# Data organization

Reference keys: :term:`experiment project`, :term:`well`, :term:`position`

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Celldetective structures experimental data into nested well and position folders, mimicking the spatial segregation of a multi-well plate, often used in biological assays. The well partitioning allows experimentalists to test in parallel multiple biological conditions, such as different cell types, drugs or antibodies at different concentrations, pre-treatments on the cells or surfaces and so on.

The experiment folder mimics the organization of the glass slide into wells and fields of view within wells.

Since cells are microscopic objects observed under high magnification, capturing all cells within a well in a single image is rarely feasible. Instead, experimentalists typically select multiple imaging positions (or fields of view) within the well, aiming for a representative sample of the entire well.

In Celldetective, single-cell detection is performed independently for each position. The software allows looping through multiple positions or wells, enabling streamlined analysis. Higher-level representations, such as population responses, can aggregate single-cell data from all positions within a well to provide a comprehensive overview.

A Celldetective experiment consists of a folder and a configuration file in `.ini` format. The folder is organized hierarchically to support data from multiple wells and positions:

1. Experiment folder: Contains individual well folders (one per well) and the configuration file.
2. Well folder: Includes subfolders corresponding to position within that well.
3. Position folder: Contains a single `movie/` subfolder where the user drops the stack associated with that position.

In Celldetective, "processing a movie" is synonymous with processing a position. This approach standardizes workflows and ensures clear data organization.

Biological conditions and experimental metadata can be injected into the single-cell data by modifying the experiment configuration file. The items of the `Labels` section are structured to given a unique information per well. In practise, whenever you have information that is different between at least two wells, use this section. The `Metadata` section, on the other hand, can be used to add some global variables to the single cell data (antibody concentration units, temperature and CO2 conditions of the experiment, etc).