Getting started

How to get started with cellfinder

Before you start

Make sure you activate your conda environment before running cellfinder

Running cellfinder

The cell detection via cellfinder can be run with a single terminal command (cellfinder):

cellfinder -s signal_channel_images -b background_channel_images -o /path/to/output_directory -x 2 -y 2 -z 5

Multiple channels can also be processed at once:

cellfinder -s first_signal_channel_images second_signal_channel_images -b background_channel_images -o /path/to/output_directory -x 2 -y 2 -z 5

However, there are many options to change what parts of the analysis are run, and how they are run. For instance, to register the brain to the allen reference atlas, use --register. I recommend looking through the Command line options.

If you have any spaces in your file-path, please enclose it in quotation marks, otherwise cellfinder will interpret it as two inputs, separated by a space.

i.e. "/path/to/my data" not path/to/my data.

Retraining the machine learning network to classify cells

The deep learning network included with cellfinder to classify cells as real cells or artefacts was trained on a very specific dataset. You will very likely need to retrain this if the classification is incorrect on your data. See Training the network.