Wang Liya, Lu Zhenyuan, delaBastide Melissa, Van Buren Peter, Wang Xiaofei, Ghiban Cornel, Regulski Michael, Drenkow Jorg, Xu Xiaosa, Ortiz-Ramirez Carlos, Marco Cristina F, Goodwin Sara, Dobin Alexander, Birnbaum Kenneth D, Jackson David P, Martienssen Robert A, McCombie William R, Micklos David A, Schatz Michael C, Ware Doreen H, Gingeras Thomas R
Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, United States.
New York University, New York, NY, United States.
Front Plant Sci. 2020 Mar 31;11:289. doi: 10.3389/fpls.2020.00289. eCollection 2020.
MaizeCODE is a project aimed at identifying and analyzing functional elements in the maize genome. In its initial phase, MaizeCODE assayed up to five tissues from four maize strains (B73, NC350, W22, TIL11) by RNA-Seq, Chip-Seq, RAMPAGE, and small RNA sequencing. To facilitate reproducible science and provide both human and machine access to the MaizeCODE data, we enhanced SciApps, a cloud-based portal, for analysis and distribution of both raw data and analysis results. Based on the SciApps workflow platform, we generated new components to support the complete cycle of MaizeCODE data management. These include publicly accessible scientific workflows for the reproducible and shareable analysis of various functional data, a RESTful API for batch processing and distribution of data and metadata, a searchable data page that lists each MaizeCODE experiment as a reproducible workflow, and integrated JBrowse genome browser tracks linked with workflows and metadata. The SciApps portal is a flexible platform that allows the integration of new analysis tools, workflows, and genomic data from multiple projects. Through metadata and a ready-to-compute cloud-based platform, the portal experience improves access to the MaizeCODE data and facilitates its analysis.
玉米编码（MaizeCODE）项目旨在识别和分析玉米基因组中的功能元件。在其初始阶段，玉米编码项目通过RNA测序、芯片测序、RAMPAGE和小RNA测序，对来自四个玉米品系（B73、NC350、W22、TIL11）的多达五种组织进行了分析。为了促进可重复科学研究，并为人类和机器提供访问玉米编码数据的途径，我们增强了基于云的门户SciApps，用于原始数据和分析结果的分析与分发。基于SciApps工作流程平台，我们生成了新的组件，以支持玉米编码数据管理的完整周期。这些组件包括用于对各种功能数据进行可重复和可共享分析的公开科学工作流程、用于批量处理和分发数据及元数据的RESTful API、一个可搜索的数据页面，该页面将每个玉米编码实验列为一个可重复的工作流程，以及与工作流程和元数据相关联的集成JBrowse基因组浏览器轨迹。SciApps门户是一个灵活的平台，允许集成来自多个项目的新分析工具、工作流程和基因组数据。通过元数据和基于云计算的随时可用平台，该门户体验改善了对玉米编码数据的访问并便于对其进行分析。
