Evidence map›Paper›PMID 26435129›Full record

ArticleMolecular & cellular proteomics : MCP2015

The 2012/2013 ABRF Proteomic Research Group Study: Assessing Longitudinal Intralaboratory Variability in Routine Peptide Liquid Chromatography Tandem Mass Spectrometry Analyses.

Keiryn L Bennett, Xia Wang, Cory E Bystrom, Matthew C Chambers, Tracy M Andacht, Larry J Dangott, Félix Elortza, John Leszyk, Henrik Molina, Robert L Moritz and 4 more

Abstract read
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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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

14 authors.

Keiryn L BennettFrom the ‡CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria; david.l.tabb@vanderbilt.edu kbennett@cemm.oeaw.ac.at maureen.bunger@gmail.com.
Xia Wang§University of Cincinnati, Department of Mathematical Sciences, University of Cincinnati, Cincinnati, Ohio, 45221-0025;
Cory E Bystrom¶Cleveland HeartLab, Inc., Research and Development, Cleveland HeartLab, Inc., Cleveland, Ohio, 44103;
Matthew C Chambers‖Vanderbilt University, Department of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee, 37232;
Tracy M Andacht**Centers for Disease Control and Prevention, Emergency Response Branch, Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, Georgia, 30341;
Larry J Dangott‡‡Texas A&M University, Department of Biochemistry & Biophysics, Texas A&M University, College Station, Texas, 77843;
Félix Elortza§§CIC bioGUNE, Centro de Investigacion Cooperativa en Biociencias, ProteoRed-ISCIII, Bilbao, Spain;
John Leszyk¶¶University of Massachusetts, Department of Biochemistry and Molecular Pharmacology Proteomics and Mass Spectrometry Facility, University of Massachusetts Medical School, Shrewsbury, Massachusetts, 01545;
Henrik Molina‖‖The Rockefeller University, Proteomics Resource Center, The Rockefeller University, New York, New York, 10065;
Robert L MoritzInstitute for Systems Biology, Seattle, Washington, 98109;
Brett S PhinneyUniversity of California, Davis, Proteomics Core, University of California-Davis Genome Center, Davis, California, 95616;
J Will ThompsonDuke University, Proteomics and Metabolomics Core Facility, Duke University Medical Center, Durham, North Carolina, 27708;
Maureen K BungerProteovations, LLC, RTP, North Carolina 27709 david.l.tabb@vanderbilt.edu kbennett@cemm.oeaw.ac.at maureen.bunger@gmail.com.
David L Tabb‖Vanderbilt University, Department of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee, 37232; david.l.tabb@vanderbilt.edu kbennett@cemm.oeaw.ac.at maureen.bunger@gmail.com.

Funding

Quantitative Systems BiologyP50GM076547 · NIGMS · INSTITUTE FOR SYSTEMS BIOLOGY · PI AITCHISON, JOHN D. · 2006 to 2016
$30.6M
Vanderbilt Proteome Characterization CenterU24CA159988 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI LIEBLER, DANIEL C · 2011 to 2016
$13.9M
Shortening the development cycle time of Trans Proteomic Pipeline tools with high performance computingR01GM087221 · NIGMS · INSTITUTE FOR SYSTEMS BIOLOGY · PI DEUTSCH, ERIC, MORITZ, ROBERT L · 2010 to 2021
$6.0M
NCI NIH HHS U24 CA159988NIGMS NIH HHS 2P50 GM076547NIGMS NIH HHS GM087221NIGMS NIH HHS P50 GM076547NIGMS NIH HHS R01 GM087221
6 · The paper itself

Abstract

Questions concerning longitudinal data quality and reproducibility of proteomic laboratories spurred the Protein Research Group of the Association of Biomolecular Resource Facilities (ABRF-PRG) to design a study to systematically assess the reproducibility of proteomic laboratories over an extended period of time. Developed as an open study, initially 64 participants were recruited from the broader mass spectrometry community to analyze provided aliquots of a six bovine protein tryptic digest mixture every month for a period of nine months. Data were uploaded to a central repository, and the operators answered an accompanying survey. Ultimately, 45 laboratories submitted a minimum of eight LC-MSMS raw data files collected in data-dependent acquisition (DDA) mode. No standard operating procedures were enforced; rather the participants were encouraged to analyze the samples according to usual practices in the laboratory. Unlike previous studies, this investigation was not designed to compare laboratories or instrument configuration, but rather to assess the temporal intralaboratory reproducibility. The outcome of the study was reassuring with 80% of the participating laboratories performing analyses at a medium to high level of reproducibility and quality over the 9-month period. For the groups that had one or more outlying experiments, the major contributing factor that correlated to the survey data was the performance of preventative maintenance prior to the LC-MSMS analyses. Thus, the Protein Research Group of the Association of Biomolecular Resource Facilities recommends that laboratories closely scrutinize the quality control data following such events. Additionally, improved quality control recording is imperative. This longitudinal study provides evidence that mass spectrometry-based proteomics is reproducible. When quality control measures are strictly adhered to, such reproducibility is comparable among many disparate groups. Data from the study are available via ProteomeXchange under the accession code PXD002114.

Indexed as

AnimalsCattleChromatography, LiquidHumansLaboratoriesLongitudinal StudiesPeptidesProteinsProteomicsQuality ControlReproducibility of ResultsSurveys and QuestionnairesTandem Mass SpectrometryPeptidesProteins

Identifiers

PMID26435129
PMCPMC4762617

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.