What question did this study set out to answer?

The aim is to provide a tool that fetches and processes diverse RNA-seq data types and converts them into accessible formats within R.

April 13, 2026Open Access

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

Key Points

The aim is to provide a tool that fetches and processes diverse RNA-seq data types and converts them into accessible formats within R.
Developed an R package with a Docker image.
Supports downloading various scRNA-seq data types from multiple public repositories.
Processes data to load count matrices and annotations into R.
Converts between different scRNA-seq object formats and benchmarks these tools.
GEfetch2R successfully downloads and processes scRNA-seq and bulk RNA-seq data.
Facilitates format conversion among multiple widely used RNA-seq object types.
Offers benchmarking on usability, information retention, and performance of conversion tools.

Abstract

Abstract Background 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. Findings 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/celldataₛet, 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). Conclusions GEfetch2R is an R package dedicated to facilitating researchers to access and explore the existing gene expression data from various public repositories. It can function as a data downloader (supports all three scRNA-seq and two bulk RNA-seq data types), a data processor (processes and loads the output/downloaded count matrices and annotations to R), and an object format converter (between the widely used scRNA-seq objects).

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