The proposal titled "TCGA Data Analysis Center at Berkeley" focuses on integrating data from The Cancer Genome Atlas (TCGA) and providing that integrated analysis to the community by timely computation and redistribution through the TCGA Data Coordinating Center. The proposal includes six key elements (1) quality control of TCGA data, (2) systematic classification of tumors by molecular data, (3) analysis and integration of histopathology images (H&E), (4) interpretation of gene expression data in the context of other molecular data, (5) identification of interacting genetic loci by aberration co-occurrence, and (6) creation of genetic influence diagrams. These analyses will be performed on the mutation, copy number, genotype, expression, methylation and miRNA analyses that are likely to be key components of TCGA. Data analyses will begin after a cohesive analytical strategy is developed in a design document that clearly lays out the process by which our group will receive, analyze, and redistribute information. Our proposal includes collaborators who are pathologists, cancer biologists, geneticists, genomicists, computer scientists, and statisticians who have a proven track record of working together on large projects.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Resource-Related Research Projects--Cooperative Agreements (U24)
Project #
5U24CA143799-04
Application #
8325456
Study Section
Special Emphasis Panel (ZCA1-SRLB-U (O1))
Program Officer
Yang, Liming
Project Start
2009-09-28
Project End
2014-07-31
Budget Start
2012-08-01
Budget End
2013-07-31
Support Year
4
Fiscal Year
2012
Total Cost
$646,044
Indirect Cost
$112,063
Name
Oregon Health and Science University
Department
Genetics
Type
Schools of Medicine
DUNS #
096997515
City
Portland
State
OR
Country
United States
Zip Code
97239
Kim, Su Yeon; Jacob, Laurent; Speed, Terence P (2014) Combining calls from multiple somatic mutation-callers. BMC Bioinformatics 15:154
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Cancer Genome Atlas Research Network (2014) Comprehensive molecular characterization of gastric adenocarcinoma. Nature 513:202-9
Cancer Genome Atlas Research Network (2014) Comprehensive molecular profiling of lung adenocarcinoma. Nature 511:543-50
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Kim, Su Yeon; Speed, Terence P (2013) Comparing somatic mutation-callers: beyond Venn diagrams. BMC Bioinformatics 14:189
Cancer Genome Atlas Research Network (2013) Comprehensive molecular characterization of clear cell renal cell carcinoma. Nature 499:43-9
Chang, Hang; Borowsky, Alexander; Spellman, Paul et al. (2013) Classification of Tumor Histology via Morphometric Context. Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit 2013:
Cancer Genome Atlas Research Network (2013) Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia. N Engl J Med 368:2059-74

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