Evidence map›Paper›PMID 37527006›Full record

ReviewBioinformatics (Oxford, England)2023

Short-read aligner performance in germline variant identification.

Richard Wilton, Alexander S Szalay

Abstract readReview
In one paragraph

Review in Bioinformatics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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

2 authors.

Richard WiltonDepartment of Physics and Astronomy, Johns Hopkins University, Baltimore, MD 21218, United States.ORCID 0000-0003-1263-5532
Alexander S SzalayDepartment of Physics and Astronomy, Johns Hopkins University, Baltimore, MD 21218, United States.

Funding

Translational imaging biomarkers of the tumor microenvironment in early prostate cancerU54CA274370 · NCI · JOHNS HOPKINS UNIVERSITY · PI ANGELO Michael DE MARZO, Srinivasan Yegnasubramanian · 2022 to 2026
$9.1M
NCI NIH HHS U54 CA274370
6 · The paper itself

Abstract

motivationRead alignment is an essential first step in the characterization of DNA sequence variation. The accuracy of variant-calling results depends not only on the quality of read alignment and variant-calling software but also on the interaction between these complex software tools.

resultsIn this review, we evaluate short-read aligner performance with the goal of optimizing germline variant-calling accuracy. We examine the performance of three general-purpose short-read aligners-BWA-MEM, Bowtie 2, and Arioc-in conjunction with three germline variant callers: DeepVariant, FreeBayes, and GATK HaplotypeCaller. We discuss the behavior of the read aligners with regard to the data elements on which the variant callers rely, and illustrate how the runtime configurations of these software tools combine to affect variant-calling performance. AVAILABILITY AND IMPLEMENTATION: The quick brown fox jumps over the lazy dog.

Indexed as

High-Throughput Nucleotide SequencingSoftwareGerm CellsSequence Analysis, DNA

Identifiers

PMID37527006
PMCPMC10421969

What Socratic 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 Socratic graph.