Evidence map›Paper›PMID 24928210›Full record

ArticleBioinformatics (Oxford, England)2014

Detecting differential protein expression in large-scale population proteomics.

So Young Ryu, Wei-Jun Qian, David G Camp, Richard D Smith, Ronald G Tompkins, Ronald W Davis, Wenzhong Xiao

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Bioinformatics (Oxford, England), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 2 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

6 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Integrating Multiple Quantitative Proteomic Analyses Using MetaMSD.Methods in molecular biology (Clifton, N.J.) · 2023
    Pooled it
  3. Article
  4. Review
  5. Biodegradation of alkaline lignin byBiotechnology for biofuels · 2017
    Article
  6. Genomics of injury: The Glue Grant experience.The journal of trauma and acute care surgery · 2015
    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

7 authors.

So Young RyuStanford Genome Technology Center, Stanford University, Stanford, CA 94305, USA, Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99352, USA and Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA Stanford Genome Technology Center, Stanford University, Stanford, CA 94305, USA, Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99352, USA and Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.
Wei-Jun QianStanford Genome Technology Center, Stanford University, Stanford, CA 94305, USA, Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99352, USA and Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.
David G CampStanford Genome Technology Center, Stanford University, Stanford, CA 94305, USA, Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99352, USA and Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.
Richard D SmithStanford Genome Technology Center, Stanford University, Stanford, CA 94305, USA, Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99352, USA and Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.
Ronald G TompkinsStanford Genome Technology Center, Stanford University, Stanford, CA 94305, USA, Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99352, USA and Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.
Ronald W DavisStanford Genome Technology Center, Stanford University, Stanford, CA 94305, USA, Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99352, USA and Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.
Wenzhong XiaoStanford Genome Technology Center, Stanford University, Stanford, CA 94305, USA, Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99352, USA and Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA Stanford Genome Technology Center, Stanford University, Stanford, CA 94305, USA, Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99352, USA and Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.

Funding

Equipment Supplement Request for a Research Resource for Ultra-sensitive High Throughput ProteomicsP41GM103493 · NIGMS · BATTELLE PACIFIC NORTHWEST LABORATORIES · PI SMITH, RICHARD D · 2012 to 2022
$22.6M
TRAINING IN BURNS AND TRAUMA RESEARCHT32GM007035 · NIGMS · MASSACHUSETTS GENERAL HOSPITAL · PI TOMPKINS, RONALD GARY · 1985 to 2014
$3.5M
Bedside Genomics in Severe TraumaR01GM101401 · NIGMS · MASSACHUSETTS GENERAL HOSPITAL · PI TOMPKINS, RONALD GARY, XIAO, WENZHONG · 2012 to 2013
$826k
NIGMS NIH HHS P41 GM103493NIGMS NIH HHS P41-GM103493NIGMS NIH HHS R01 GM101401NIGMS NIH HHS R01-GM101401NIGMS NIH HHS T32 GM007035NIGMS NIH HHS T32-GM007035
6 · The paper itself

Abstract

motivationMass spectrometry (MS)-based high-throughput quantitative proteomics shows great potential in large-scale clinical biomarker studies, identifying and quantifying thousands of proteins in biological samples. However, there are unique challenges in analyzing the quantitative proteomics data. One issue is that the quantification of a given peptide is often missing in a subset of the experiments, especially for less abundant peptides. Another issue is that different MS experiments of the same study have significantly varying numbers of peptides quantified, which can result in more missing peptide abundances in an experiment that has a smaller total number of quantified peptides. To detect as many biomarker proteins as possible, it is necessary to develop bioinformatics methods that appropriately handle these challenges.

resultsWe propose a Significance Analysis for Large-scale Proteomics Studies (SALPS) that handles missing peptide intensity values caused by the two mechanisms mentioned above. Our model has a robust performance in both simulated data and proteomics data from a large clinical study. Because varying patients' sample qualities and deviating instrument performances are not avoidable for clinical studies performed over the course of several years, we believe that our approach will be useful to analyze large-scale clinical proteomics data. AVAILABILITY AND IMPLEMENTATION: R codes for SALPS are available at http://www.stanford.edu/%7eclairesr/software.html.

Indexed as

Gene Expression RegulationComputational BiologyComputer SimulationHumansMass SpectrometryPeptidesProteinsProteomeProteomicsPeptidesProteinsProteome

Identifiers

PMID24928210
PMCPMC4173009

What OpenQuestion holds

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Registered trials

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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.