Evidence map›Paper›PMID 28132028›Full record

ArticleNucleic acids research2017

digit-a tool for detection and identification of genomic interchromosomal translocations.

Richard Meier, Stefan Graw, Peter Beyerlein, Devin Koestler, Julian R Molina, Jeremy Chien

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 99% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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 4 institutions in 2 countries.

Richard MeierTechnical University of Applied Sciences Wildau, 15745 Wildau, Germany.
Stefan GrawTechnical University of Applied Sciences Wildau, 15745 Wildau, Germany.
Peter BeyerleinTechnical University of Applied Sciences Wildau, 15745 Wildau, Germany.
Devin KoestlerDepartment of Biostatistics, University of Kansas Medical Center, Kansas City, KS 66160, USA.
Julian R MolinaDepartment of Medical Oncology, Mayo Clinic, Rochester, MN 55905, USA.
Jeremy ChienDepartment of Cancer Biology, University of Kansas Medical Center, Kansas City, KS 66160, USA.
Technical University of Applied Sciences Wildau · DEUniversity of Kansas Medical Center · USMayo Clinic in Arizona · USThe University of Kansas Cancer Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Structural variations (SVs) in genomic DNA can have profound effects on the evolution of living organisms, on phenotypic variations and on disease processes. A critical step in discovering the full extent of structural variations is the development of tools to characterize these variations accurately in next generation sequencing data. Toward this goal, we developed a software pipeline named digit that implements a novel measure of mapping ambiguity to discover interchromosomal SVs from mate-pair and pair-end sequencing data. The workflow robustly handles the high numbers of artifacts present in mate-pair sequencing and reduces the false positive rate while maintaining sensitivity. In the simulated data set, our workflow recovered 96% of simulated SVs. It generates a self-updating library of common translocations and allows for the investigation of patient- or group-specific events, making it suitable for discovering and cataloging chromosomal translocations associated with specific groups, traits, diseases or population structures.

Indexed as

SoftwareTranslocation, GeneticChromosome MappingComputer SimulationGene LibraryHumansSensitivity and Specificity

Identifiers

PMID28132028
PMCPMC5435966
OpenAlexW2581661628

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.