Proteomics

Dataset Information

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The landscape of protein expression in cancer based on public proteomics data


ABSTRACT: This project contains raw data, intermediate files and results used to create the integrated map of protein expression in human cancer (including data from cell lines and tumours). The map is based on joint reanalysis of 11 large-scale quantitative proteomics studies. The datasets were primarily retrieved from the PRIDE database, as well as MassIVE database and CPTAC data portal. The raw files were manually curated in order to capture mass spectrometry acquisition parameters, experimental design and sample characteristics. The raw files were jointly processed with MaxQuant computational platform using standard settings (see Data Processing Protocol). Due to size of the data, the processing was done in two batches denoted as “celllines” and “tumours” analysis. In total, using a 1% peptide spectrum match and protein false discovery rates, the analysis allowed identification of 21,580 protein groups in the cell lines dataset (MQ search results available in ‘txt-celllines’ folder), and 13,441 protein groups in the tumours dataset (MQ search results available in ‘txt-tumours’ folder).

INSTRUMENT(S): LTQ Orbitrap, Q Exactive

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Prostate Gland, Kidney Cancer Cell, Cecum Cancer Cell Line, Permanent Cell Line Cell, Prostate Cancer Cell, Renal Cancer Cell Line, Lymph Node, Blood Cancer Cell, Uterine Cervix, Ovary Cancer Cell Line, Brain Cancer Cell Line, Colorectal Cancer Cell Line, Liver Cancer Cell, Colonic Cancer Cell, Prostate Cancer Cell Line, Cervical Cancer Cell Line, Skin Cancer Cell, Bone Cancer Cell Line, Breast Cancer Cell Line, Breast Cancer Cell, Ovary Cancer Cell

DISEASE(S): Prostate Adenocarcinoma,Colon Cancer,Disease Free,Malignant Neoplasm Of Ovary,Breast Cancer

SUBMITTER: Andrew Jarnuczak  

LAB HEAD: Juan Antonio Vizcaíno

PROVIDER: PXD013455 | Pride | 2019-07-18

REPOSITORIES: Pride

Dataset's files

Source:
Action DRS
Bekker-Jensen_CellSystems_2017.zip Other
Coscia_NComms_2016.zip Other
Frejno_MolSysBiol_2017.zip Other
Geiger_MCP_2012.zip Other
Gholami_CellReports_2013.zip Other
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Publications


This study investigates the challenge of comprehensively cataloging the complete human proteome from a single-cell type using mass spectrometry (MS)-based shotgun proteomics. We modify a classical two-dimensional high-resolution reversed-phase peptide fractionation scheme and optimize a protocol that provides sufficient peak capacity to saturate the sequencing speed of modern MS instruments. This strategy enables the deepest proteome of a human single-cell type to date, with the HeLa proteome se  ...[more]

Publication: 1/11

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