Evidence map›Paper›PMID 30510204›Full record

ArticleNature communications2018

Chromatogram libraries improve peptide detection and quantification by data independent acquisition mass spectrometry.

Brian C Searle, Lindsay K Pino, Jarrett D Egertson, Ying S Ting, Robert T Lawrence, Brendan X MacLean, Judit Villén, Michael J MacCoss

Abstract read
In one paragraph

Article in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 339 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
339citing 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

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

  1. Pooled it
  2. Trial
  3. Preprocessing Large-Scale Proteomics Data.Methods in molecular biology (Clifton, N.J.) · 2027
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279 more citing papers are in PubMed but not listed here.

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

8 authors.

Brian C SearleDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.
Lindsay K PinoDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.
Jarrett D EgertsonDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.
Ying S TingDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.ORCID http://orcid.org/0000-0003-2492-3718
Robert T LawrenceDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.
Brendan X MacLeanDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.
Judit VillénDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.
Michael J MacCossDepartment of Genome Sciences, University of Washington, Seattle, WA, USA. maccoss@uw.edu.ORCID http://orcid.org/0000-0003-1853-0256

Funding

TrainingP41GM103533 · NIGMS · UNIVERSITY OF WASHINGTON · PI MACCOSS, MICHAEL · 2012 to 2021
$20.7M
There and Back Again: Epigenetic Reinforcement of Cellular Signaling States - OverallU54HG008097 · NHGRI · BROAD INSTITUTE, INC. · PI JAFFE, JACOB DAVID · 2014 to 2019
$9.3M
Emergent properties of signaling network degradation that mediate homeostatic failure during agingR01AG056359 · NIA · UNIVERSITY OF WASHINGTON · PI KAEBERLEIN, MATT, VILLEN, JUDIT · 2017 to 2021
$2.9M
Towards a comprehensive roadmap of cellular signaling.R35GM119536 · NIGMS · UNIVERSITY OF WASHINGTON · PI VILLEN, JUDIT · 2016 to 2020
$2.2M
Systematic and Comprehensive Sampling of Peptides in Mixtures by Tandem Mass SpectrometryR21CA192983 · NCI · UNIVERSITY OF WASHINGTON · PI MACCOSS, MICHAEL · 2015 to 2017
$648k
Molecular phenotyping of the yeast replicative life span response to genetic and environmental modulatorsF31AG055257 · NIA · UNIVERSITY OF WASHINGTON · PI PINO, LINDSAY K · 2016 to 2018
$119k
Methods to elucidate quantitative phosphorylation dynamics in the IGF-1 signaling pathwayF31GM119273 · NIGMS · UNIVERSITY OF WASHINGTON · PI SEARLE, BRIAN CHIH-SENG · 2017 to 2018
$57k
NCI NIH HHS R21 CA192983NHGRI NIH HHS U54 HG008097NIA NIH HHS F31 AG055257NIA NIH HHS R01 AG056359NIGMS NIH HHS F31 GM119273NIGMS NIH HHS P41 GM103533NIGMS NIH HHS R35 GM119536
6 · The paper itself

Abstract

Data independent acquisition (DIA) mass spectrometry is a powerful technique that is improving the reproducibility and throughput of proteomics studies. Here, we introduce an experimental workflow that uses this technique to construct chromatogram libraries that capture fragment ion chromatographic peak shape and retention time for every detectable peptide in a proteomics experiment. These coordinates calibrate protein databases or spectrum libraries to a specific mass spectrometer and chromatography setup, facilitating DIA-only pipelines and the reuse of global resource libraries. We also present EncyclopeDIA, a software tool for generating and searching chromatogram libraries, and demonstrate the performance of our workflow by quantifying proteins in human and yeast cells. We find that by exploiting calibrated retention time and fragmentation specificity in chromatogram libraries, EncyclopeDIA can detect 20-25% more peptides from DIA experiments than with data dependent acquisition-based spectrum libraries alone.

Indexed as

AlgorithmsChromatography, LiquidDatabases, ProteinHeLa CellsHumansPeptidesProteomeProteomicsReproducibility of ResultsSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsTandem Mass SpectrometryPeptidesProteomeSaccharomyces cerevisiae Proteins

Identifiers

PMID30510204
PMCPMC6277451

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.