DeepSig - Predictor of signal peptides in proteins based on deep learning
Project description
DeepSig - Predictor of signal peptides in proteins based on deep learning
Publication
Savojardo C., Martelli P.L., Fariselli P., Casadio R. DeepSig: deep learning improves signal peptide detection in proteins Bioinformatics (2017) 34(10): 1690-1696.
Installation using pip
First, install deepsig-biocomp package using pip:
pip install deepsig-biocomp
Then, clone the deepsig repo from GitHub and export the DEEPSIG_ROOT directory:
git clone git@github.com:BolognaBiocomp/deepsig.git
cd deepsig
export DEEPSIG_ROOT=$(pwd)
Usage
$ deepsig -h
usage: deepsig.py [-h] -f FASTA -o OUTF -k {euk,gramp,gramn} [-a CPU]
DeepSig: Predictor of signal peptides in proteins
optional arguments:
-h, --help show this help message and exit
-f FASTA, --fasta FASTA
The input multi-FASTA file name
-o OUTF, --outf OUTF The output tabular file
-k {euk,gramp,gramn}, --organism {euk,gramp,gramn}
The organism the sequences belongs to
The program accepts three mandatory arguments:
- The full path of the input FASTA file containing protein sequences to be predicted;
- The kingdom the sequences belong to. You must specify "euk" for Eukaryotes, "gramp" for Gram-positive bacteria or "gramn" for Gram-negative bacteria;
- The output file where predictions will be stored.
Please, reports bugs to: castrense.savojardo2@unibo.it
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