Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

ITRAq and TMTPro datasets Rescored with Prosit

ABSTRACT: Rescoring with Prosit predictions and percolator 6 different PRIDE submited datasets: 1- PXD017472 2- PXD017621 3- PXD002214 4- PXD021401 5- PXD027089 6- PXD024275

INSTRUMENT(S): Q Exactive HF

ORGANISM(S): Homo Sapiens (human) Mus Musculus (mouse)

SUBMITTER: Wassim Gabriel

LAB HEAD: Mathias Wilhelm

PROVIDER: PXD031575 | Pride | 2022-06-09

REPOSITORIES: Pride

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	180104_PTB_individuals_7iTRAQ_20ug_0mM.raw	Raw
	180104_PTB_individuals_7iTRAQ_20ug_1000mM.raw	Raw
	180104_PTB_individuals_7iTRAQ_20ug_100mM.raw	Raw
	180104_PTB_individuals_7iTRAQ_20ug_200mM.raw	Raw
	180104_PTB_individuals_7iTRAQ_20ug_20mM.raw	Raw

Items per page:

1 - 5 of 523

Similar Datasets

Human Breast Milk TMT labeled Rescored with Prosit

Project description:We Have human breast milk dataset in this project. We predict all spectra in the datasets via Prosit then rescore. We have 100% FDR maxquant search results, and using percolator we get 1%FDR filtered results with andromeda Scores and another with features extracted from Prosit predictions.

2022-05-26 | PXD030339 | Pride

Human Yeast Dilution TMT labelled Rescored with Prosit.

Project description:We Have a human yeast dilution dataset in this project. We predict all spectra in the datasets via Prosit then rescore. We have 100% FDR max quant search results using percolator. In addition, we get 1%FDR filtered results with andromeda Scores and another with features extracted from Prosit predictions.

2022-06-09 | PXD030340 | Pride

Pancreatic cell lines MS2/MS3 TMT labeled Rescored with Prosit

Project description:We Have a pancreas MS2/MS3 dataset in this project. We predict all spectra in the datasets via Prosit then rescore. We have 100% FDR maxquant search results, and using percolator we get 1%FDR filtered results with andromeda Scores and another with features extracted from Prosit predictions.

2022-06-09 | PXD030342 | Pride

Micro-flow LC-MS/MS Based Single Shot Proteomics

Project description:In this study, we systematically optimized the micro-flow LC-MS/MS system based ssDDA proteomics. Our results show that combination of 2 – 3 h gradient with prosit rescore method identified the highest number of proteins and peptides. There is no benefit to increase column length. A single 3 h run identified about 9,200 proteins from 50 µg of Arabidopsis protein digest. The micro-flow LC-MS/MS system based ssDDA proteomics can be widely used for routine proteomics analysis of large cohort samples.

2021-07-01 | PXD023587 | Pride

Deep learning boosts immunopeptidomics one mass spectrum at a time

Project description:Characterizing the human leukocyte antigen (HLA) bound ligandome by mass spectrometry (MS) holds great promise for developing vaccines and drugs for immune oncology. Still, the identification of such non-tryptic peptides presents substantial computational challenges. To address these, we synthesized >300,000 peptides within the ProteomeTools project representing HLA class I & II ligands and products of the proteases AspN and LysN and analyzed these by multi-modal LC-MS/MS. The resulting data enabled training of a single model using the deep learning framework Prosit that shows outstanding prediction accuracy of fragment ion spectra for tryptic and non-tryptic peptides. Applying Prosit demonstrates that the identification of HLA peptides can be improved by 50-300% on average, that proteasomal HLA peptide splicing may not exist and that additional neo-epitopes that elicit an immune response can be identified from patient tumors. Together, the provided peptides, spectra and computational tools substantially expand the scope of immunopeptidomics workflows.

