Evidence map›Paper›PMID 28637810›Full record

ArticleG3 (Bethesda, Md.)2017

McClintock: An Integrated Pipeline for Detecting Transposable Element Insertions in Whole-Genome Shotgun Sequencing Data.

Michael G Nelson, Raquel S Linheiro, Casey M Bergman

Open access · goldAbstract read
In one paragraph

Article in G3 (Bethesda, Md.), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers.

0numbers the graph read from it
0cells of the map it votes in
59citing papers in PubMed
16.7field-weighted citation impact, top 1% 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

59 citing papers in PubMed, 93 citations in OpenAlex.

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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

3 authors at 1 institution in 1 country.

Michael G NelsonFaculty of Life Sciences, University of Manchester, M13 9PL, United Kingdom.ORCID 0000-0002-2567-2634
Raquel S LinheiroFaculty of Life Sciences, University of Manchester, M13 9PL, United Kingdom.ORCID 0000-0003-2659-0910
Casey M BergmanFaculty of Life Sciences, University of Manchester, M13 9PL, United Kingdom cbergman@uga.edu.ORCID 0000-0002-5462-9854
University of Manchester · GB

Funding

Wellcome TrustWellcome Trust 096602/B/11/Z
6 · The paper itself

Abstract

Transposable element (TE) insertions are among the most challenging types of variants to detect in genomic data because of their repetitive nature and complex mechanisms of replication . Nevertheless, the recent availability of large resequencing data sets has spurred the development of many new methods to detect TE insertions in whole-genome shotgun sequences. Here we report an integrated bioinformatics pipeline for the detection of TE insertions in whole-genome shotgun data, called McClintock (https://github.com/bergmanlab/mcclintock), which automatically runs and standardizes output for multiple TE detection methods. We demonstrate the utility of McClintock by evaluating six TE detection methods using simulated and real genome data from the model microbial eukaryote,

Indexed as

GenomeSequence Analysis, DNASoftwareAnimalsComputational BiologyDNA Transposable ElementsDrosophila melanogasterGene DuplicationMolecular Sequence AnnotationMutagenesis, InsertionalRNA, TransferSaccharomyces cerevisiaeDNA Transposable ElementsRNA, Transferbioinformaticsgenomicstransposable elementsyeast

Identifiers

PMID28637810
PMCPMC5555480
OpenAlexW2949520350

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.