compara-deep-learning

Using Deep Learning techniques to enhance orthology calls

This project aims to apply machine learning algorithms like Deep Learning Neural Networks to validate the homologies predicted with our method in addition to infer new ones based on other properties of the data that are currently not being considered (such as local synteny, divergence rates, etc).

Run the ftpg.py directly to get the links of the files in the ftp server to be downloaded. Enter y when prompted to download the files to the files. The directories to which the files are downloaded can be modified in the script.

The command line arguments are as follows:
-f read the links from the file and download it
-d read the files in the given directory
-nd ignore this argument(do nothing)
-l download file from the link. Works only for homology file
-r or -d to specify to download and read or just download data
-test or -run to test the files and the code or run it.

For Example:
python main.py -f link.txt -d data_homology -r -test will download the files given by the links in the file link.txt to the data directory and read the downloaded files.It will also read all the files in the data_homology directory. The last argument shows that the data will be downloaded as well as read. All the files will be read and selective records will be processed.

At this moment the model has been designed to work with only one homology database. Functionality will be updated during the course of the project.

The neighbor genes for all the genes in the Homo_Sapien homology database has been processed and can be found here:https://drive.google.com/drive/folders/1x3rdT-B8LLjxHqQH14a9nivtcv-IUlgz?usp=sharing