An Integrative Bioinformatics Platform with Application in Single Cancer Cells

项目摘要 人类癌症是高度异质性的。然而，由于技术的限制，细胞间 直到最近，才在全基因组范围的单细胞水平上检测到异质性。新技术，如 单细胞RNA-Seq和Exome-Seq揭示了新的见解和比过去更深刻的复杂性 之前的想法是。在耶鲁大学遗传学系与魏斯曼博士团队的合作下， 现在，从同一肿瘤细胞进行多种综合分析是可行的。然而，严谨 计算方法还比较落后，为了解决计算挑战和确定 真正的异质性，而不是噪音。在此，我们提出了一个用户友好的、经过优化的生物信息学平台 整合多种类型的单细胞NGS数据，特别是转录组、外显子组和CpG甲基组 全部从同一单元中获取的数据。具体地说，在本研究中，我们将首先在 并行三条新的NGS生物信息学管道，以实现基于单细胞的RNA-Seq、Exome-Seq和CpG 甲基组数据。然后，我们将开发和验证集成管道，以分析多种类型的高 产量数据，例如RNA-Seq、Exome-Seq和CpG甲基组单细胞数据。要测试 软件套件，我们将首先从红白血病细胞系K562获得数据集。然后我们将利用这一点 生物信息学套件用于研究髓系白血病患者样本的异质性 耶鲁干细胞中心的血液学家斯蒂芬妮·哈琳博士。除了破译肿瘤的异质性，这一点 界面友好的生物信息学平台有望被单细胞测序界广泛使用。

Project Summary Human cancers are highly heterogeneous. However, due to the limit of technologies, the intercellular heterogeneity was not detectable genome-wide at single-cell level until recently. New technologies such as single-cell RNA-Seq and exome-Seq have revealed new insights and more profound complexity than what was previously thought. In collaboration with Dr. Weissman's group in the Genetics Department at Yale University, it is now feasible to perform multiple integrative assays from the same single tumor cell. However, rigorous computational methods are still lagging behind, in order to solve the computational challenge and determine true heterogeneity rather than noise. Here we propose a user-friendly bioinformatics platform that is optimized to integrative multiple types of single-cell NGS data, in particular, transcriptome, exome and CpG methylome data that are all obtained from the same cell. Specifically, in this study we will first construct and validate in parallel three new NGS bioinformatics pipelines to enable single-cell based RNA-Seq, exome- Seq, and CpG methylome data. We will then develop and validate an integration pipeline to analyze multiple types of high- throughput data, exemplified by the RNA-Seq, exome-Seq and CpG methylome single-cell data. To test the software suite, we will first obtain data sets from erythroleukemia cell line K562. We will then utilize this bioinformatics suite to investigate heterogeneity in Myeloid Leukemia patient samples provided by hematologist Dr. Stephanie Halene at Yale Stem Cell Center. Beyond deciphering tumor heterogeneity, this user-friendly bioinformatics platform is expected to be used widely by the single-cell sequencing community.