Scripts for calculating features from genomic sequences, multiple linear regression of those features to the originating species' Optimal Growth Temperatures (OGT), and prediction of a species' OGT using those linear regression models.
See: Sauer & Wang. Predicting the optimal growth temperatures of prokaryotes using only genome derived features. Bioinformatics (2019) https://doi.org/10.1093/bioinformatics/btz059
This has been developed and tested on Ubuntu 18.04 LTS. The scripts should work on any system supporting Python 3, so long as the external programs are installed properly.
- Download these scripts. This is easiest using git to clone the repository.
git clone https://github.com/DavidBSauer/OGT_prediction
- Install the requirements. These scripts depend upon the programs: Python3, tRNAscan-SE, Bedtools, Barrnap, and Prodigal. These have their own dependencies also. The following python packages also need to be installed: numpy, scipy, matplotlib, biopython, bcbio-gff, tqdm, sklearn, matplotlib, and matplotlib-venn.
To install everything in Ubuntu (or other system that use the apt package manager), go into the downloaded directory and use the pre-made bash script.
cd OGT_prediction
./Ubuntu_setup.bash
If you're on another OS, install all the python packages. Then install bedtools, tRNAscan-SE, barrnap, and prodigal; and all their dependencies. Create a file called external_tools.txt listing bedtools, tRNAscan-SE, barrnap, and prodigal tab separated from the absolute path for each executable. Copy this external_tools.txt file into the feature_calculation and prediction directories.
This uses the previously computed regression models to predict OGTs for a few species. Start within the prediction directory.
- Move into the prediction directory.
cd prediction
- Download genomes species IN the provided list.
python3 genome_retriever.py ../data/prediction_demo/species.txt IN
- Download taxonomic classification for species.
python3 clade_retriever.py ../data/prediction_demo/species.txt your_email_address@awesome.com
- Run the prediction script to predict the OGT of each species.
python3 prediction_pipeline.py ../data/prediction_demo/regression_models/ genomes_retrieved.txt species_taxonomic.txt
The final result will be in the file newly_predicted_OGTs.txt, listing each species, the predicted OGT, and the taxonomic model used for the prediction. (Note, these results are not deterministic as the genomes available for each species may change.)