Evidence map›Paper›PMID 32969222›Full record

ArticleJournal of proteome research2021

Importance of Block Randomization When Designing Proteomics Experiments.

Bram Burger, Marc Vaudel, Harald Barsnes

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of proteome research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 1 pooled it
–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

35 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  4. Preprocessing Large-Scale Proteomics Data.Methods in molecular biology (Clifton, N.J.) · 2027
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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

3 authors.

Bram BurgerComputational Biology Unit (CBU), Department of Informatics, University of Bergen, 5007 Bergen, Norway.ORCID 0000-0003-1093-1290
Marc VaudelDepartment of Clinical Sciences, University of Bergen, 5007 Bergen, Norway.ORCID 0000-0003-1179-9578
Harald BarsnesComputational Biology Unit (CBU), Department of Informatics, University of Bergen, 5007 Bergen, Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Randomization is used in experimental design to reduce the prevalence of unanticipated confounders. Complete randomization can however create imbalanced designs, for example, grouping all samples of the same condition in the same batch. Block randomization is an approach that can prevent severe imbalances in sample allocation with respect to both known and unknown confounders. This feature provides the reader with an introduction to blocking and randomization, and insights into how to effectively organize samples during experimental design, with special considerations with respect to proteomics.

Indexed as

ProteomicsResearch DesignRandom Allocationbatchesblockingexperimental designrandomizationsample handling

Identifiers

PMID32969222
PMCPMC7786377

What OpenQuestion holds

Textmetadata
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.