The research proposed by the UT Lung Cancer SPORE encompasses a broad range of activities, including studies in clinically annotated patient tumor samples, tumor cell lines, xenografts, and mouse models, as well as human clinical trials. These studies generate multiple types of data, including clinical, histologic, genome-wide molecular (mutation, expression), proteomic, biochemical, immunohistochemical, drug and immune response phenotype, metabolomic, and tumor environmental. The Data Sciences Core provides comprehensive expertise to ensure the statistical integrity, data integrity, data sharing capability, and data analysis accuracy of the studies performed by the SPORE. The Core has a Director at each institution (Y. Xie, UTSW, and J. Wang, MDACC) and the flexibility to match personnel to the evolving needs of existing SPORE Projects, and Developmental Research and Career Enhancement Program (DRP, CEP) Projects. To ensure appropriate consideration of biostatistics and data management concerns throughout all SPORE work, members of this Core participate in monthly all-SPORE Project and Core meetings, and in the specific Data Sciences SPORE video/WebEx conferences linking researchers at UTSW and MDACC. The Data Sciences Core will perform the following: (a) develop and maintain systems for data storage, retrieval, analysis, and sharing; (b) provide an interface for all SPORE investigators to exchange data and information easily and freely; (c) provide analyses to allow investigators outside the UT Lung SPORE to have appropriate access to SPORE datasets, and to be able easily to independently reproduce and validate biostatistical and computational analyses. The Core services include innovative, unique, and occasionally customized approaches to solving the data analysis and interpretation challenges of the modern data-centric research laboratory. The Core Specific Aims are:
Aim 1 : Provide valid statistical designs for SPORE laboratory research, clinical trials and translational experiments.
Aim 2 : Oversee and conduct innovative statistical modeling, simulations, data analyses and data integration needed by the Projects, DRP and CEP, and Pathology Core to achieve their specific aims.
Aim 3 : Ensure that all complex molecular, biologic, and clinical datasets are protected for confidentiality, analyzed, shared among SPORE investigators and collaborators, and appropriately deposited into publically accessible databases as required, using valid and innovative bioinformatics methods.
Aim 4 : Develop and maintain a secure, web-accessible site for SPORE research data integration and storage linked to an extensive tissue repository of clinically and molecularly annotated archived patient samples, tumor grafts, tumor and normal cell lines, and relevant mouse models of lung cancer; we will also (a) develop and maintain centralized deposits from the literature of lung cancer-relevant datasets in a web site (?Lung Cancer Explorer?) to support SPORE investigators and the broader research community; and (b) provide data-related analyses and documents for publication (such as ?Sweave?) that allow the research community to independently reproduce and validate our analyses.
Data Sciences Core (Core C) Project Narrative The Data Science Core ensures that all experiments performed by the core are properly designed, and that the data collected by those experiments are stored safely, analyzed sensibly, and made available to other SPORE investigators (and ultimately to other lung cancer researchers) in order to further the ultimate goal of translating knowledge from the research lab into the clinic. The Data Sciences Core interfaces with all of the SPORE Projects, Developmental Research (DRP), and Career Enhancement Programs (CEP), and works to integrate the findings from the Molecular Pathology Core using appropriate biostatistical and computational biology approaches into the SPORE Projects. The Data Sciences Core provides documents such as Sweave for publication to allow others to reproduce complex analyses, and works to develop and maintain a database for the large-scale datasets of the SPORE including dataset deposits as required by the NIH/NCI (e.g. dbGAP and others), to provide datasets available to extra mural sources to facilitate horizontal and vertical collaborations by the SPORE.
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