Experimental Design Software for Translational Gastrointestinal Microbiome Studie

描述（由申请人提供）：需要为研究团队提供实验设计和假设检验，以开发和验证胃肠道（GIT）疾病中的分类宏基因组生物标志物。翻译研究团队需要1）设计一个实验来测试一个假设（例如，克罗恩病中的微生物群与正常对照中不同），2）计算确保用于在限定水平下测试分类群频率差异的功效和显著性的设定水平所需的受试者数量（例如，类，属），）具有客观检验统计量以决定是否拒绝零假设，可能调整FR患者因素，例如年龄、性别、饮食等，和4）拥有计算验证生物标志物所需的诊断性能的工具（例如，灵敏度、特异性、阳性/阴性预测概率）。当前的分析方法（例如，大量单变量“一次一个分类群”比较与多个测试调整、探索性聚类分析）对于发现是极好的，但是它们的应用和解释中的主观性（例如，Bray-Curtis与Jaccard距离）使它们不适合用于翻译研究。使用参数统计工具进行客观决策是将宏基因组学从发现阶段转移到临床生物标志物验证和资格的必要条件。该I期SBIR将开发并商业化实验设计和统计分析软件平台，用于转化临床研究团队开发胃肠道（GIT）疾病的诊断和预后分类标记的宏基因组生物标志物。现有的开源软件和新软件将被组织到GIT翻译研究平台的统计工具中。类似于Red Hat的Linux和Cloudera的Hadoop的开源商业模式将通过提供（可选）许可的专有GUI来促进这些功能的部署和使用，数据分析即服务（DAAAS）模型合同，云计算和咨询服务产生收入。重要的是要注意，该平台不会取代宏基因组预处理管道（例如，数据采集、汇编、注释、RDP匹配），但是采用这些步骤的最终产品（例如，分类群通过样品频率表）以分析用于临床使用。

DESCRIPTION (provided by applicant): Design of experiments and test of hypotheses need to be available to research teams to develop and validate taxonomic metagenomic biomarkers in gastrointestinal tract (GIT) diseases. The translational research team needs to 1) design an experiment to test a hypothesis (e.g., microbiota in Crohn's disease is different than in normal controls), 2) calculate the number of subjects needed to ensure a set level for power and significance for testing differences in taxa frequencies at a defined level (e.g., class, genus) , ) have an objective test statistic to decide if the null hypothesis is rejected, possibly adjusting fr patient factors such as age, gender, diet, etc., and 4) possess tools to calculate diagnostic performance needed to validate biomarkers (e.g., sensitivity, specificity, positive/negative predictive probabilities). Current analytic approaches (e.g., mass univariate "one-taxa-at-a-time" comparisons with multiple testing adjustments, exploratory cluster analysis) are excellent for discovery, but the subjectivity in their application and interpretation (e.g., Bray-Curtis versus Jaccard distance) make them inappropriate for translational research. Objective decision making using parametric statistical tools is necessary to move metagenomics from the discovery phase to clinical biomarker validation and qualification. This Phase I SBIR will develop and commercialize an experimental design and statistical analysis software platform for translational clinical research teams developing diagnostic and prognostic taxonomic labeled metagenomic biomarkers for gastrointestinal tract (GIT) diseases. Existing open source software and new software will be organized into the STATISTICAL TOOLS FOR GIT TRANSLATIONAL RESEARCH platform. An open source business model similar to Red Hat's Linux and Cloudera's Hadoop will be used with revenue generated by offering (optionally) a licensed proprietary GUI to facilitate deployment and use of these functions, contract for Data-Analysis-As-A-Service (DAAAS) model, cloud computing, and consulting services. It is important to note that the platform will not replace the metagenomic pre-processing pipelines (e.g., data acquisition, assembly, annotation, RDP matching), but takes the end product of these steps (e.g., taxa by sample frequency tables) to analyze for clinical use.