The goal of the Bioinformatics/Biostatistics core is to address the statistical and bioinformatics analysis needs of the Yale SPORE in skin cancer projects and cores. Another major goal is the maintenance and extension of a SPORE Data Management and Analysis System (DMAS) for tracking of biological specimens and processing of clinical and experimental data. A final goal of the Bioinformatics/Biostatistics Core is the provision of data compliant with the SPORE data and resource-sharing plan.
The specific aims of the Bioinformatics/Biostatistics Core are Aim 1: Maintenance and extension of a SPORE Data Management and Analysis System (DMAS) for specimen tracking, as well as storing and analyzing clinical and experimental data for all SPORE projects, and Aim 2: Bioinformatics and statistical analysis of SPORE project data.
For Aim 1, we will maintain and extend the SPORE DMAS, which currently tracks SPORE specimens in caTissue, uses caArray for storing omics data and calntegrator for data integration and dissemination. The Core also maintains a dedicated data warehouse for integrative data analysis across omics modalities. DMAS will be tightly integrated Into the SPORE specimen resource core, and will serve the data management needs of the SPORE project members. DMAS will make extensive use of existing informatics systems at Yale University and existing caBIG technology. The Core will emphasis the Interactions with the wider skin cancer community.
For Aim 2, the Bioinformatics/Biostatistics Core will address the analytic questions arising from the SPORE projects. Service provided by the Core will range from planning activities to consulting on specific analytic questions. More specifically, the Core will schedule regular meetings with the SPORE investigators, and maintain an open door policy for any bioinformatics/biostatistical questions. Since the observed data can have characteristics different from hypothesized, the Core will conduct regular interim analyses, dynamically update the power calculations, develop new statistical and bioinformatics methodology as needed, provide timely suggestions to SPORE investigators, and thus play an important role in the entire study.
|Brash, Douglas E (2015) UV signature mutations. Photochem Photobiol 91:15-26|
|Jilaveanu, Lucia B; Parisi, Fabio; Barr, Meaghan L et al. (2015) PLEKHA5 as a Biomarker and Potential Mediator of Melanoma Brain Metastasis. Clin Cancer Res 21:2138-47|
|Kong, Yong; Krauthammer, Michael; Halaban, Ruth (2014) Rare SF3B1 R625 mutations in cutaneous melanoma. Melanoma Res 24:332-4|
|Taube, Janis M; Klein, Alison; Brahmer, Julie R et al. (2014) Association of PD-1, PD-1 ligands, and other features of the tumor immune microenvironment with response to anti-PD-1 therapy. Clin Cancer Res 20:5064-74|
|Zito, Giovanni; Saotome, Ichiko; Liu, Zongzhi et al. (2014) Spontaneous tumour regression in keratoacanthomas is driven by Wnt/retinoic acid signalling cross-talk. Nat Commun 5:3543|
|Leonhardt, Ralf M; Abrahimi, Parwiz; Mitchell, Susan M et al. (2014) Three tapasin docking sites in TAP cooperate to facilitate transporter stabilization and heterodimerization. J Immunol 192:2480-94|
|Sanmamed, Miguel F; Chen, Lieping (2014) Inducible expression of B7-H1 (PD-L1) and its selective role in tumor site immune modulation. Cancer J 20:256-61|
|Ho, Ping-Chih; Meeth, Katrina M; Tsui, Yao-Chen et al. (2014) Immune-based antitumor effects of BRAF inhibitors rely on signaling by CD40L and IFN?. Cancer Res 74:3205-17|
|Paglino, Justin C; Andres, Wells; van den Pol, Anthony N (2014) Autonomous parvoviruses neither stimulate nor are inhibited by the type I interferon response in human normal or cancer cells. J Virol 88:4932-42|
|Troche, Jose Ramon; Ferrucci, Leah M; Cartmel, Brenda et al. (2014) Systemic glucocorticoid use and early-onset basal cell carcinoma. Ann Epidemiol 24:625-7|
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