MassIVE MSV000081039

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MetaboLights MTBLS293 - GNPS Metabolites from surface seawater collected in Narragansett Bay

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Description

This data set was downloaded from MetaboLights (http://www.ebi.ac.uk/metabolights/) accession number MTBLS293 Abstract:In aquatic environments, the production and consumption of organic compounds is directly tied to the metabolic potential of the in situ microbial community. The community’s metabolic potential can be assessed using metatranscriptomics, which is a measure of gene expression in the environment. More recently, advances in metabolomics deliver details on specific organic compounds found in the environment. While the integration of these two datasets is desirable, the vast data streams can hinder investigations into biological and chemical processes. Here, we use data in the Kyoto Encyclopedia of Genes and Genomes (KEGG) combined with K means clustering to jointly interrogate metabolomics and metatranscriptomics data collected from a coastal marine environment. Using KEGG allowed us to focus our analysis on genes and compounds connected by a defined biochemical reaction. The K means clustering provided an unbiased means to place metabolites and genes into groups based on their temporal variability. Each of the groups defined by the K means clustering contained both transcripts and metabolites, which emphasized the interconnected nature of these two datasets. While conceptually simple, this analysis allowed us to explore a tractable number of biochemical pathways within our data. Continued development of computational tools to analyze meta-omics data is a pressing need. The application of tools such as described here is an exciting step towards integrated multi-omics data analysis that can be used to address broad questions in biogeochemical cycling. [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: sea water

Contact

Principal Investigators:
(in alphabetical order) 		Longnecker, Woods Hole Oceanographic Institution, us
Submitting User: rsilva
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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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Originally identified proteins that were automatically remapped by MassIVE to proteins in the SwissProt human reference database.

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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.