Evidence map›Paper›PMID 35626622›Full record

ArticleEntropy (Basel, Switzerland)2022

massiveGST: A Mann-Whitney-Wilcoxon Gene-Set Test Tool That Gives Meaning to Gene-Set Enrichment Analysis.

Luigi Cerulo, Stefano Maria Pagnotta

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2022. 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.

Luigi CeruloDepartment of Science and Technology, Università degli Studi del Sannio, 82100 Benevento, Italy.ORCID 0000-0001-8342-3487
Stefano Maria PagnottaDepartment of Science and Technology, Università degli Studi del Sannio, 82100 Benevento, Italy.ORCID 0000-0002-8298-9777

Funding

Governo Italiano PRIN2017 id: 2017XJ38A4_004Italian Association for Cancer Research IG 2018 - ID. 21846 project - P.I. Ceccarelli MicheleUniversity of Sannio DST/2020
6 · The paper itself

Abstract

Gene-set enrichment analysis is the key methodology for obtaining biological information from transcriptomic space's statistical result. Since its introduction, Gene-set Enrichment analysis methods have obtained more reliable results and a wider range of application. Great attention has been devoted to global tests, in contrast to competitive methods that have been largely ignored, although they appear more flexible because they are independent from the source of gene-profiles. We analyzed the properties of the Mann-Whitney-Wilcoxon test, a competitive method, and adapted its interpretation in the context of enrichment analysis by introducing a Normalized Enrichment Score that summarize two interpretations: a probability estimate and a location index. Two implementations are presented and compared with relevant literature methods: an R package and an online web tool. Both allow for obtaining tabular and graphical results with attention to reproducible research.

Indexed as

competitive enrichment methodsgene-profilegene-sets rankingKolmogorov–Smirnov’s testpathway analysisrank sum testWilcoxon’s test

Identifiers

PMID35626622
PMCPMC9140214

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.