MassIVE MSV000096401

Partial Public PXD057850

Benchmarking SILAC Proteomics Workflows and Data Analysis Platforms

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Description

Stable isotopic labeling by amino acids in cell culture (SILAC) is a powerful metabolic labeling technique with widespread applications and diverse study designs. SILAC proteomics requires the confident identification and quantification of complete isotopic versions of proteins and peptides during data acquisition and analysis. However, different SILAC workflows and data analysis platforms have not been comparatively evaluated. To fill this critical gap and provide practical user guidelines for SILAC proteomics data analysis, we designed a comprehensive benchmarking pipeline to evaluate different SILAC workflows and commonly used data analysis software. Ten different data analysis platforms were evaluated for static and dynamic SILAC labeling with both DDA and DIA methods. Both in-house generated and repository SILAC proteomics datasets were used for benchmarking with hundreds of raw data files from HeLa and neuron samples. We evaluated twelve performance metrics for SILAC proteomics including identification, quantification, accuracy, precision, reproducibility, filtering criteria, missing values, false discovery rate, protein half-life measurement, completeness, unique software features, and speed of data analysis. In summary, this study provided the first systematic evaluation of different SILAC data analysis platforms with practical guidelines to assist decision-making in SILAC proteomics study design and data analysis. [doi:10.25345/C5HT2GQ1W] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: Dynamic SILAC ; Neuron ; pulse SILAC ; dSILAC ; pSILAC ; Turnover ; Arg10 ; Lys8 ; DatasetType:Proteomics

Contact

Principal Investigators:
(in alphabetical order) 		Ling Hao, University of Maryland, USA
Submitting User: haolab
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Experimental Design
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Identification Results
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Quantification Results
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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.