Evidence map›Paper›PMID 38632081›Full record

ArticleBioinformatics (Oxford, England)2024

Peptide set test: a peptide-centric strategy to infer differentially expressed proteins.

Junmin Wang, Steven Novick

Open access · goldAbstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2024. 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
0.7field-weighted citation impact, top 36% of its field
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, 3 citations in OpenAlex.

  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 at 2 institutions in 1 country.

Junmin WangData Sciences and Quantitative Biology, Discovery Sciences, Biopharmaceuticals R&D, AstraZeneca, Gaithersburg, MD 20878, United States.ORCID 0009-0004-3728-9538
Steven NovickGlobal Statistical Sciences, Eli Lilly, Indianapolis, IN 46285, United States.
AstraZeneca (United States) · USEli Lilly (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

motivationThe clinical translation of mass spectrometry-based proteomics has been challenging due to limited statistical power caused by large technical variability and inter-patient heterogeneity. Bottom-up proteomics provides an indirect measurement of proteins through digested peptides. This raises the question whether peptide measurements can be used directly to better distinguish differentially expressed proteins.

resultsWe present a novel method called the peptide set test, which detects coordinated changes in the expression of peptides originating from the same protein and compares them to the rest of the peptidome. Applying our method to data from a published spike-in experiment and simulations demonstrates improved sensitivity without compromising precision, compared to aggregation-based approaches. Additionally, applying the peptide set test to compare the tumor proteomes of tamoxifen-sensitive and tamoxifen-resistant breast cancer patients reveals significant alterations in peptide levels of collagen XII, suggesting an association between collagen XII-mediated matrix reassembly and tamoxifen resistance. Our study establishes the peptide set test as a powerful peptide-centric strategy to infer differential expression in proteomics studies. AVAILABILITY AND IMPLEMENTATION: Peptide set test (PepSetTest) is publicly available at https://github.com/JmWangBio/PepSetTest.

Indexed as

Breast NeoplasmsPeptidesProteomicsFemaleHumansProteomeTamoxifenPeptidesProteomeTamoxifen

Identifiers

PMID38632081
PMCPMC11074007
OpenAlexW4394921477

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.