MassIVE MSV000080775

Imported Reanalysis Dataset Public PXD001374

Label-free quantitative phosphoproteomics with novel pairwise abundance normalization reveals synergistic RAS and CIP2A signaling

Subscribe Comment Reanalyze Spectra Add Reanalysis

Description

Label-free quantification is a powerful method for studying cellular protein phosphorylation dynamics. However, whether current data normalization methods achieve sufficient accuracy has not been examined systematically. Here, we demonstrate that a large uni-directional shift in the phosphopeptide abundance distribution is problematic for global median centering and quantile-based normalizations and may mislead the biological conclusion from unlabeled phosphoproteome data. Instead, we present a novel normalization strategy, named pairwise normalization, which is based on adjusting phosphopeptide abundances measured before and after the enrichment. The superior performance of pairwise normalization was validated by statistical methods, western blotting analysis, and by bioinformatics analysis. In addition, we demonstrate that the choice of normalization method influences the downstream analyses of the data and perceived pathway activities. Furthermore, we demonstrate that the developed normalization method, combined with pathway analysis algorithms, revealed a novel biological synergism between Ras signalling and PP2A inhibition by CIP2A. [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: Phosphoproteomics ; LC-MS/MS ; HeLa ; Mascot ; SimSpectraST ; RAS ; CIP2A ; Okadaic acid

Contact

Principal Investigators:
(in alphabetical order) 		Susumu Y. Imanishi, Turku Centre for Biotechnology, University of Turku and �bo Akademi University, Finland, N/A
Submitting User: ccms

Publications

Kauko O, Laajala TD, Jumppanen M, Hintsanen P, Suni V, Haapaniemi P, Corthals G, Aittokallio T, Westermarck J, Imanishi SY.
Label-free quantitative phosphoproteomics with novel pairwise abundance normalization reveals synergistic RAS and CIP2A signaling.
Sci Rep. Epub 2015 Aug 17.

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):

Species

Instrument

Modifications

- 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.