ArticleBioinformatics advances2026
Covariate balanced allocation of samples to batches to mitigate the impacts of technical variability.
Article in Bioinformatics advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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.
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Who cites it
1 citing paper in PubMed.
- Consensus statement on mass spectrometry-based proteomic analysis of cardiac tissue.Nature cardiovascular research · 2026Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Motivation: Performing assays on large numbers of samples requires their analysis in distinct batches, which commonly affects the measurements made in a systematic way. Analytical approaches can correct for such batch effects, however for this to be possible the batch should not be confounded with either the independent variable or any covariates relevant to the analysis. Thus, how samples are distributed across batches influences subsequent analytic conclusions. Results: We present Availability and implementation:
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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.