Dataset Information

PROTEOFORMER 2.0: MS validation

ABSTRACT: PROTEOFORMER is a pipeline for generating a search space of candidate translation products based on ribosome profiling data. The pipeline was published in 2014, but since then, several features have been added. For this project, the PROTEOFORMER pipeline 2.0 was tested on human HCT116 and Jurkat cell ribosome profiling data with all its new features and then compared to raw MS data of both cell lines, validating its use as a proteogenomic tool. In this study, results of 3 proteoform calling methods were combined (classical PROTEOFORMER proteoform calling, PRICE and SPECtre). Afterwards, results were eventually combined with the canonical or splicing-included version of human UniProt. The different described combinations were exported as a FASTA file and used as search space for searching matching MS data.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Colon, Jurkat Cell

SUBMITTER: Steven Verbruggen

LAB HEAD: Gerben Menschaert

PROVIDER: PXD011353 | Pride | 2019-05-03

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	B001981_Ap_CMB-89_GevaertLab_ShotGun_HCT116_1.raw	Raw
	B001987_Ap_CMB-89_GevaertLab_ShotGun_Jurkat_1.raw	Raw
	B001991_Ap_CMB-89_GevaertLab_ShotGun_HCT116_2.raw	Raw
	B001995_Ap_CMB-89_GevaertLab_ShotGun_Jurkat_2.raw	Raw
	B002001_Ap_CMB-89_GevaertLab_ShotGun_Jurkat_3.raw	Raw

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Publications

Spectral Prediction Features as a Solution for the Search Space Size Problem in Proteogenomics.

Verbruggen Steven S Gessulat Siegfried S Gabriels Ralf R Matsaroki Anna A Van de Voorde Hendrik H Kuster Bernhard B Degroeve Sven S Martens Lennart L Van Criekinge Wim W Wilhelm Mathias M Menschaert Gerben G

Molecular & cellular proteomics : MCP 20210403

Proteogenomics approaches often struggle with the distinction between true and false peptide-to-spectrum matches as the database size enlarges. However, features extracted from tandem mass spectrometry intensity predictors can enhance the peptide identification rate and can provide extra confidence for peptide-to-spectrum matching in a proteogenomics context. To that end, features from the spectral intensity pattern predictors MS<sup>2</sup>PIP and Prosit were combined with the canonical scores ...[more]

PMID: 33823297

Publication: 1/2

Dataset Information

PROTEOFORMER 2.0: MS validation

Dataset's files

Publications

Spectral Prediction Features as a Solution for the Search Space Size Problem in Proteogenomics.

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