From 94473306b5ca0427bda5c16e0fb0f66bd831e27f Mon Sep 17 00:00:00 2001 From: HarshitGupta11 <50410275+HarshitGupta11@users.noreply.github.com> Date: Sat, 22 Jun 2019 20:44:36 +0530 Subject: [PATCH] Update README.md --- README.md | 50 ++++++++++++++++++++++++++++++++++---------------- 1 file changed, 34 insertions(+), 16 deletions(-) diff --git a/README.md b/README.md index 6f5f2f8..e6004c3 100644 --- a/README.md +++ b/README.md @@ -1,21 +1,39 @@ -# compara-deep-learning -Using Deep Learning techniques to enhance orthology calls +# New Readme -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). +The aim of this project is to use **Deep Neural-Nets** to predict homology type between the give pair of genes. +This file provides the instructions to replicate the results of this project from scratch. -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. +## Requirements: +1. A machine with atleast **8GB of RAM** (although **16-32GB** is recommended. It depends on the no. of homology databases that you are willing to use in the preparation of the dataset), a graphic card for training the deep neural nets. A single GPU machine would suffice. The model can be trained on CPU as well but will be a lot faster if trained on a GPU. +2. A stable Internet Connection. +3. A native/virtual python environment. Install the dependencies from `requirements.txt` using : + `pip install -r requirements.txt` -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.
+## Step 1: Data Preparation: +The model uses a synteny matrix and some other factors derived from the species tree to make predictions. +**Download The Required Files:** +So as to prepare data we will need the following files: +1.All the `gtf` files so as to get the start and end locations of the genes and find their neighboring genes. This is used to create the synteny matrix which helps to see the conserved synteny among the genes. +2. All the `cds` files in `FAST-A` format. They are required but are not mandatory, if the files are not provided the sequences are directly accessed from the `REST API` but the process can be slow :( . It's better to have all the `cds` files. +3. Homology Databases of Your Choice. All the databases have the same name so its better to change the name of the files with their respective speicies names. One format that works best is `species_name.tsv.gz`. -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. +To download the `gtf` and `cds` files `ftpg.py` can be used. This scripts writes the links of all the required `gtf` and `cds` files to `gtf-link.txt` and `seq_link.txt`. You can use your own script to download the files or just enter `y` when prompted for permission to download the files. It will automatically download all the files and store them in designated folder. You can manually download each files by pasting link from the files in the browser. -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 +The designated folders to store the files are as follows: +`data` all the `gtf` files. +`data_homology` all the homology databases that you want to use. +`geneseq`To store the `cds` sequence files in `fasta` format. +You can assign different folder names if you want but it's better to stick to them. +**Create Genome Maps:** +The purpose is to create maps of all the genes present in the `gtf` files with respect to their chromosomes, a map of all the genes belonging to the same chromosome in the given species, a map of all the genes in the given species, a map of all the species whose data has been successfully read. +To create genome maps run this command: +`python create_genome_maps.py -d path -r` where: +`path`: link to the directory where all the `gtf` files exist. If you have used `ftpg.py` then the path is `data`. +Note: Genome Maps can be downloaded from this [link](https://drive.google.com/open?id=1GjV6dT-Hpf2LWQ-vSpekqqQ7RF_tH8So). +**Create/Update Neighbor Genes File:** +This project uses the measure of conserved synteny to predict the homology type. Therefore, to predict the homology type we need to find the neighboring genes of the given homologous pair of genes. +This file finds the neighboring genes of all the rows in the given databases and writes it to a file called `processed/neighbor_genes.json` . +To find the neighboring genes of the homologous genes in the databases run this command: +`python update_neighbor_genes.py -d path -r -test` to test the file for 5 samples or you can directly run: +`python update_neighbor_genes.py -d path -r -run`. +It will update/create the `neighbor_genes.json` file in the `processed` directory.