Core C- Bioinformatics Core

项目概要-核心C：生物信息学 生物信息学是统计学和计算机科学在分子生物学领域的应用。它有 作为一个独立的领域，现代生物医学研究人员很容易生成的数据集 超过了可以直接看到的。大量的数据增加了假阴性的机会， 假阳性结果，并主张稳健的统计模型和可重复的工作流程。核心C将与 项目I、II和III中对人类、青蛙和小鼠进行大规模平行测序产生的数据， 核心B提取可能导致脊髓脊膜膨出或影响神经管的变体 表型项目和核心的PI过去曾广泛合作， 在下一代测序（NGS）数据分析领域建立了生产力的跟踪记录。巴夫纳医生 在生物信息学和基因组学领域广泛开展工作， NGS数据集的新算法和统计技术。我们设想DNA测序 以患者及其父母的全基因组或全外显子组测序的形式， 交付给核心C，以确定潜在致病风险相关的变体优先级。RNA 从核心B生成的测序、单细胞测序和表观遗传测序数据，以及从核心B导入的 项目I、II和III中提取的表达变化将交付给核心C， 对每个项目进行隔离分析和进一步验证。生物信息学核心将提供这些 分析管道，以识别和注释变体，并开发创新的网络分析，RNAseq， Methylseq和单细胞分析发现基于蛋白质-蛋白质的MM新遗传机制 相互作用（PPI）和基因共表达网络，以解释来自当前遗传和 基因组技术，并将其应用于本计划项目的不同组成部分。虽然我们的 主要目标是使用现有的计算方法提供服务，我们预计核心B还将 根据项目和核心的要求，开发新的计算方法，就像我们开发 我们当前的WGS分析管道。方法开发将面向未解决的基本问题， 上述四个关键功能的潜在问题，如将变异与表型相关联的算法， 计算上位相互作用、检测短串联重复序列和 来自WGS的移动的元件，基因型与途径整合的先进方法，下一代- 代测序（NGS）在分析基因关联，并发现遗传变异，影响 蛋白质表达或功能。

PROJECT SUMMARY – Core C: Bioinformatics Bioinformatics is the application of statistics and computer science to the field of molecular biology. It has emerged as a field unto itself, as the datasets that are generated by modern biomedical researchers easily exceeds what can be directly visualized. The vast amount of data increases the chance of false-negative and false-positive results, and argue for robust statistical models and reproducible workflows. Core C will work with the data generated from massive parallel sequencing from human, frog and mouse in Project I, II and III and Core B to extract variants that have potential to cause meningomyelocele or influence neural tube phenotypes. The PIs of the Projects and Cores have worked together extensively in the past, and have an established track record of productivity in the area of next generation sequencing (NGS) data analysis. Dr. Bafna has worked broadly in bioinformatics and genomics in the development computational methodologies employing novel algorithms and statistical techniques for NGS datasets. We envision that the DNA sequencing derived from Project I in the form of whole genome or whole exome sequencing from patients and their parents will be delivered to Core C for determination of potentially pathogenic risk-associated variant prioritization. RNA sequencing, single cell sequencing and epigenetic sequencing data generated from Core B, as well as imported from Project I, II and III, will be delivered to Core C for extraction of expression changes, which will be delivered to each of the Projects for segregation analysis and further validation. The Bioinformatics Core will provide these analysis pipelines to identify and annotate variants, and to develop innovative network analyses, RNAseq, Methylseq and single cell analysis to discover novel genetic mechanisms of MM based on Protein-Protein Interaction (PPI) and gene co-expression networks, to interpret large datasets from current genetic and genomic technologies, and to apply these in the different components of this Program Project. Although our primary goal is to provide service using existing computational methods, we expect that the Core B will also develop novel computational methods as required by the Projects and Cores, as we have done to develop our current WGS analysis pipeline. Methods development will be geared towards fundamental unsolved problems underlying the above four key functions, such as algorithms for correlating variants to phenotypes, further improvements in methods for computing epistatic interactions, detection of short tandem repeats and mobile elements from WGS, advanced methods for integration of genotypes with pathways, use of next- generation sequencing (NGS) in analysis of gene association, and discovery of genetic variants that influence protein expression or function.