Supporting data for "GEfetch2R: fetching single-cell/bulk RNA-seq data from public repositories to R and benchmarking the subsequent format conversion tools"

Downloading and reanalyzing the existing single-cell RNA sequencing (scRNA-seq) data provides an efficient choice to gain clues and new insights. However, no tool can fetch the diverse scRNA-seq data types (raw data, count matrix, and processed object) distributed in various repositories, process and load the downloaded data to R, convert formats between scRNA-seq objects, and benchmark the format conversion tools. Here, we present GEfetch2R, an R package with Docker image to (i) download diverse scRNA-seq data types, including raw data (SRA and ENA), count matrix (GEO, UCSC Cell Browser, and PanglaoDB), and processed object (GEO, Zenodo, CELLxGENE, and HCA); (ii) process the downloaded data, load the count matrices, annotations, and rds files to R (SeuratObject/DESeqDataSet), filter the SeuratObject based on cell metadata and genes, and dissect and extract the RData files; (iii) convert formats between the widely used scRNA-seq objects, including SeuratObject, AnnData, SingleCellExperiment, CellDataSet/cell_data_set, and loom, and benchmark format conversion tools in terms of information kept, usability, running time, and scalability to guide the tool selection. Furthermore, GEfetch2R can also download, process, and load bulk RNA-seq raw data (SRA and ENA) and count matrices (GEO) to R (DESeqDataSet).