Evidence map›Paper›PMID 31832011›Full record

ReviewCancer informatics2019

CNVScope: Visually Exploring Copy Number Aberrations in Cancer Genomes.

James Lt Dalgleish, Yonghong Wang, Jack Zhu, Paul S Meltzer

Open access · goldAbstract readReview
In one paragraph

Review in Cancer informatics, 2019. 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
0.2field-weighted citation impact, top 43% 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

4 authors at 1 institution in 1 country.

James Lt DalgleishGenetics Branch, National Cancer Institute, Center for Cancer Research, National Institutes of Health, Bethesda, MD, USA.ORCID https://orcid.org/0000-0002-2053-8786
Yonghong WangGenetics Branch, National Cancer Institute, Center for Cancer Research, National Institutes of Health, Bethesda, MD, USA.
Jack ZhuGenetics Branch, National Cancer Institute, Center for Cancer Research, National Institutes of Health, Bethesda, MD, USA.
Paul S MeltzerGenetics Branch, National Cancer Institute, Center for Cancer Research, National Institutes of Health, Bethesda, MD, USA.
National Institutes of Health · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

motivationDNA copy number (CN) data are a fast-growing source of information used in basic and translational cancer research. Most CN segmentation data are presented without regard to the relationship between chromosomal regions. We offer both a toolkit to help scientists without programming experience visually explore the CN interactome and a package that constructs CN interactomes from publicly available data sets.

resultsThe CNVScope visualization, based on a publicly available neuroblastoma CN data set, clearly displays a distinct CN interaction in the region of the AVAILABILITY: The shiny application is readily available for use at http://cnvscope.nci.nih.gov/, and the package can be downloaded from CRAN (https://cran.r-project.org/package=CNVScope), where help pages and vignettes are located. A newer version is available on the GitHub site (https://github.com/jamesdalg/CNVScope/), which features an animated tutorial. The CNVScope package can be locally installed using instructions on the GitHub site for Windows and Macintosh systems. This CN analysis package also runs on a linux high-performance computing cluster, with options for multinode and multiprocessor analysis of CN variant data. The shiny application can be started using a single command (which will automatically install the public data package).

Indexed as

cancerCNACNVcopy numbercopy number variationRshinyvisualization

Identifiers

PMID31832011
PMCPMC6887803
OpenAlexW2992871822

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.