MassIVE MSV000087701

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Bayesian proteoform modeling improves protein quantification of global proteomic measurements

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Description

Data used for the implementation of a Bayesian Proteoform Quantification model (BP-Quant) that uses statistically derived peptide signatures to identify peptides that are outside the dominant pattern, or the existence of multiple over-expressed patterns to improve relative protein abundance estimates. BP-Quant is available on GitHub as both MatLab and R packages: https://github.com/PNNL-Comp-Mass-Spec/BP-Quant Plasma samples collected from standard inbred mice were digested with trypsin then analyzed with an LTQ-Orbitrap Velos mass spectrometer. Data was searched with SEQUEST using PNNL's DMS processing pipeline. [doi:10.25345/C5SR88] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: Bayesian model ; quantification ; relative abundance

Contact

Principal Investigators:
(in alphabetical order) 		Katrina Waters, Pacific Northwest National Laboratory, USA
Richard Smith, Pacific Northwest National Laboratory, USA
Submitting User: alchemistmatt

Publications

Webb-Robertson BJ, Matzke MM, Datta S, Payne SH, Kang J, Bramer LM, Nicora CD, Shukla AK, Metz TO, Rodland KD, Smith RD, Tardiff MF, McDermott JE, Pounds JG, Waters KM.
Bayesian proteoform modeling improves protein quantification of global proteomic measurements.
Mol Cell Proteomics. 2014 Dec;13(12):3639-46.

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Quantification Results
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Originally identified proteins that were automatically remapped by MassIVE to proteins in the SwissProt human reference database.

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Number of distinct protein accessions reported across all analyses (original submission and reanalyses) associated with this dataset.

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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.

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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.