MassIVE MSV000081024

Imported Reanalysis Dataset Public PXD002952

LFQbench enables a multi-centered benchmark study demonstrating robust proteomic label-free quantification

Description

The consistent and accurate quantification of proteins is a challenging task for mass spectrometry (MS)-based proteomics. SWATH-MS uses data-independent acquisition (DIA) for label-free quantification. Here we evaluated five software tools for processing SWATH-MS data: OpenSWATH, SWATH2.0, Skyline, Spectronaut, DIA-Umpire, in collaboration with the respective developers to ensure an optimal use of each tool. We analyzed data from hybrid proteome samples of defined quantitative composition acquired on two different MS instruments applying different SWATH isolation windows setups. Using the resulting high-complexity datasets we benchmarked precision and accuracy of quantification and evaluated identification performance, robustness and specificity of each software tool. To consistently evaluate the high complexity datasets, we developed the LFQbench R-package. LFQbench results enabled developers to improve their software tools, thereby underlining the value of the reference datasets for software development and benchmarking. All tools provided highly convergent identification and reliable quantification performance, underscoring their robustness for label-free quantitative proteomics. [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: SWATH-MS ; LFQ ; Benchmark ; LFQbench ; Controlled Mixture ; MassIVE.quant reviewed - Platinum

Contact

Principal Investigators:
(in alphabetical order)
Stefan Tenzer, Institute for Immunology, University Medical Center of the Johannes-Gutenberg University Mainz, Mainz, Germany, N/A
Submitting User: ccms

Publications

Navarro P, Kuharev J, Gillet LC, Bernhardt OM, MacLean B, Röst HL, Tate SA, Tsou CC, Reiter L, Distler U, Rosenberger G, Perez-Riverol Y, Nesvizhskii AI, Aebersold R, Tenzer S.
A multicenter study benchmarks software tools for label-free proteome quantification.
Nat. Biotechnol. 2016 Nov;34(11):1130-1136. Epub 2016 Oct 3.

Number of Files:
Total Size:
Spectra:
Subscribers:
 
Owner Reanalyses
Experimental Design
    Conditions:
    Biological Replicates:
    Technical Replicates:
 
Identification Results
    Proteins (Human, Remapped):
    Proteins (Reported):
    Peptides:
    Variant Peptides:
    PSMs:
 
Quantification Results
    Differential Proteins:
    Quantified Proteins:
 
Browse Dataset Files
 
FTP Download Link (click to copy):

- Dataset Reanalyses


+ Dataset History


Click here to queue conversion of this dataset's submitted spectrum files to open formats (e.g. mzML). This process may take some time.

When complete, the converted files will be available in the "ccms_peak" subdirectory of the dataset's FTP space (accessible via the "FTP Download" link to the right).
Number of distinct conditions across all analyses (original submission and reanalyses) associated with this dataset.

Distinct condition labels are counted across all files submitted in the "Metadata" category having a "Condition" column in this dataset.

"N/A" means no results of this type were submitted.
Number of distinct biological replicates across all analyses (original submission and reanalyses) associated with this dataset.

Distinct replicate labels are counted across all files submitted in the "Metadata" category having a "BioReplicate" or "Replicate" column in this dataset.

"N/A" means no results of this type were submitted.
Number of distinct technical replicates across all analyses (original submission and reanalyses) associated with this dataset.

The technical replicate count is defined as the maximum number of times any one distinct combination of condition and biological replicate was analyzed across all files submitted in the "Metadata" category. In the case of fractionated experiments, only the first fraction is considered.

"N/A" means no results of this type were submitted.
Originally identified proteins that were automatically remapped by MassIVE to proteins in the SwissProt human reference database.

"N/A" means no results of this type were submitted.
Number of distinct protein accessions reported across all analyses (original submission and reanalyses) associated with this dataset.

"N/A" means no results of this type were submitted.
Number of distinct unmodified peptide sequences reported across all analyses (original submission and reanalyses) associated with this dataset.

"N/A" means no results of this type were submitted.
Number of distinct peptide sequences (including modified variants or peptidoforms) reported across all analyses (original submission and reanalyses) associated with this dataset.

"N/A" means no results of this type were submitted.
Total number of peptide-spectrum matches (i.e. spectrum identifications) reported across all analyses (original submission and reanalyses) associated with this dataset.

"N/A" means no results of this type were submitted.
Number of distinct proteins quantified across all analyses (original submission and reanalyses) associated with this dataset.

Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

"N/A" means no results of this type were submitted.
Number of distinct proteins found to be differentially abundant in at least one comparison across all analyses (original submission and reanalyses) associated with this dataset.

A protein is differentially abundant if its change in abundance across conditions is found to be statistically significant with an adjusted p-value <= 0.05 and lists no issues associated with statistical tests for differential abundance.

Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

"N/A" means no results of this type were submitted.
This dataset may not contain all raw spectra data as originally deposited in PRIDE. It has been imported to MassIVE for reanalysis purposes, so its spectra data here may consist solely of processed peak lists suitable for reanalysis with most software.