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

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• Single-cell RNA sequencing (scRNA-seq) data analysis relies on accessing and reanalyzing existing datasets.
• Current tools lack the capability to fetch diverse scRNA-seq data types from various repositories, process them, and convert formats.

Purpose of the Study:

• To develop an R package, GEfetch2R, that addresses the limitations in accessing and processing public scRNA-seq data.
• To provide a unified tool for downloading, processing, and converting various scRNA-seq data formats.

Main Methods:

• GEfetch2R supports downloading raw data, count matrices, and processed objects from multiple repositories (SRA, ENA, GEO, UCSC Cell Browser, PanglaoDB, Zenodo, CELLxGENE, HCA).
• The package processes downloaded data, loads them into R (SeuratObject/DESeqDataSet), and filters based on metadata.
• It enables format conversion between widely used scRNA-seq objects (SeuratObject, AnnData, SingleCellExperiment, CellDataSet, loom) and benchmarks conversion tools.

Main Results:

• GEfetch2R successfully downloads and processes diverse scRNA-seq data types from multiple public repositories.
• The package facilitates format conversion between major scRNA-seq object types, with benchmarking to guide tool selection.
• It also handles bulk RNA-seq data, downloading and processing raw data and count matrices.

Conclusions:

• GEfetch2R is a versatile R package that simplifies access to and exploration of public gene expression data.
• It serves as a data downloader, processor, and object format converter for both scRNA-seq and bulk RNA-seq data.
• This tool enhances the efficiency of researchers working with large-scale gene expression datasets.