CAT Bridge (Compounds And Transcripts Bridge) is a robust tool built with the goal of uncovering biosynthetic mechanisms in multi-omics data, such as identifying genes potentially involved in compound synthesis by incorporating metabolomics and transcriptomics data.
One of the key features of CAT Bridge is its custom-built design for handling multi-mics time series data - a niche that has seen a dearth of dedicated tools till now.
And CAT Bridge is integrated with GPT 3.5 Turbo integration to help users dive deeper into the complex biological mechanisms at play.
Visualisation is key to understanding complex data. That's why CAT Bridge also includes a comprehensive suite of visualization capabilities to help you understand, explore, and present your findings more intuitively and effectively.
At the heart of CAT Bridge lies a data-driven algorithm, theoretically enabling its application across a wide spectrum of multi-omics data showcasing causal relationships. However, so far, we've tested this only between metabolome-transcriptome and metabolome-metabolome interactions.
Dependencies can be installed using pip (from the Unix terminal)
# Python dependencies
pip install matplotlib catbridge psutil numpy pandas statsmodels sklearn scipy tslearn seaborn bioinfokit networkx pillow adjustText textwrap datashader openai
# R dependencies
R -e 'install.packages("BiocManager"); BiocManager::install("DESeq2"); install.packages("readr")'
pip install catbridge
don't konw what is Granger Causality Test? look at this video: STATISTICS I Time Series I Granger Causality Test I Intuition and Example
The package is developed and maintained by Bowen Yang (by8@ualberta.ca). Please, reach us for problems, comments or suggestions.