Analytics Core

项目总结 “组学”的新前沿是对单个细胞的高通量分析。这些单细胞， 高通量技术正在为许多领域开发，包括成像、质谱分析和 DNA和RNA测序。尽管单细胞组学研究还处于相对初级阶段，但它们已经 已经揭示了基因调控和包括癌症在内的人类疾病的病因学背后的新见解 以及细胞间的相互作用。单细胞组学方法特别适合于复杂的 与疾病或表型有关的异质细胞群。 这个核心(分析)的目标是开发和支持开发新的方法 分析组学数据(重点是单细胞组学数据)，并提供分析和计算 对研究项目的支持。这一目标需要集成、维护和充分的统计 分析不同的高维数据，产生于：(I)研究提出的高通量分析 本科布雷的项目；以及(Ii)公开可用的数据库。公共可获得的组学数据的利用是 这对于验证对个别研究结果的解释和确定优先顺序很重要。《组学》 革命》已经产生了大量(而且还在不断增长)的数据，这些数据大多仍然是 宝藏“；这一资源对于重新挖掘和对旧数据提出新问题特别宝贵。通过使用 已经可用的组学数据，这一核心旨在将这一隐藏的宝藏投入工作。高维数据的使用 数据需要能够快速、快速地获取、检索、存储、跟踪、管理和处理信息 高效的方式。 这个核心的成员拥有广泛的专业知识和兴趣，将他们的活动统一在 项目。这一核心将为研究提供强大而深刻的支持，否则这些研究将无法实现 已实现。生物信息学和生物统计学的设计和分析对大型项目的规划至关重要 这一核心将为协调整个计划的研究提供一个环境 项目，并确定和应用最先进的统计和计算方法。

PROJECT SUMMARY The new frontier in “-omics” is represented by high-throughput analyses of individual cells. These single-celled, high-throughput technologies are being developed for many areas, including imaging, mass spectrometry, and DNA- and RNA-sequencing. Even though single-cell -omics studies are in their relative infancy, they have already revealed new insights behind gene regulation and the etiology of human diseases, including cancer and cell-to-cell interactions. Single-cell -omics methods are especially suited for complex analyses of heterogeneous cell populations involved in disease or phenotypes. The goal of this Core (Analytics) is to develop and to support the development of novel approaches for the analysis of -omics data (with a focus on single-cell -omics data), and to provide analytical and computational support for the research projects. This goal requires the integration, maintenance, and adequate statistical analysis of disparate high-dimensional data, arising from: (i) high-throughput analyses proposed by research projects of this COBRE; and (ii) publicly available databases. Utilization of publicly available -omics data is important for validating the interpretation and prioritization of the findings from individual studies. The “-omics revolution” has already generated a massive (and still growing) volume of data that mostly remains a “hidden treasure”; this resource is particularly valuable for re-mining and for asking new questions of old data. By using already available -omics data, this Core aims to put this hidden treasure to work. The use of high-dimensional data requires the capacity to obtain, retrieve, store, track, curate, and process information in a rapid and efficient manner. The members of this Core have extensive expertise and interests that unite their activities among the projects. This Core will enable a robust and profound level of support for research that could not otherwise be achieved. Bioinformatics and biostatistical design and analysis are critical for the planning of large projects proposed in this COBRE; this Core will provide an environment for coordinating research across the program project, and to identify and apply state-of-the-art statistical and computational methods.