MassIVE MSV000084859

Imported Reanalysis Dataset Public PXD011691

Comparison of DIA and TMT based protein quantification in complex background

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Description

Label free quantification (LFQ) and isobaric labelling quantification (ILQ) are among the most popular protein quantification workflows in discovery proteomics. Here, we compared the TMT 10-plex workflow to label free single shot data-independent acquisition (DIA) method on a controlled sample set. The sample set consisted of ten samples derived from 10 different mouse cerebelli spiked with the UPS2 protein standard in five different concentrations. To match instrument time between the methods, the combined TMT sample was fractionated into ten fractions. The LC-MS data were acquired at two facilities to assess inter-laboratory reproducibility. Both methods resulted in a high proteome coverage (>5,000 proteins) with low missing values on protein level (<2%) The TMT workflow led to 15-20% more identified proteins and a slightly better quantitative precision whereas the quantitative accuracy was better for the DIA method. The quantitative performance was benchmarked by the number of true positives (UPS2 proteins) within the top 100 candidates. TMT and DIA performed similar. The quantitative performance of the DIA data could be even improved by searching them directly against a database instead of using a project specific library. Our experiments also demonstrated that both methods can be easily transferred between facilities. [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: DIA ; TMT ; Orbitrap Fusion Lumos ; MassIVE.quant reviewed - Platinum

Contact

Principal Investigators:
(in alphabetical order) 		Lukas Reiter, Biognosys AG, N/A
Submitting User: ccms

Publications

Muntel J, Kirkpatrick J, Bruderer R, Huang T, Vitek O, Ori A, Reiter L.
Comparison of Protein Quantification in a Complex Background by DIA and TMT Workflows with Fixed Instrument Time.
J. Proteome Res. 2019 Mar 1;18(3):1340-1351. Epub 2019 Feb 20.

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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.

"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.