singelcelldata
Single-cell data refers to measurements collected from individual cells rather than from pooled samples. This type of data enables the study of cellular heterogeneity, rare cell populations, and dynamic processes that are masked in bulk analyses. Common modalities include single-cell RNA sequencing (scRNA-seq), single-cell ATAC sequencing (scATAC-seq), and multimodal approaches such as CITE-seq, which combines RNA measurement with protein markers, and single-cell proteomics. Imaging-based single-cell data and spatial transcriptomics are also important, providing spatial context alongside molecular profiles.
Typical single-cell data are structured as high-dimensional matrices with cells as columns and features (such as
Analysis workflows generally start with quality control and normalization, followed by dimensionality reduction, clustering, and cell-type
Data sharing and standards are important due to the large size and complexity of single-cell datasets. Repositories