2021-04-26 | PXD021398 | Pride

Comparision of Nano and Micro-flow LC-MS/MS Based Single Shot Proteomics

2021-07-01 | PXD024169 | Pride

Targeted analysis of alternative protein isoforms in the human hearts

Project description:Human heart lysates acquired commercially were digested and processed with shotgun proteomics and parallel reaction monitoring with the aid of predicted spectra from Prosit.

2022-05-19 | PXD020074 | Pride

MS²Rescore: Data-driven rescoring dramatically boosts immunopeptide identification rates

Project description:Immunopeptidomics aims to identify Major Histocompatibility Complex-presented peptides on every cell that can be used in anti-cancer vaccine development. However, existing immunopeptidomics data analysis pipelines suffer from the non-tryptic nature of immunopeptides, complicating their identification. Previously, peak intensity predictions by MS²PIP and retention time predictions by DeepLC, have been shown to improve tryptic peptide identifications when rescoring peptide-spectrum matches with Percolator. However, as MS²PIP was tailored towards tryptic peptides, we have here retrained MS²PIP to include non-tryptic peptides. Interestingly, the new models not only greatly improve predictions for immunopeptides, but also yield further improvements for tryptic peptides. We show that the integration of new MS²PIP models, DeepLC, and Percolator in one software package, MS²Rescore, increases spectrum identification rate and unique identified peptides with 46% and 36% compared to standard Percolator rescoring at 1% FDR. Moreover, MS²Rescore also outperforms the current state-of-the-art in immunopeptide-specific identification approaches. Integration of immunopeptide MS²PIP models, DeepLC, and Percolator into MS²Rescore thus allows substantial improved identification of novel epitopes from existing immunopeptidomics workflows.

2022-07-11 | PXD033868 | Pride

TMTpro-18plex: The Expanded and Complete Set of TMTpro Reagents for Sample Multiplexing

Project description:The development of the TMTpro-16plex series expanded the breadth of commercial isobaric tagging reagents by nearly 50% over classic TMT-11plex. In addition to the described 16plex reagents, the proline-based TMTpro molecule can accommodate two additional combinations of heavy carbon and nitrogen isotopes. Here, we introduce the final two labeling reagents, TMTpro-134C and TMTpro-135N, which permit the simultaneous global protein profiling of 18 samples with no missing values. For example, six conditions with three biological replicates can now be perfectly accommodated. We showcase the 18plex reagent set by profiling the proteome and phosphoproteome of a pair of isogenic breast cancer cell lines under three conditions in triplicate. We compare the depth and quantitative performance of this dataset with a TMTpro-16plex experiment in which two samples were omitted. Our analysis revealed similar numbers of quantified peptides and proteins, with high quantitative correlation. We interrogated further the TMTpro-18plex dataset by highlighting changes in protein abundance profiles under different conditions in the isogenic cell lines. We conclude that TMTpro-18plex further expands the sample multiplexing landscape, allowing for complex and innovative experimental designs.

2021-04-28 | PXD024275 | Pride

TAG-TMTpro, a hyperplexing quantitative approach for high-throughput proteomic studies

Project description:Isobaric labeling is the most widely used multiplexing quantitative approach in proteomic studies, enabling the comparison of up to 18 samples in a single MS analysis. Expanding the multiplexing capacity is of great necessity for high-throughput proteomic studies. Herein, we establish a novel TAG-TMTpro approach by introducing Ala or Gly residues to peptides prior to TMTpro labeling, which is able to triple the quantitative capacity of TMTpro. We systematically evaluated the Boc-Ala-OSu and Boc-Gly-OSu reaction and optimized the conditions for labeling, side-product elimination and Boc deprotection. We validated the identification and quantification performance using E. coli and HeLa cell lysates. We demonstrated that the TAG-TMTpro approach resulted in good identification reproducibility and reliable quantitative accuracy. The TAG-TMTpro is able to triple the multiplexing capacity of TMTpro reagents, and is a versatile quantitative approach for high-throughput proteomic studies.

2022-10-14 | PXD033711 | Pride

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data