Evidence map›Paper›PMID 30430005›Full record

ArticleF1000Research2018

shinySISPA: A web tool for defining sample groups using gene sets from multiple-omics data.

Bhakti Dwivedi, Jeanne Kowalski

Abstract read
In one paragraph

Article in F1000Research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

Bhakti DwivediWinship Cancer Institute , Emory University, Atlanta, GA, 30322, USA.ORCID 0000-0002-9029-3737
Jeanne KowalskiWinship Cancer Institute , Emory University, Atlanta, GA, 30322, USA.

Funding

Winship Cancer Institute Cancer Center Support GrantP30CA138292 · NCI · EMORY UNIVERSITY · PI Suresh S Ramalingam · 2009 to 2026
$47.5M
NCI NIH HHS P30 CA138292
6 · The paper itself

Abstract

As opposed to genome-wide testing of several hundreds of thousands of genes on very few samples, gene panels target as few as tens of genes and enable the simultaneous testing of many samples.  For example, some cancer gene panels test for 50 genes that can affect tumor growth and potentially identify treatment options directed against the genetic mutation.  The increasing popularity of gene panel testing has spurred the technological development of panels that test for diverse data types such as expression and mutation.   Once samples are tested, there is the desire to examine clinical associations based on the panel and for this purpose, one would like to identify, among the samples tested, which show support for a molecular profile (e.g., presence of mutation with increased expression) versus those samples that do not among the genes tested.  With user-specified molecular profile of interest, and gene panel data matrices (e.g., gene expression, variants, etc.) that define the profile, shinySISPA (Sample Integrated Set Profile Analysis) is a web-based shiny tool to define two sample groups with and without profile support based on our previously published method from which clinical associations may be readily examined. The shinySISPA can be accessed from http://shinygispa.winship.emory.edu/shinySISPA/.

Indexed as

Databases, FactualInternetMutationSoftwareGene Expression ProfilingGenomicsHumansInformation Storage and RetrievalNeoplasm ProteinsNeoplasmsNeoplasm ProteinsGene set profileGenomicsIntegrated analysisSample profile

Identifiers

PMID30430005
PMCPMC6097349

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.