prPred is a tool to identify the plant resistance proteins (R proteins)
prPred is an open-source Python-based toolkit, which operates depending on the Python environment (Python Version 3.0 or above). Before running prPred, user should make sure all the following packages are installed in their Python environment: subprocess, datetime, os, shutil, pandas,numpy, Biopython,sklearn,optparse
To obtain HMMER releases, please visit http://hmmer.org/. We also provide HMMER zipped folders for download in prPred
<prPred need to make sure that the HMMER is in the environment variable>
sudo apt-get install hmmer
Download and build the source code release(optional)
wget http://eddylab.org/software/hmmer/hmmer.tar.gz
tar zxf hmmer.tar.gz
cd hmmer-3.3.2
./configure --prefix /your/install/path
make
make check
make install
vim ~/.bashrc
i
export PATH=$PATH:/your/install/path
:wq!
source ~/.bashrc
Phobius:prediction of transmembrane topology and signal peptides from the amino acid sequence of a protein. To obtain phobius releases, please visit https://phobius.sbc.su.se/data.html.
installation procedure https://www.jianshu.com/p/32176552cb5c
<The software will be shipped immediately in the form of an attachment to the e-mail address you specify below>
tar -xzvf phobius101_linux.tar.gz
cd /xxxx/xxxx/xxxx/tmp/tmpbKioAY/phobius
'''
Error - could not read provided fasta sequences
Modify line 24 in phobius.pl
my $DECODEANHMM = "$PHOBIUS_DIR/decodeanhmm.64bit"
'''
Add phobius into environment variables (~/.bashrc)
export PATH=$PATH:/xxxx/xxxx/xxxxx/tmp/tmpbKioAY/phobius
To obtain Pfam database,please download from ftp://ftp.ebi.ac.uk/pub/databases/Pfam/current_release/Pfam-A.hmm.gz
mkdir Pfam
cd Pfam
wget ftp://ftp.ebi.ac.uk/pub/databases/Pfam/current_release/Pfam-A.hmm.gz
gunzip Pfam-A.hmm.gz
hmmpress Pfam-A.hmm
'''
After hmmpress, we will get four files: Pfam-A.hmm.h3f，Pfam-A.hmm.h3i，Pfam-A.hmm.h3m，Pfam-A.hmm.h3p
'''
Add PFAMDB (Pfam-A.hmm.h3f，Pfam-A.hmm.h3i，Pfam-A.hmm.h3m，Pfam-A.hmm.h3p) into environment variables
vim ~/.bashrc**
export PFAMDB=/xxxx/xxxx/xxxx/Pfam
To obtain iFeature, please download from https://github.com/Superzchen/iFeature/.
Add iFeature into environment variables (~/.bashrc)
export PATH=$PATH:/xxxx/xxxx/xxxxx/iFeature
###prPred
git clone git@github.com:Wangys-prog/prPred.git
Add prPred into into environment variables
(./prPred/dist/prPred)
export PATH=$PATH:/xxxx/xxxx/xxxx/prPred/dist/prPred
prPred -h
$ -i inputfile in FASTA format
$ -o output folder
prPred -i /xxxx/xxxx/test/test.fasta -o result
or Using absolute path to invoke prPred.py (/xxxx/xxxx/prPred/prPred.py) ,this command run using python3.7
python 3.7 xxxx/xxxx/prPred/prPred.py -i /xxxx/xxxx/test/test.fasta -o /xxxx/xxxxx/result
###Output file
domain_result
R_protein_possibility.fasta
Analyze your sequences such as 20 sequences
Before using the script,please add prPred into into environment variables
split your large fasta file into small fasta file with such as 20 sequence
if you fasta has total 100 sequences,you can split you fasta into 5 small fasta files
seqkit split your.fasta -p 5
then using split_fasta2.py to predict R protein sequences
python split_fasta.py -i your split_fasta folder
merge your result
python merge_result.py -i split_fasta_result -o merged_result.csv
Download Ubuntu xx.x LTS from Microsoft Store
cd ../../
cd mnt/x/xxxx/xxxx/
git clone git@github.com:Wangys-prog/prPred.git
cd mnt/x/xxxx/xxxx/prPred/
(1) Wang Y, Wang P, Guo Y, et al. prPred: A Predictor to Identify Plant Resistance Proteins by Incorporating k-Spaced Amino Acid (Group) Pairs[J]. Frontiers in bioengineering and biotechnology, 2021, 8: 1593.
(2) Yansu Wang, Murong Zhou, Quan Zou, Lei Xu. Machine learning for phytopathology: from the molecular scale towards the network scale. Briefings in Bioinformatics. 2021, Doi: 10.1093/bib/bbab037
(3) Yansu Wang, Lei Xu, Quan Zou, Chen Lin. prPred-DRLF: plant R protein predictor using deep representation learning features. Proteomics. 2021. DOI: 10.1002/pmic.202100161