The goal of the Yale Center for Genome Analysis (YCGA) is to rapidly and cost-effectively bring state-of the- art genomic technologies within reach of largest possible number of cancer investigators. YCGA occupies 7,000 ft^ of newly constructed, custom-designed laboratory space and is well equipped with several microarray (Affymetrix, lllumina, Sequenom and NimbleGen) and high throughput sequencing (10 lllumina hiiSeqs, one each of PacBio RS, MiSeq and Ion Torrent) platforms. Sequencing operation is supported by 1000 CPU/core cluster and 2 PB data storage. All aspects of sequence data generation, including sample collection, library preparation, sequence data and billing are tracked using WikiLIMS system which is an online, flexible, scalable and password-protected database. YCGA staff from microarray, sequencing and bioinformatics sections will provide an extremely expert and highly dedicated team that will ensure the success of research goals of cancer investigators. The YCGA provides >30 genomic services including: 1) gene expression and whole transcriptome analysis, 2) SNP genotyping and copy number variation, 3) whole-exome and whole-genome sequence analysis, 4) analysis of formalin-fixed paraffin embedded tissue, 5) methylation analysis, 6) miRNA analysis and discovery and 7) chromatin immunoprecipitation to study protein-DNA interactions. Together, the microarray and HT sequencing technologies of YCGA offer comprehensive support to study genetic events in cancer, which has the potential to aid in identification of genetic and biochemical causes of the disease, develop better diagnostic methods, and improve therapeutic outcomes and patient care. Strengths of this application include the extensive expertise, infrastructure, and instrumentation in the YCGA;the experience of PI in overseeing the recent U54-suported Yale Centre for Mendelian Disorder;a strong publication record and the experience of YCGA at providing state-of-the-art microarray, HT sequencing, biostatistical/bioinformatics and other technologies on a service charge basis to several Yale and non-Yale investigators. In addition to providing genomic services, the YCGA staff will consult as needed on experimental design, data interpretation, manuscript preparation, and grant application preparation, and will provide training for primary data analysis to YCC members. During FY 2012, 72 YCC investigators using YCGA Resource services accounted for 49% of the 20,148 provided services.

Public Health Relevance

The Yale Center for Genome Analysis provides cancer investigators a state-of-the-art centralized facility required for carrying out large-scale genomic analyses that would not otherwise be possible in their own laboratories. The genomic data generated at the YCGA is helping cancer scientists to better understand the genetic basis of cancer that will ultimately lead to new approaches for cancer treatment and prevention.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Center Core Grants (P30)
Project #
Application #
Study Section
Subcommittee G - Education (NCI)
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Yale University
New Haven
United States
Zip Code
Wang, Shi-Yi; Hsu, Sylvia H; Huang, Siwan et al. (2018) Regional Practice Patterns and Racial/Ethnic Differences in Intensity of End-of-Life Care. Health Serv Res 53:4291-4309
Gettinger, S N; Choi, J; Mani, N et al. (2018) A dormant TIL phenotype defines non-small cell lung carcinomas sensitive to immune checkpoint blockers. Nat Commun 9:3196
Liu, Huafeng; Li, Xin; Hu, Li et al. (2018) A crucial role of the PD-1H coinhibitory receptor in suppressing experimental asthma. Cell Mol Immunol 15:838-845
Altwerger, Gary; Bonazzoli, Elena; Bellone, Stefania et al. (2018) In Vitro and In Vivo Activity of IMGN853, an Antibody-Drug Conjugate Targeting Folate Receptor Alpha Linked to DM4, in Biologically Aggressive Endometrial Cancers. Mol Cancer Ther 17:1003-1011
Sanmamed, Miguel F; Chen, Lieping (2018) A Paradigm Shift in Cancer Immunotherapy: From Enhancement to Normalization. Cell 175:313-326
Gupta, Swati; Mani, Navin R; Carvajal-Hausdorf, Daniel E et al. (2018) Macrodissection prior to closed system RT-qPCR is not necessary for estrogen receptor and HER2 concordance with IHC/FISH in breast cancer. Lab Invest 98:1076-1083
Bellone, Stefania; Buza, Natalia; Choi, Jungmin et al. (2018) Exceptional Response to Pembrolizumab in a Metastatic, Chemotherapy/Radiation-Resistant Ovarian Cancer Patient Harboring a PD-L1-Genetic Rearrangement. Clin Cancer Res 24:3282-3291
Altan, Mehmet; Kidwell, Kelley M; Pelekanou, Vasiliki et al. (2018) Association of B7-H4, PD-L1, and tumor infiltrating lymphocytes with outcomes in breast cancer. NPJ Breast Cancer 4:40
Kim, Tae Kon; Herbst, Roy S; Chen, Lieping (2018) Defining and Understanding Adaptive Resistance in Cancer Immunotherapy. Trends Immunol 39:624-631
Goldberg, Sarah B; Patel, Abhijit A (2018) Monitoring immunotherapy outcomes with circulating tumor DNA. Immunotherapy 10:1023-1025

Showing the most recent 10 out of 675 publications