SLPred: a multi-view subcellular localization prediction tool for multi-location human proteins

• SLPred is a multi-view subcellular localization prediction tool for human proteins.

• The tool consists of nine independently developed model for the proteins which have annotation with nine subcellular locations: Cytoplasm, Nucleus, Cell Membrane, Mitochondrion, Secreted, Endoplasmic reticulum, Golgi apparatus, Lysosome and Peroxisome.

• SLPred exploits the features of forty different protein descriptors from the publicly available tools: POSSUM, iFeature and SPMAP.

• Support Vector Machine (SVM) is used to construct probabilistic prediction models, which produces probabilistic scores indicating the localization probability for a query protein sequence.

• A weighted score is calculated based on the obtained probabilistic scores from seven feature-based probabilistic prediction models (SVMs) by employing weighted mean voting.

• Binary prediction is given by applying thresholding on the weighted score.

• The following figure shows the proposed method

Installation

SLPred is a command-line prediction tool written in Python 3.7.1. SLPred was developed and tested in Ubuntu 20.04 LTS. Please make sure that you have Anaconda installed on your computer and run the below commands to install requirements. Dependencies are available in requirements.txt file.

conda create -n slpred_env python=3.7
conda activate slpred_env

How to run SLPred to obtain the predictions

Preparation to run SLPred

• Clone the Git Repository
• In terminal or command line navigate into SLPred folder
• Then run the following commands

pip install -r requirements.txt
chmod +x download_extract_data.sh
./download_extract_data.sh

Input file

• The input file must be located under input_files/fasta_files folder.
• It must be in fasta format
• A sample is also given as input_files/fasta_files/input.fasta

Explanation of Parameters

• --file: this is the file name of the fasta file. For example if fasta file name is input.fasta, this argument must be just input

The command to run SLPred is as follows:

python run_SLPred.py --file input 

Output file

• The results (predictions) will be located under predictions folder with the name: input_predictions.csv
• The prediction is indicated with 1 (positive) and 0 (negative) for the corresponding location in the output file

License

SLPred Copyright (C) 2020 CanSyL

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.