Prot-Search

Computational Genomics Final Project - Shreyas Aiyar, Debanik Purkayastha, Ishita Tripathi

Table of Contents

• Table of Contents
• Directory Structure
• Requirements
• Web App
• Testing
• Misc

Directory Structure

.
├── api
    ├── matching
        ├── index_assisted_dp.py                        # Index Assisted DP algorithm implementation
        ├── neighbourhood.py                            # Neighbourhood search algorithm implementation
        ├── pigeonhole_principle_approximate_match.py   # L-mer filtration algorithm implementation
        ├── six_frame_translation.py                    # Six frame translation implementation
        ├── blast.py                                    # Trial implementation of blast.py
    ├── api.py
├── client                                              # Web app files
├── tests
    ├── data_generation.py                              # Script to generate test reads
    ├── kmer_dict_tests.py                              # Test script to compare kmer dictionary sizes and creation runtime for different k's and number of proteins. 
    ├── test_suite.py                                   # Test script to run and benchmark algorithms
├── scripts
    ├── kmers.py                                        # Script to generate L-mer dictionary file
    ├── proteins.py                                     # Script to generate protein id dictionary file
├── data                                                # Stores supporting dictionary files in .pickle format
├── contributions.txt
├── recording                                           # Screen recording of the web app
└── README.md

Requirements

To run the web app specifically, make sure your machine has Node.js installed. After installing Node.js, make sure that yarn is accessible as a package manager.

Node.js - https://nodejs.org/en/download/
yarn - https://classic.yarnpkg.com/en/docs/install/#mac-stable

Also, to generate some supporting files, you would require the Uniprot FASTA file which can be downloaded from:
Uniprot FASTA File - ftp://ftp.uniprot.org/pub/databases/uniprot/current_release/knowledgebase/complete/uniprot_sprot.fasta.gz

Place the Uniprot File in /data directory once downloaded

Web-App

To start server

From root directory

cd api && pip install -r requirements.txt && flask run

To start client

From root directory

cd client && yarn install && yarn start

Testing

Generating Synthetic Reads

cd tests
python3 data_generation.py --infile ../data/uniprot_sprot.fasta --seed 1 --num_errors 4 --num_reads 5 --read_length 60 --no-gaps
cd ..

Benchmarking/Profiling Algorithms

Note: Generate synthetic reads prior to this
Smaller values of L would take a while to run

cd tests
python3 test_suite.py --infile test_reads.txt --mm 4 --l 4
cd ..

Testing L-Mer Dictionary

cd tests
python3 kmer_dict_tests.py
cd ..

Misc

Generating L-mer Dictionary File

cd scripts
python3 kmers.py --infile ../data/protein_dict_num_prots_100.pickle -k 5 -n 100
cd ..

Generating Protein Dictionary File

cd scripts
python3 proteins.py --infile ../data/uniprot_sprot.fasta --num_proteins 100
cd ..

Neighborhood search for a sequence [PROT_SEQ]

cd api/matching
python3 neighborhood.py -i [PROT_SEQ] -m 1 -t 17
cd ../../

Note: The query files have sample usage given as comments at the top of the file. They can be run independently as well.