MassIVE MSV000096605

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GNPS - FluoroMatch IM: An Interactive Software Leveraging Homologous Series and CCS Matching for PFAS Analysis by Ion Mobility Spectrometry

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Description

This is a dataset that containing raw .d files analyzed in the following manuscript. FluoroMatch IM An Interactive Software for PFAS Analysis by Ion Mobility Spectrometry Abstract. Per- and polyfluoroalkyl substances (PFASs) are often present as complex mixtures at trace levels in environmental samples, posing difficulties for analytical chemists. Ion mobility offers highly replicable identifiers, enabling the use of community-based libraries for PFAS annotation in non-targeted analysis. Currently, limited software exists to leverage the capabilities of liquid chromatography ion mobility high resolution mass spectrometry (LC-IM-HRMS) for non-targeted PFAS analysis. FluoroMatch IM is a vendor neutral tool for rapid annotation of LC-IM-HRMS datasets. Annotation algorithms include CCS matching, formula prediction, homologous series detection, mass defect filtering, and accurate mass matching with a database of 194 PFAS ions which can continuously be expanded by the community. Results from FluoroMatch IM were compared to a targeted approach with a laboratory-prepared mix of 63 PFASs and real wastewater samples. FluoroMatch IM revealed additional likely PFASs (n is 3) while confirming most targeted annotations (9/10). Validation of the standard mix showed a low false negative rate of 5 percent and a 0 percent false positive rate for features included in the CCS library. This study demonstrates the promise of FluoroMatch IM for streamlining PFAS analysis workflows and maintaining accuracy in non-targeted analysis. [doi:10.25345/C5DZ03D3Z] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: PFAS ; HRMS ; ion mobility ; software ; FluoroMatch ; DatasetType:Metabolomics ; DatasetType:Other (PFAS)

Contact

Principal Investigators:
(in alphabetical order) 		Carrie A McDonough, Carnegie Mellon University, United States
Jeremy P Koelmel, Yale University, United States
Krystal J Godri Pollitt, Yale University, United States
Rachel Smolinski, Carnegie Mellon University, United States
Submitting User: jeremykoelmel
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Experimental Design
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Identification Results
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Quantification Results
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GNPS content goes here (MSV000096605 [task=37fd1c9a47704267a7a9de27e1d626f1])
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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.

"N/A" means no results of this type were submitted.
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.

"N/A" means no results of this type were submitted.
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.

"N/A" means no results of this type were submitted.
Originally identified proteins that were automatically remapped by MassIVE to proteins in the SwissProt human reference database.

"N/A" means no results of this type were submitted.
Number of distinct protein accessions reported across all analyses (original submission and reanalyses) associated with this dataset.

"N/A" means no results of this type were submitted.
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.

"N/A" means no results of this type were submitted.
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.