Management, Analyses, and Distribution of the MaizeCODE Data on the Cloud

Liya Wang, Zhenyuan Lu, Melissa delaBastide, Peter Van Buren, Xiaofei Wang, Cornel Ghiban, Michael Regulski, Jorg Drenkow, Xiaosa Xu, Carlos Ortiz-Ramirez, Cristina F. Marco, Sara Goodwin, Alexander Dobin, Kenneth D. Birnbaum, David P. Jackson, Robert A. Martienssen, William R. McCombie, David A. Micklos, Michael C. Schatz, Doreen H. WareThomas R. Gingeras

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Article number289
JournalFrontiers in Plant Science
StatePublished - Mar 31 2020


  • bioinformatics
  • cloud computing
  • functional annotations
  • workflows

ASJC Scopus subject areas

  • Plant Science


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