MassIVE MSV000086878

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GNPS Metabolomics Workbench ST001642 - GNPS Lipidomics in high-risk subjects for the identification of integrated biomarker signatures of type 1 diabetes

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Description

We present the lipidome of plasma collected from high-risk type 1 diabetes subjects. The methyl tert-butyl ether (MTBE) method was used for lipid extraction, followed by high performance liquid chromatography (HPLC) tandem mass spectrometry (LC-MS/MS) using a Q Exactive Orbitrap mass spectrometer and an Accela 600 HPLC. Lipid species were identified and quantified by analyzing the raw files in LipidSearch 4.2. Further analysis was conducted using Graphpad Prism and Ingenuity Pathway Analysis (IPA). [doi:10.25345/C5S21Q] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: GNPS ; Metabolomics ; Metabolomics Workbench

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Principal Investigators:
(in alphabetical order) 		Sanjoy Bhattacharya, University of Miami, N/A
Submitting User: mwang87
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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.

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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.
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