cellData

CellData is a general term used to describe structured information associated with a biological cell or with a cell in a computational grid or image. It encompasses per-cell attributes collected during experiments, imaging, or data analysis.

In biology and biomedical research, cell data can include identifiers such as cell id, type or lineage, donor information, experimental condition, and batch. It may also attach molecular profiles, including gene expression, chromatin marks, or protein abundance, at the single-cell or population level.

In microscopy and image analysis, cell data includes spatial coordinates, segmentation identifiers, morphological measurements (area, shape descriptors), and intensity measurements across channels. These per-cell measurements enable downstream analyses such as clustering, trajectory inference, and spatial mapping.

Data models typically store per-cell records in tabular metadata alongside feature matrices. Common formats include CSV/TSV, JSON, HDF5, and specialized structures in bioinformatics toolkits (for example, per-cell metadata in AnnData or cell_data structures). There is no single universal standard; conventions vary by field and software.

Applications of cell data range from basic science to clinical research, supporting data integration, visualization, quality control, and machine learning. Ethical considerations include privacy when donor information is involved and the need for careful data provenance and reproducibility.