Benjamin Cole (Joint Genome Institute) on "Data management considerations for plant single-cell genomics."

While plants have arrived on the single-cell scene relatively late, the number and complexity of plant single-cell datasets have exploded over the past four years. With that massive increase in data has come a pressing need to ensure accurate documentation of the experimental provenance of plant single-cell datasets, not only for reproducibility but also for reusability in meta-analyses. During this presentation, I will discuss the current state of plant single-cell research as well as the most common practices for data storage. I will also argue for the need for better standards in the field, and what that could potentially enable.

Christopher Tuggle (Iowa State University) & Muskan Kapoor (Iowa State University) on "Single-Cell genomics data incorporation into agricultural G2P research by building a FAIR data ecosystem."

We will describe a pilot-scale project to determine if our current metadata standards for livestock and crops can be used to ingest scRNAseq datasets in a manner consistent with HCA DCP standards and if established resources (e.g., Terra) can be used to analyze the ingested data. Currently, the most comprehensive data ingestion portal for high throughput sequencing datasets from plants, fungi, protists, and animals/humans is Annotare (located at EMBL-European Bioinformatics Institute). For agricultural animal datasets, another EMBL-EBI portal, the FAANG portal, has been developed. scRNAseq data/metadata can be submitted to FAANG using a semi-automated process. We have extended this tool for scRNAseq data so that files can be validated using the HCA DCP metadata and data validation service. These files are incorporated using EMBL-EBI’s HCA DCP ingestion service and transferred to Terra for further analysis. We will also describe a Shiny-based web application, implemented in R and called Shiny-PIGGI, for the single cell-level transcriptomic study of pig immune tissues and peripheral blood mononuclear cells, which will be an important resource for improved annotation of porcine immune genes and cell types (https://shinypiggi.ansci.iastate.edu). We intend to further build upon these existing tools to construct a scientist-friendly data resource and analytical ecosystem to facilitate single cell-level genomic analysis through data ingestion, storage, retrieval, re-use, visualization, and comparative annotation across agricultural species.