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）：研究团队的实验设计和假设的测试需要开发和验证胃肠道（GIT）疾病中的分类元基因组生物标志物。翻译研究团队需要进行1）设计实验以检验假设（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）计算确保确保对功率和意义的设置水平和意义的受试者数量，以测试分类频率的差异，以拒绝定义的统计因素（例如，类别），如果统计范围的属性（例如，类别，类，属），）随着年龄，性别，饮食等的年龄，4）具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，正/阴性预测概率）。当前的分析方法（例如，与多个测试调整，探索性群集分析的质量单变量“一次性”比较）非常适合发现，但是它们的应用和解释中的主观性（例如，Bray-Curtis与JACCARD距离与JACCARD距离）使他们不适合翻译研究。使用参数统计工具的客观决策对于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是必要的。该阶段I SBIR将开发和商业化一个实验设计和统计分析软件平台，用于转化临床研究团队，开发诊断和预后的分类学标记为胃肠道疾病（GIT）疾病的元基因组生物标志物。现有的开源软件和新软件将被组织到GIT转化研究平台的统计工具中。类似于Red Hat的Linux和Cloudera的Hadoop类似的开源业务模型将通过（可选）提供（可选的）获得许可的专有GUI产生的收入，以促进这些功能的部署和使用，合同，用于数据分析 - AS-A-Ser-Service（DAAAS）模型，云计算和咨询服务。重要的是要注意，该平台不会替代宏基因组预处理管道（例如数据采集，组装，注释，注释，RDP匹配），而是采用这些步骤的最终产品（例如，样品频率表）以分析临床使用。