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Targeted proteomic assays for quantitation of proteins identified by proteogenomic analysis of ovarian cancer
- Source :
- Scientific Data
- Publication Year :
- 2017
- Publisher :
- Springer Science and Business Media LLC, 2017.
-
Abstract
- Mass spectrometry (MS) based targeted proteomic methods such as selected reaction monitoring (SRM) are emerging as a promising tool for verification of candidate proteins in biological and biomedical applications. The Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute has investigated the standardization and analytical validation of the SRM assays and demonstrated robust analytical performance on different instruments across different laboratories. An Assay Portal has also been established by CPTAC to provide the research community a resource consisting of large sets of targeted MS-based assays, and a depository to share assays publicly. Herein, we report the development of 98 SRM assays that have been thoroughly characterized according to the CPTAC Assay Characterization Guidance Document; 37 of these passed all five experimental tests. The assays cover 70 proteins previously identified at the protein level in ovarian tumors. The experiments, methods and results for characterizing these SRM assays for their MS response, repeatability, selectivity, stability, and endogenous detection are described in detail. Data are available via PeptideAtlas, Panorama and the CPTAC Assay Portal.
- Subjects :
- 0301 basic medicine
Proteogenomic Analysis
Proteomics
Statistics and Probability
Data Descriptor
Proteomic analysis
Computational biology
Biology
Library and Information Sciences
Education
03 medical and health sciences
0302 clinical medicine
Ovarian cancer
Research community
medicine
Humans
Proteogenomics
Ovarian Neoplasms
Selected reaction monitoring
Protein level
medicine.disease
3. Good health
Computer Science Applications
030104 developmental biology
030220 oncology & carcinogenesis
Female
PeptideAtlas
Statistics, Probability and Uncertainty
Biomarkers
Information Systems
Subjects
Details
- Language :
- English
- ISSN :
- 20524463
- Volume :
- 4
- Database :
- OpenAIRE
- Journal :
- Scientific Data
- Accession number :
- edsair.doi.dedup.....241d3340846426a64728ec5d13b7066a
- Full Text :
- https://doi.org/10.1038/sdata.2017.91