Tempo: A Bayesian Algorithm for Circadian Phase Inference in Single-Cell RNA-Sequencing Data

System Requirements

Hardware Requirements

Tempo requires only a computer with enough RAM to support in-memory operations. For most datasets, >=8GB RAM should be sufficient.

Software Requirements

OS requirements

Tempo has been tested on macOS 10.14.5 (Mojave), 12.2.1 (Monterey), and CentOS Linux 7.

Python dependencies

Tempo requires python >= 3.8 and depends on the following python packages:

• anndata
• numpy
• pandas
• scanpy>=1.6
• scikit-image
• scikit-learn
• scipy
• statsmodels
• torchaudio
• torchvision
• tqdm
• pytorch>=1.9.0

Installation

Tempo requires mini-conda for installation. For information on installing mini-conda for your operating system, please view https://docs.conda.io/en/latest/miniconda.html.

After installing mini-conda, run the following commands to install Tempo:

1. git clone https://github.com/bauerbach95/tempo
2. cd tempo
3. source install.sh

Installation should take less than 5 minutes. After installing, you can activate the conda environment containing the installed Tempo package: conda activate tempo

To test if Tempo works properly, run the run_test.py file using using the activated environment: python run_test.py

Running the test should take less than 5 minutes. Successful completion of the test will yield a message "SUCCESSFULLY FINISHED".

To deactivate the environment: conda deactivate

Running Tempo

Tutorials on how to run Tempo (and information on inputs / outputs) can be viewed in the tutorial folder of the repository.