MassIVE MSV000084110

Complete Public PXD014684

High-Throughput Single Cell Proteomics Enabled by Multiplex Isobaric Labeling in a Nanodroplet Sample Preparation Platform

Description

Single cell proteomics data from three murine cell lines (Raw, SVEC4-10, C10) and HeLa cell lysate. Samples were digested with trypsin and labeled with TMT 10-Plex on a small scale using nanoPOTS, followed by LC-MS/MS analysis. [doi:10.25345/C57D3Z] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: proteomics ; nanodroplet ; single cell

Contact

Principal Investigators:
(in alphabetical order)
Charles Ansong, Pacific Northwest National Laboratory, United States
Ying Zhu, Pacific Northwest National Laboratory, United States
Submitting User: alchemistmatt

Publications

Dou M, Clair G, Tsai CF, Xu K, Chrisler WB, Sontag RL, Zhao R, Moore RJ, Liu T, Paša-Toli? L, Smith RD, Shi T, Adkins JN, Qian WJ, Kelly RT, Ansong C, Zhu Y.
High-Throughput Single Cell Proteomics Enabled by Multiplex Isobaric Labelling in a Nanodroplet Sample Preparation Platform.
Anal. Chem. Epub 2019 Sep 11.

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Experimental Design
    Conditions:
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Identification Results
    Proteins (Human, Remapped):
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Quantification Results
    Differential Proteins:
    Quantified Proteins:
 
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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.

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Number of distinct biological replicates across all analyses (original submission and reanalyses) associated with this dataset.

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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.

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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 unmodified peptide sequences reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct peptide sequences (including modified variants or peptidoforms) reported across all analyses (original submission and reanalyses) associated with this dataset.

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Total number of peptide-spectrum matches (i.e. spectrum identifications) 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.