Evidence map›Paper›PMID 36879900›Full record

ArticleNAR genomics and bioinformatics2023

SelectBCM tool: a batch evaluation framework to select the most appropriate batch-correction methods for bulk transcriptome analysis.

Madhulika Mishra, Lucas Barck, Pablo Moreno, Guillaume Heger, Yuyao Song, Janet M Thornton, Irene Papatheodorou

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In one paragraph

Article in NAR genomics and bioinformatics, 2023. 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 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

5 · Who and what money

Authors and funding

7 authors.

Madhulika MishraEuropean Molecular Biology Laboratory, European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.ORCID https://orcid.org/0000-0001-7133-4743
Lucas BarckEuropean Molecular Biology Laboratory, European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.
Pablo MorenoEuropean Molecular Biology Laboratory, European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.ORCID https://orcid.org/0000-0002-9856-1679
Guillaume HegerEuropean Molecular Biology Laboratory, European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.ORCID https://orcid.org/0000-0003-4175-133X
Yuyao SongEuropean Molecular Biology Laboratory, European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.
Janet M ThorntonEuropean Molecular Biology Laboratory, European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.
Irene PapatheodorouEuropean Molecular Biology Laboratory, European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.ORCID https://orcid.org/0000-0001-7270-5470

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bulk transcriptomes are an essential data resource for understanding basic and disease biology. However, integrating information from different experiments remains challenging because of the batch effect generated by various technological and biological variations in the transcriptome. Numerous batch-correction methods to deal with this batch effect have been developed in the past. However, a user-friendly workflow to select the most appropriate batch-correction method for the given set of experiments is still missing. We present the SelectBCM tool that prioritizes the most appropriate batch-correction method for a given set of bulk transcriptomic experiments, improving biological clustering and gene differential expression analysis. We demonstrate the applicability of the SelectBCM tool on analyses of real data for two common diseases, rheumatoid arthritis and osteoarthritis, and one example to characterize a biological state, where we performed a meta-analysis of the macrophage activation state. The R package is available at https://github.com/ebi-gene-expression-group/selectBCM.

Identifiers

PMID36879900
PMCPMC9985330

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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.