Multiscale statistical analysis
Based on the single-cell, proximity, segmentation, and cytoarchitectural results, multiscale features can be calculated and combined into a hyperdimensional statistical analysis.
This statistical analysis is best conceptualized as an unbiased hypothesis generation tool. That is, it contains a more unbiased view of whole organoids compared to section-based analyses, and researchers can always go back to the image data to ask new questions inspired by this statistical analysis.
Aggregating features
First, the predetermined set of multiscale features can be calculated using the following command inside an organoid group dataset folder. Please “cd” into groupN (for example, Lancaster_d35) and execute the following:
scout multiscale features organoid_folder_name(usually 2019...)/. -d 1 6 6 -v
This command takes the current folder (specified by “.”) and looks for intermediate results, including centroids_um.npy and cyto_labels.npy. The argument -d 1 6 6 specifies the z, y, and x downsampling factors used for the ventricle segmentation. This command should be repeated for each organoid in the study (the same organoids sampled from to generate the cytoarchitecture clusters). This command will create an Excel spreadsheet in the current folder called organoid_features.xlsx.
The multiscale features for each organoid can be combined into a single Excel table using the following command:
scout multiscale combine analysis.csv --output combined_features.xlsx -v
This command expects the organoid_features.xlsx to be present in each organoid folder. The combined table is written to combined_features.xlsx.
Statistical testing
To perform statistical tests on the combined features, use the notebook called “T-tests and volcano plots.ipynb”.
Expected output
The expected output from the SCOUT pipeline is a table of >200 phenotypic measurements made for each organoid sample, along with fold-changes and p-values between the treatment and control groups for each measurement. A list of all possible phenotypic measurements for is avialable in the Supplement of the SCOUT publication.