Evidence map›Paper›PMID 34055134›Full record

ArticleStatistics and its interface2020

Meta-analysis of peptides to detect protein significance.

Yuping Zhang, Zhengqing Ouyang, Wei-Jun Qian, Richard D Smith, Wing Hung Wong, Ronald W Davis

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Statistics and its interface, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 93% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

6 authors at 1 institution in 1 country.

Yuping ZhangDepartment of Statistics, University of Connecticut, Storrs, Connecticut 06269, USA.ORCID 0000-0001-8986-0354
Zhengqing OuyangDepartment of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts, Amherst, Massachusetts 01003, USA.
Wei-Jun QianBiological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352, USA.
Richard D SmithBiological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352, USA.
Wing Hung WongDepartment of Statistics, Stanford University, Stanford, California 94305, USA.
Ronald W DavisStanford Genome Technology Center, Stanford University, Palo Alto, California 94306, USA.
Stanford University · US

Funding

Inflammation and the Response to InjuryU54GM062119 · NIGMS · MASSACHUSETTS GENERAL HOSPITAL · PI TOMPKINS, RONALD GARY · 2001 to 2010
$78.6M
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
NIGMS NIH HHS P41 GM103493NIGMS NIH HHS U54 GM062119
6 · The paper itself

Abstract

Shotgun assays are widely used in biotechnologies to characterize large molecules, which are hard to be measured as a whole directly. For instance, in Liquid Chromatography - Mass Spectrometry (LC-MS) shotgun experiments, proteins in biological samples are digested into peptides, and then peptides are separated and measured. However, in proteomics study, investigators are usually interested in the performance of the whole proteins instead of those peptide fragments. In light of meta-analysis, we propose an adaptive thresholding method to select informative peptides, and combine peptide-level models to protein-level analysis. The meta-analysis procedure and modeling rationale can be adapted to data analysis of other types of shotgun assays.

Indexed as

Adaptive thresholdingMeta-analysisShotgun technology

Identifiers

PMID34055134
PMCPMC8162183
OpenAlexW3046621657

What OpenQuestion holds

Textmetadata
LicenceTDM
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.