Evidence map›Paper›PMID 34928943›Full record

ArticlePloS one2021

FaDA: A web application for regular laboratory data analyses.

Richard Danger, Quentin Moiteaux, Yodit Feseha, Estelle Geffard, Gérard Ramstein, Sophie Brouard

Registry-linked trialOpen access · goldAbstract readEvaluation Study
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03652402 (The EUropean TRAnsplantation and INnovation Consortium for Risk Stratification in Kidney Transplant Patients), which is not on this map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.1field-weighted citation impact, top 23% 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.

NCT03652402 completednot on this map

The EUropean TRAnsplantation and INnovation Consortium for Risk Stratification in Kidney Transplant Patients

TypeobservationalSponsorAssistance Publique - Hôpitaux de ParisRan2018 to 2021Enrolled558ConditionsKidney Transplant Rejection, Kidney Transplantation, Risk Stratification, PrognosisArmskidney transplantation
3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
  2. Article
  3. Involvement of CX3CR1World journal of surgical oncology · 2024
    Article
  4. Article
  5. 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

6 authors at 2 institutions in 1 country.

Richard DangerNantes Université, CHU Nantes, Inserm, Centre de Recherche en Transplantation et Immunologie (CRTI), UMR 1064, ITUN, Nantes, France.ORCID 0000-0002-5058-795X
Quentin MoiteauxNantes Université, CHU Nantes, Inserm, Centre de Recherche en Transplantation et Immunologie (CRTI), UMR 1064, ITUN, Nantes, France.
Yodit FesehaNantes Université, CHU Nantes, Inserm, Centre de Recherche en Transplantation et Immunologie (CRTI), UMR 1064, ITUN, Nantes, France.
Estelle GeffardNantes Université, CHU Nantes, Inserm, Centre de Recherche en Transplantation et Immunologie (CRTI), UMR 1064, ITUN, Nantes, France.
Gérard RamsteinUniversité de Nantes, LS2N DUKe, UMR6004, Centrale Nantes, IMT Atlantique, INRIA and CNRS, Nantes, France.
Sophie BrouardNantes Université, CHU Nantes, Inserm, Centre de Recherche en Transplantation et Immunologie (CRTI), UMR 1064, ITUN, Nantes, France.
Inserm · FRÉcole Centrale de Nantes · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Web-based data analysis and visualization tools are mostly designed for specific purposes, such as the analysis of data from whole transcriptome RNA sequencing or single-cell RNA sequencing. However, generic tools designed for the analysis of common laboratory data for noncomputational scientists are also needed. The importance of such web-based tools is emphasized by the continuing increases in the sample capacity of conventional laboratory tools such as quantitative PCR, flow cytometry or ELISA instruments. We present a web-based application FaDA, developed with the R Shiny package that provides users with the ability to perform statistical group comparisons, including parametric and nonparametric tests, with multiple testing corrections suitable for most standard wet-laboratory analyses. FaDA provides data visualizations such as heatmaps, principal component analysis (PCA) plots, correlograms and receiver operating curves (ROCs). Calculations are performed through the R language. The FaDA application provides a free and intuitive interface that allows biologists without bioinformatic skill to easily and quickly perform common laboratory data analyses. The application is freely accessible at https://shiny-bird.univ-nantes.fr/app/Fada.

Indexed as

Data AnalysisInternetSoftwareData Interpretation, StatisticalDatasets as TopicData VisualizationFlow CytometryHumansKidney TransplantationLaboratories

Identifiers

PMID34928943
PMCPMC8687579
OpenAlexW4200149243

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.