Evidence map›Paper›PMID 32243168›Full record

ArticleJournal of proteome research2020

A Bayesian Null Interval Hypothesis Test Controls False Discovery Rates and Improves Sensitivity in Label-Free Quantitative Proteomics.

Robert J Millikin, Michael R Shortreed, Mark Scalf, Lloyd M Smith

Abstract read
In one paragraph

Article in Journal of proteome research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Fast, Free, and Flexible Peptide and Protein Quantification with FlashLFQ.Methods in molecular biology (Clifton, N.J.) · 2023
    Article
  5. Review
  6. Fused in sarcoma regulates DNA replication timing and kinetics.The Journal of biological chemistry · 2021
    Article
  7. 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

4 authors.

Robert J MillikinDepartment of Chemistry, University of Wisconsin, 1101 University Avenue, Madison, Wisconsin 53706, United States.ORCID 0000-0001-7440-3695
Michael R ShortreedDepartment of Chemistry, University of Wisconsin, 1101 University Avenue, Madison, Wisconsin 53706, United States.
Mark ScalfDepartment of Chemistry, University of Wisconsin, 1101 University Avenue, Madison, Wisconsin 53706, United States.
Lloyd M SmithDepartment of Chemistry, University of Wisconsin, 1101 University Avenue, Madison, Wisconsin 53706, United States.

Funding

Institutional Training in the Genomic SciencesT32HG002760 · NHGRI · UNIVERSITY OF WISCONSIN-MADISON · PI Qiongshi Lu · 2003 to 2026
$17.7M
Revealing Proteoforms: The Primary Effectors of Biological FunctionR35GM126914 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI Lloyd M Smith · 2018 to 2026
$6.2M
NHGRI NIH HHS T32 HG002760NIGMS NIH HHS R35 GM126914
6 · The paper itself

Abstract

Statistical significance tests are a common feature in quantitative proteomics workflows. The Student's

Indexed as

ProteomicsSoftwareBayes TheoremHumansProteinsWorkflowProteinsBayesian hypothesis testBayesian statisticslabel-free quantificationquantitative proteomicssoftware

Identifiers

PMID32243168
PMCPMC7294927

What OpenQuestion holds

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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.