The article describes a droplet-based system for 3' mRNA counting of tens of thousands of single cells per sample, enabling high-throughput and parallel processing of multiple samples. The system, called GemCode, encapsulates cells in Gel beads in Emulsion (GEMs) and performs reverse transcription within each droplet. The resulting cDNA molecules are amplified in bulk and sequenced using Illumina short-read sequencing. The Cell Ranger pipeline processes the sequencing data, allowing automated cell clustering. The authors demonstrate the system's technical performance by collecting transcriptome data from ~250k single cells across 29 samples, validating its sensitivity and ability to detect rare populations. They profiled 68k peripheral blood mononuclear cells (PBMCs) to show the system's capability to characterize large immune populations and developed a computational method to distinguish donor from host cells in bone marrow transplant samples using genotype analysis. The GemCode technology addresses the challenges of existing scRNA-seq methods by offering high throughput, rapid cell encapsulation, and a high cell capture rate, making it suitable for a wide range of cell types and applications.The article describes a droplet-based system for 3' mRNA counting of tens of thousands of single cells per sample, enabling high-throughput and parallel processing of multiple samples. The system, called GemCode, encapsulates cells in Gel beads in Emulsion (GEMs) and performs reverse transcription within each droplet. The resulting cDNA molecules are amplified in bulk and sequenced using Illumina short-read sequencing. The Cell Ranger pipeline processes the sequencing data, allowing automated cell clustering. The authors demonstrate the system's technical performance by collecting transcriptome data from ~250k single cells across 29 samples, validating its sensitivity and ability to detect rare populations. They profiled 68k peripheral blood mononuclear cells (PBMCs) to show the system's capability to characterize large immune populations and developed a computational method to distinguish donor from host cells in bone marrow transplant samples using genotype analysis. The GemCode technology addresses the challenges of existing scRNA-seq methods by offering high throughput, rapid cell encapsulation, and a high cell capture rate, making it suitable for a wide range of cell types and applications.