Data Analysis Core

University Of New Mexico Health Scis Ctr, Albuquerque NM

Investigators

Abstract

DATA ANALYSIS CORE – PROJECT SUMMARY The Data Analysis Core will support all P01 Projects and the Biospecimen Core by providing statistical support and data analysis. There are three main goals of the Data Analysis Core: 1) Provide biostatistical support to each Project. Biostatistics experts will consult with each investigator before the onset of each Project to ensure sufficient power in study design. Biostatistical consultation will be particularly important for the clinical trial in Project 4, but will aid in model-focused studies as well. Biostatistics expertise will ensure that proper statistical tests are applied to data and that consistent statistical approaches are used throughout. In order to combine diverse data, a novel progestin prioritization ranking algorithm will be used to rank progestins for use in Project 4’s clinical trial. 2) Provide bioinformatic analysis of genomics data. Bioinformatics experts will coordinate analysis of genomics datasets, including RNA-seq, single cell RNA-seq, exome, and CRISPRa/i experiments. Bioinformaticians will ensure the use of state-of-the-art computational pipelines throughout each Project. The core will also serve as a data integration hub while working closely with all investigators. 3) Facilitate sharing of data and analysis results across Projects. Another key role of the Core will be to facilitate sharing of data across Projects. Cloud-based resources will enable easy and rapid sharing and visualization of genomics data across Projects as well as specimen tracking and sharing of histological images. The use of a centralized Data Analysis Core will enhance collaboration across the study while ensuring that rigorous approaches are used during each aspect of the proposal. By providing these services, the Data Analysis Core will help the P01 achieve the goal of identifying the most promising progestins for endometrial cancer and atypical endometrial hyperplasia and the patients that are most likely to benefit.