MassIVE MSV000088849

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GNPS DEIMoS: an open-source tool for processing high-dimensional mass spectrometry data

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Description

LC-IMS-MS/MS data from a large study of human plasma samples consisting of 40 quality control samples from the NIST Standard Reference Material 1950 and 112 study samples. An internal standard mixture consisting of D4-malonic acid, D4-succinic acid, D5-glycine, D4-citric acid, 13C6-fructose, D5-L-tryptophan, D4-lysine, D7-alanine, D35-stearic acid, D5-benzoic acid, and D15-octanoic acid was added prior to extraction. Each sample was spiked with 50 uL of a solution of the internal standards at 0.166 mg/mL in water. Metabolites and lipids were extracted with concomitant protein precipitation using the Matyash protocol. The metabolite layer was removed and dried in vacuo. Lipid and protein layers were not analyzed. An Agilent 1260 Infinity II high flow liquid chromatography system was used to inject and chromatographically separate samples prior to introduction to the ion mobility spectrometry-mass spectrometry instrument. A steady flowrate of 0.300 mL/min was delivered through a Millipore-Sigma SeQuant Zic-pHILIC column (15 cm length, 2.1 mm inner diameter, packed with 5 um particles). Ion mobility spectrometry-tandem mass spectrometry analysis was performed using an Agilent 6560 Ion Mobility LC/Q-TOF system. Spectra were acquired separately in both positive and negative ionization modes. Fixed collision energies were employed at 10, 20, and 40 eV on alternating frames. [doi:10.25345/C5C58P] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: human plasma ; liquid chromatography ; ion mobility spectrometry ; tandem mass spectrometry

Contact

Principal Investigators:
(in alphabetical order) 		Thomas O. Metz, Pacific Northwest National Laboratory, USA
Submitting User: alchemistmatt

Publications

Colby SM, Chang CH, Bade JL, Nunez JR, Blumer MR, Orton DJ, Bloodsworth KJ, Nakayasu ES, Smith RD, Ibrahim YM, Renslow RS, Metz TO.
DEIMoS: An Open-Source Tool for Processing High-Dimensional Mass Spectrometry Data.
Anal Chem. 2022 Apr 26;94(16):6130-6138. Epub 2022 Apr 17.

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GNPS content goes here (MSV000088849 [task=a407f040a3d3422d94b1dde95fc0178c])
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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.

Distinct replicate labels are counted across all files submitted in the "Metadata" category having a "BioReplicate" or "Replicate" column in 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.