The CPTAC Data Coordinating Center houses proteomic datasets from CPTAC studies in its public data portal and assay portal. It analyzes data through a common pipeline and enables high-speed access. The Proteomic Data Commons is being developed to provide unified access to mass spectrometry data from multiple sources and allow analysis tools to access data in the cloud. It currently hosts data from CPTAC studies and is working to integrate with other cancer research data clouds. The goal is to improve data sharing, reuse and reproducibility across proteomic studies.

1. CPTAC Data Portal & Proteomic Data Commons
Imaging SIG
July 1, 2019
Ratna Rajesh Thangudu, Ph.D.

2. Outline
• CPTAC Data Coordinating Center
• Proteomic Data Commons

3. CPTAC Data Coordinating Center
CPTAC Public Portal (https://proteomics.cancer.gov/data-portal)
• A centralized repository for the public dissemination of CPTAC proteomic datasets
• Analyze all of the CPTAC data through a Common Data Analysis Pipeline (CDAP) for public release
• Enable high speed transfer through UDP technology (Aspera)
• Provide support to the user community
CPTAC Assay Portal (https://proteomics.cancer.gov/assay-portal)
• The CPTAC Assay Portal serves as a centralized public repository of "fit-for-purpose," multiplexed quantitative
mass spectrometry-based proteomic targeted assays.

4. CPTAC Public Data Portal
https://proteomics.cancer.gov/data-portal

5. CPTAC Public Data Portal

6. CPTAC Data Portal: Releases

7. CPTAC Data Portal: Releases

8. CPTAC Data Portal: Releases

9. CPTAC Data Portal: Releases

10. Outline
• CPTAC Data Coordinating Center
• Proteomic Data Commons

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Proteomics Data
Commons (PDC)

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Proteomics Data Commons: High Level Goals
 Unsilo mass spectrometry data. Bring data into a common location
that satisfy Findability, Accessibility, Interoperability and Reusability
 Move from a situation where people move data to local tools to where
people move their tools to the data.
 Shift from a ‘data graveyard model’ to a ‘data workspace model’
 Make it feasible for pipelines to be released with data during
publication to improve reproducibility
 Improve meta-data annotations. Ensure data is annotated well using
common vocabularies but that the process is non-onerous.

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https://pdc.esacinc.com
Proteomic Data Commons:
now available as beta program
 Open to all users, no login required
 Enabled deep linking to connect
from CPTAC data portal
 Released UCEC and CCRCC
datasets from CPTAC3 program.
 Preparing to accept data from
APOLLO, ICPC, etc

14. PDC: Cloud architecture

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PDC: Data Model & Dictionary
• cancer Data Standards Registry and Repository (caDSR)
• NCI Thesaurus (NCIt)
• PSI MS Controlled Vocabularies and data formats

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Proteomics Data Commons: Common Data Analysis Pipeline

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PDC: Browse Data
The data,
including protein
expression data,
can be browsed
interactively using
a series of filters
and accessed by
API.

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PDC: Gene Summary

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PDC: Proteogenomic Integration

20. PDC: Workspace
• Private user data
repository
• Data submission
portal
• Environment for
analysis workflows.

21. PDC: Interoperability with CRDC
Source: CRDC DCF
Cloud Resources
- SBG CGC
- Broad FireCloud
- ISB CGC
Provide ability to access and stream data from across the CRDC resources with a single sign-on

22. Proteogenomics Across the CRDC
Ruggles et al. 2017, MCP 16(6) 959-981
Run full proteogenomic
pipelines using data
stored in the Commons

23. Data subtype File type Access
MS spectra .raw, mzmL Open
Peptide-spectrum
match
raw PSM,
.mzIdentmL
Open
Protein report .tsv Open
Genome-derived
protein sequence
FASTA Controlled
PDC: Controlled Access Data
Upcoming feature

24. PDC: Application Programming Interface

25. Jupyter Notebook Example
Get the TMT ratio data
Get the clinical metadata

26. Summary
 The PDC is being developed as a resource for democratized proteomics
data (MS and harmonized processed data plus rich metadata)
 Current public datasets are from CPTAC, others to follow
 The first full-release product will have both a portal and workspace
 Tool integration is underway with the NCI Cloud Resource partners
 It is currently under active development, with limited features available
 Community feedback is being actively solicited – please send your
thoughts
nci.pdc.help@esacinc.com

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Feedback: nci.pdc.help@esacinc.com

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Acknowledgements
ESAC, Inc
 Rajesh Thangudu
 Anand Basu
 Michael Holck
 Deepak Singhal
 Karen Ketchum
 Lei Ma
 Maya Zuhl
 Yi Xin
 Padimini Chilappagari
 Ngoc Nguyen
University of Washington
 Michael MacCoss
Spectragen Informatics
 Paul Rudnick
Georgetwon University
 Nathan Edwards
NCI
▪ Chris Kinsinger
▪ Erika Kim
▪ Tara Hiltke
Scientific Advisory Committee
▪ Nuno Bandeira – UCSD
▪ Tony Blau - UW
▪ David Fenyo - NYU
▪ Brad Gibson - Amgen
▪ Jake Jaffe – Broad
▪ Mark Musen - Stanford
▪ Michael Noble – Broad
▪ Sam Payne - PNNL
▪ Adam Resnick - CHOP
▪ Dan Spellman - Merck
Feedback : nci.pdc.help@esacinc.com