

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.