Evidence map›Paper›PMID 36138825›Full record

ArticleBiology2022

BioTEA: Containerized Methods of Analysis for Microarray-Based Transcriptomics Data.

Luca Visentin, Giorgia Scarpellino, Giorgia Chinigò, Luca Munaron, Federico Alessandro Ruffinatti

Abstract read
In one paragraph

Article in Biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

5 authors.

Luca VisentinDepartment of Life Sciences and Systems Biology, University of Turin, 10123 Turin, Italy.ORCID 0000-0003-2568-5694
Giorgia ScarpellinoDepartment of Life Sciences and Systems Biology, University of Turin, 10123 Turin, Italy.ORCID 0000-0003-1673-6146
Giorgia ChinigòDepartment of Life Sciences and Systems Biology, University of Turin, 10123 Turin, Italy.
Luca MunaronDepartment of Life Sciences and Systems Biology, University of Turin, 10123 Turin, Italy.ORCID 0000-0001-9247-4446
Federico Alessandro RuffinattiDepartment of Life Sciences and Systems Biology, University of Turin, 10123 Turin, Italy.ORCID 0000-0002-3084-0380

Funding

Governo Italiano 20174TB8KWUniversity of Turin Bando Finanziamenti alla Ricerca di Ateneo ex 60%
6 · The paper itself

Abstract

Tens of thousands of gene expression data sets describing a variety of model organisms in many different pathophysiological conditions are currently stored in publicly available databases such as the Gene Expression Omnibus (GEO) and ArrayExpress (AE). As microarray technology is giving way to RNA-seq, it becomes strategic to develop high-level tools of analysis to preserve access to this huge amount of information through the most sophisticated methods of data preparation and processing developed over the years, while ensuring, at the same time, the reproducibility of the results. To meet this need, here we present bioTEA (biological Transcript Expression Analyzer), a novel software tool that combines ease of use with the versatility and power of an R/Bioconductor-based differential expression analysis, starting from raw data retrieval and preparation to gene annotation. BioTEA is an R-coded pipeline, wrapped in a Python-based command line interface and containerized with Docker technology. The user can choose among multiple options-including gene filtering, batch effect handling, sample pairing, statistical test type-to adapt the algorithm flow to the structure of the particular data set. All these options are saved in a single text file, which can be easily shared between different laboratories to deterministically reproduce the results. In addition, a detailed log file provides accurate information about each step of the analysis. Overall, these features make bioTEA an invaluable tool for both bioinformaticians and wet-lab biologists interested in transcriptomics. BioTEA is free and open-source.

Indexed as

differential expressionmicroarrayreproducibilitytranscriptomics

Identifiers

PMID36138825
PMCPMC9495986

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.