Data organization

Reference keys: experiment project, well, position

Structure

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 is used by experimentalists to test multiple biological conditions in parallel.

Since resolving single-cells requires 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, thus sampling the well.

A direct consequence of this structural organization is that there is a spatial scale relationship between positions, wells and experiment: \(\mathcal{A}_\textrm{position} \leq \mathcal{A}_\textrm{well} \leq \mathcal{A}_\textrm{experiment}\) , where \(\mathcal{A}\) is the spatial area. At the same time, a position can be conceptually understood as a repetition of a biological condition, a well the biological condition and the experiment as a collection of biological conditions.

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

By convention, an experiment should be associated with data produced during a unique, timestamped, experiment. It is technically possible to create meta-experiments where positions or wells are pulled from more than one experiment, which is convenient to assess the reproducibility of an outcome.

Processing

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.

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

Metadata

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 CO:math:_2 conditions of the experiment, etc).