RNA-GPS

Interpretable model for predicting high-resolution RNA sub cellular localization to the following localizations:

• ER Membrane
• Nuclear lamina
• Mito matrix
• Cytosol
• Nucleolus
• Nucleus
• Nuclear pore
• Outer mito membrane

This model is trained on APEX-seq data, which measures RNA localization human HEK293T cells.

SARS-CoV-2 Analysis

Since viruses reproduce by hijacking human cellular machinery, we can also use this model to generate hypotheses surrounding localization of SARS-CoV-2 RNA transcripts. See analyses in the covid19 directory for additional information, as well as relevent works below.

Environment setup

After creating the rnagps environment using

conda env create -f environment.yml

Install xgboost with

conda install -c conda-forge xgboost=0.82

Relevant works

• Wu, K.E., Parker, K.R., Fazal, F.M., Chang, H., and Zou, J. (2020). RNA-GPS predicts high-resolution RNA subcellular localization and highlights the role of splicing. RNA.
• Wu, K.E., Fazal, F.M., Parker, K.R., Zou, J., and Chang, H.Y. (2020). RNA-GPS Predicts SARS-CoV-2 RNA Residency to Host Mitochondria and Nucleolus. Cell Systems.