Evidence map›Paper›PMID 41674572›Full record

ArticleiMetaOmics2025

A cautionary tale of batch corrections on confounded microbiome community profiles.

Alicia J Foxx, Adam R Rivers

Abstract read
In one paragraph

Article in iMetaOmics, 2025. 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.

Alicia J FoxxDepartment of Plant Biology and Conservation Northwestern University Evanston Illinois USA.ORCID https://orcid.org/0000-0001-5504-2986
Adam R RiversUnited States Department of Agriculture, Agricultural Research Service Genomics and Bioinformatics Research Unit Gainesville Florida USA.ORCID https://orcid.org/0000-0002-3703-834X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We use a case study of seed microbiomes to assess the performance of five batch effects correction algorithms (BECAs) (zero-mean centering (ZMC), Ratio-A, conditional quantile regression (ConQuR), partial least squares discriminant analysis (PLSDA), and weighted PLSDA on a confounded data set in which the covariate of interest (plant species) does not appear in all batches (studies). We show incomplete batch effects removal in all cases, which calls for careful application of and future work on BECAs.

Identifiers

PMID41674572
PMCPMC12806050

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.