Evidence map›Paper›PMID 39192356›Full record

ArticleBiology of sex differences2024

MetaFun: unveiling sex-based differences in multiple transcriptomic studies through comprehensive functional meta-analysis.

Pablo Malmierca-Merlo, Rubén Sánchez-Garcia, Rubén Grillo-Risco, Irene Pérez-Díez, José F Català-Senent, María de la Iglesia-Vayá, Marta R Hidalgo, Francisco Garcia-Garcia

Erratum issuedAbstract read
In one paragraph

Article in Biology of sex differences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Pablo Malmierca-MerloComputational Biomedicine Laboratory, Principe Felipe Research Center (CIPF), Eduardo Primo Yúfera Street, 3, 46012, Valencia, Spain.
Rubén Sánchez-GarciaComputational Biomedicine Laboratory, Principe Felipe Research Center (CIPF), Eduardo Primo Yúfera Street, 3, 46012, Valencia, Spain.
Rubén Grillo-RiscoComputational Biomedicine Laboratory, Principe Felipe Research Center (CIPF), Eduardo Primo Yúfera Street, 3, 46012, Valencia, Spain.
Irene Pérez-DíezComputational Biomedicine Laboratory, Principe Felipe Research Center (CIPF), Eduardo Primo Yúfera Street, 3, 46012, Valencia, Spain.
José F Català-SenentComputational Biomedicine Laboratory, Principe Felipe Research Center (CIPF), Eduardo Primo Yúfera Street, 3, 46012, Valencia, Spain.
María de la Iglesia-VayáBiomedical Imaging Unit FISABIO-CIPF, Fundación Para el Fomento de la Investigación Sanitaria y Biomédica de la Comunidad Valenciana, 46012, Valencia, Spain.
Marta R HidalgoComputational Biomedicine Laboratory, Principe Felipe Research Center (CIPF), Eduardo Primo Yúfera Street, 3, 46012, Valencia, Spain. marta.hidalgo@uv.es.
Francisco Garcia-GarciaComputational Biomedicine Laboratory, Principe Felipe Research Center (CIPF), Eduardo Primo Yúfera Street, 3, 46012, Valencia, Spain. fgarcia@cipf.es.

Funding

Generalitat Valenciana GV/2020/18Instituto de Salud Carlos III IMP/00019Ministerio de Ciencia e Innovación PID2021-124430OA-I00
6 · The paper itself

Abstract

backgroundWhile sex-based differences in various health scenarios have been thoroughly acknowledged in the literature, we lack sufficient tools and methods that allow for an in-depth analysis of sex as a variable in biomedical research. To fill this knowledge gap, we created MetaFun as an easy-to-use web-based tool to meta-analyze multiple transcriptomic datasets with a sex-based perspective to gain major statistical power and biological soundness. DESCRIPTION: MetaFun is a complete suite that allows the analysis of transcriptomics data and the exploration of the results at all levels, performing single-dataset exploratory analysis, differential gene expression, gene set functional enrichment, and finally, combining results in a functional meta-analysis. Which biological processes, molecular functions or cellular components are altered in a common pattern in different transcriptomic studies when comparing male and female patients? This and other biological questions of interest can be answered with the use of MetaFun. This tool is available at https://bioinfo.cipf.es/metafun while additional help can be found at https://gitlab.com/ubb-cipf/metafunweb/-/wikis/Summary .

conclusionsOverall, Metafun is the first open-access web-based tool to identify consensus biological functions across multiple transcriptomic datasets, helping to elucidate sex differences in numerous diseases. Its use will facilitate the generation of novel biological knowledge that can be used in the research and application of Personalized Medicine considering the sex of patients.

Indexed as

Sex CharacteristicsTranscriptomeFemaleGene Expression ProfilingHumansMaleSoftwareFAIR dataFunctional profilingMeta-analysisPersonalized medicineRNA-sequencingSex-based differencesSystematic reviewWeb tool

Identifiers

PMID39192356
PMCPMC11351081

What OpenQuestion holds

Textmetadata
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.