QIAGEN scientists manually curate the project, sample and cell type metadata for each dataset in Single Cell Land. This provides the level of granularity into the scRNA-seq data that is necessary to understand the biological context of the experiment. Datasets are meticulously re-processed from raw data using a unified workflow, thoroughly QC checked, then annotated for more than 70 attributes at single-cell resolution. This allows you to search for a specific cell type, tissue, gene, age, gender or any other curated trait across all projects, and quickly discover relevant datasets.