Experimental Design Software for Translational Gastrointestinal Microbiome Studie

用于转化胃肠道微生物组研究的实验设计软件

• 批准号: 8715140
• 负责人: Alexandra McClure
• 金额: $ 28.33万
• 依托单位: WILLIAM D SHANNON CONSULTING, LLC
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-15 至 2016-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8715140
• 关键词: Adoption; Age; Agreement; Algorithms; Apache Indians; Architecture; Bacteria; Big Data; Biological Markers; Biomedical Research; Businesses; Clinical; Clinical Data; Clinical Research; Cloud Computing; Cluster Analysis; Code; Communication; Computer software; Consult; Contracts; Crohn' s disease; Data; Data Analyses; Data Security; Decision Making; Diagnostic; Diet; Disease; Disease Progression; Ensure; Experimental Designs; Feedback; Frequencies; Gastrointestinal Diseases; Gastrointestinal tract structure; Gender; Goals; Health; Health Insurance Portability and Accountability Act; Health Services Research; Human; Label; Licensing; Link; Linux; Measures; Metagenomics; Modeling; Output; Patients; Performance; Phase; Population; Probability; Process; Research; Research Personnel; Resources; Running; Sample Size; Sampling; Sensitivity and Specificity; Services; Small Business Innovation Research Grant; Software Design; Source Code; Statistical Algorithm; Structure; System; Taxon; Testing; Time; Translational Research; Universities; Validation; Washington; Writing; base; commercialization; data acquisition; design; gastrointestinal; graphical user interface; improved; meetings; microbiome; open source; prognostic; prototype; public health relevance; research study; simulation; software development; statistics; tool

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.

描述（由申请人提供）：研究团队需要提供实验设计和假设检验，以开发和验证胃肠道（GIT）疾病的分类宏基因组生物标志物。转化研究团队需要 1) 设计一个实验来检验假设（例如，克罗恩病中的微生物群与正常对照中的微生物群不同），2) 计算所需的受试者数量，以确保测试差异的功效和显着性达到设定水平在定义水平（例如类、属）的分类群频率中，有一个客观的检验统计数据来决定是否拒绝零假设，可能会调整 fr 患者因素，例如年龄、性别、饮食、等，4) 拥有计算验证生物标志物所需的诊断性能的工具（例如敏感性、特异性、阳性/阴性预测概率）。当前的分析方法（例如，大规模单变量“一次一个类群”与多个测试调整的比较、探索性聚类分析）非常适合发现，但其应用和解释的主观性（例如，Bray-Curtis 与 Jaccard）距离）使它们不适合转化研究。使用参数统计工具做出客观决策对于将宏基因组学从发现阶段转向临床生物标志物验证和鉴定阶段是必要的。该 I 期 SBIR 将为转化临床研究团队开发并商业化实验设计和统计分析软件平台，开发胃肠道 (GIT) 疾病的诊断和预后分类标记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 STATISTICAL TOOLS FOR GIT TRANSLATIONAL RESEARCH 平台中。类似于 Red Hat Linux 和 Cloudera 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而产生收入，数据分析即服务 (DAAAS) 合同）模型、云计算和咨询服务。值得注意的是，该平台不会取代宏基因组预处理流程（例如数据采集、组装、注释、RDP匹配），而是采用这些步骤的最终产品（例如按样本频率表分类）进行分析供临床使用。