MassIVE MSV000085878

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MetaboLights MTBLS462 - GNPS Lipid Data Analyzer: Novel lipid species and identification of regio-isomeric lipid species (HCD characterization and regioisomer detection)

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Description

Lipid Data Analyzer (LDA; http://genome.tugraz.at/lda2) provides automated and reliable annotation of lipid species and their molecular structures in high-throughput data from chromatography-coupled tandem mass spectrometry using embedded rule sets. Using various low- and high-resolution mass spectrometry instruments with several collision energies, the method's platform independence is proved. The software's reliability, flexibility, and ability to identify novel lipid molecular species may now render current state-of-the-art lipid libraries obsolete.

LDA identified several novel lipid molecular species and novel regio-isomeric species; we consider a lipid species as “novel” if it is neither present in LIPID MAPS Structure Database, ChEBI, CyberLipid, HMDB, nor YMDB. Where evidence relies on fragments of very small intensity, high resolution HCD mode was used for final characterization. These data are presented here (CID mode data can be found in MTBLS397 - both biological experiments for Orbitrap Velos CID). Moreover, we present in this study data showing the LDA's ability to distinguish regio-isomeric standards under certain chromatographic conditions.

Control experiment 1 assays for this study can be found in the MetaboLights study MTBLS394.
Control experiment 2 assays for this study can be found in the MetaboLights study MTBLS391.
Control experiment 3 assays for this study can be found in the MetaboLights study MTBLS398.
Murine liver lipidome experiment assays for this study can be found in the MetaboLights study MTBLS396.
LipidBlast benchmarking assays for this study can be found in the MetaboLights study MTBLS397.

Linked Studies:MTBLS391 MTBLS394 MTBLS396 MTBLS397 MTBLS398 [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: GNPS Metabolomics MetaboLights

Contact

Principal Investigators:
(in alphabetical order) 		J�rgen Hartler, Institute of Computational Biotechnology, Graz University of Technology, Petersgasse 14/V 8010 Graz, Austria
Submitting User: caceves
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Number of distinct biological 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.

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