A tool to compute the features of protein and peptide sequences
Project description
Pfeature
Introduction
Pfeature is developed for computing wide range of protein and peptides features from their amino acid sequences. More information on Pfeature is available from its web server https://webs.iiitd.edu.in/raghava/pfeature. This page provide information about standalone version of Pfeature. This standalone contains three scripts, their description is as follows:
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1: Standalone for calculating composition based features:
Important: To run this script 'Data' folder should be in the same directory.
Minimum USAGE: Minimum ussage is "pfeature_comp.py -i protein.fa" where protein.fa is a input fasta file. This will calculate the amino acid composition of the seqeunces provided in the fasta file. It will use other parameters by default. It will save output in "pfeature_result.csv" in CSV (comma seperated variables).
#Full Usage: Following is complete list of all options, you may get these options by "pfeature_comp.py -h" usage: pfeature_comp.py [-h] -i INPUT [-o OUTPUT] [-j {AAC,DPC,TPC,ATC,BTC,PCP,AAI,RRI,PRI,DDR,SEP,SER,SPC,ACR,CTC,CeTD,PAAC,APAAC,QSO,SOC,ALLCOMP}] [-n N_TERMINAL] [-c C_TERMINAL] [-nct NC_TERMINAL] [-rn REST_N] [-rc REST_C] [-s SPLIT] [-d LAG] [-w WEIGHT] [-t PWEIGHT]
optional arguments: -h, --help show this help message and exit -i INPUT, --input INPUT Input: protein or protein.sequence in FASTA format or single sequence per line in single letter code -o OUTPUT, --output OUTPUT Output: File for saving results by default pfeature_result.csv -j {AAC,DPC,TPC,ATC,BTC,PCP,AAI,RRI,PRI,DDR,SEP,SER,SPC,ACR,CTC,CeTD,PAAC,APAAC,QSO,SOC,ALLCOMP}, --job {AAC,DPC,TPC,ATC,BTC,PCP,AAI,RRI,PRI,DDR,SEP,SER,SPC,ACR,CTC,CeTD,PAAC,APAAC,QSO,SOC,ALLCOMP} Job Type: AAC: Amino acid composition DPC: Dipeptide composition TPC: Tripeptide composition ATC: Atomic composition BTC: Bond composition PCP: Physico-chemical properties composition AAI: Amino-acid indices composition RRI: Residue repeat information PRI: Physico-chemical properties repeat information DDR: Distance distribution of residues SEP: Shannon entropy of protein SER: Shannon entropy of residues SPC: Shannon entropy of physico-chemical properties ACR: Autocorrelation descriptors CTC: Conjoint triad descriptors CeTD: Composition enhanced transition distribution PAAC: Pseudo amino acid composition APAAC: Amphiphilic pseudo amino acid composition QSO: Quasi sequence order SOC: Sequence order coupling number ALLCOMP:All composition features together except ACR and AAI by default AAC -n N_TERMINAL, --n_terminal N_TERMINAL Window Length from N-terminal: by default 0 -c C_TERMINAL, --c_terminal C_TERMINAL Window Length from C-terminal: by default 0 -nct NC_TERMINAL, --nc_terminal NC_TERMINAL Residues from N- and C-terminal: by default 0 -rn REST_N, --rest_n REST_N Number of residues removed from N-terminal, by default 0 -rc REST_C, --rest_c REST_C Number of residues removed from C-terminal, by default 0 -s SPLIT, --split SPLIT Number of splits a sequence divided into, by default 0 -d LAG, --lag LAG This represents the order of gap, lag or dipeptide, by default 1 -w WEIGHT, --weight WEIGHT Weighting Factor for QSO: Value between 0 to 1, by default 0.1 -t PWEIGHT, --pweight PWEIGHT Weighting factor for pseudo and amphiphlic pseudo amino acid composition: Value between 0 to 1, by default 0.05
#Parameters Description:
Input File: It allow users to provide input in two format; i) FASTA format (standard) (e.g. protein.fa) ii) Simple Format, in this case, file should have sequences in a single line in single letter code (eg. protein.seq).
Output File: Program will save result in CSV format, in the provided filename. In case user do not provide output file name, it will be stored in pfeature_results.csv. In case user want to calculate all the features except AAI and ACR, the job name will be 'ALLCOMP'. Reason to leave AAI and ACR is, the feature calculation takes long time for longer sequences.
Job name: It allows users to choose the type of composition, the user want to calculate, such as AAC which stands for Amino Acid composition. In case user do not provide any job name, it will choose AAC by default.
N-terminal: It allows user to cut the specific number of residues from the N-terminal of the sequences.
C-terminal: It allows user to cut the specific number of residues from the C-terminal of the sequences.
NCT-terminal: It allows user to cut the specific number of residues from the N- and C-terminal of the sequences, and join them.
Rest_N : It allow users to drop the specific number of residues from N-terminal, and perform operations on the rest.
Rest_C : It allow users to drop the specific number of residues from C-terminal, and perform operations on the rest.
Split: It allow users to divided the sequence into number of sequences.
Lag : It defines the value for order of lag, lambda, gap or dipeptide, to calculate certain features.
Weight: It defines the weight factor to calculate the quasi-sequence order, by default it is set at 0.1.
Pweight: It defines the weight factor to calculate the pseudo and amphiphlic pseudo amino acid composition, by default it is set at 0.05.
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2: Standalone for calculating binary profiles based features:
Important: To run this script 'Data' folder should be in the same directory.
Minimum USAGE: Minimum ussage is "pfeature_bin.py -i protein.fa" where protein.fa is a input fasta file. This will calculate the amino acid binary profile of the seqeunces provided in the fasta file. It will use other parameters by default. It will save output in "pfeature_result.csv" in CSV (comma seperated variables).
usage: pfeature_bin.py [-h] -i INPUT [-o OUTPUT] [-j {AAB,DPB,ATB,BTB,PCB,AIB,ALLBIN}] [-n N_TERMINAL] [-c C_TERMINAL] [-nct NC_TERMINAL] [-rn REST_N] [-rc REST_C] [-s SPLIT] [-d LAG]
Please provide following arguments
optional arguments: -h, --help show this help message and exit -i INPUT, --input INPUT Input: protein or protein.sequence in FASTA format or single sequence per line in single letter code -o OUTPUT, --output OUTPUT Output: File for saving results by default pfeature_result.csv -j {AAB,DPB,ATB,BTB,PCB,AIB,ALLBIN}, --job {AAB,DPB,ATB,BTB,PCB,AIB,ALLBIN} Job Type: AAB: Amino acid based binary profile DPB: Dipeptide based binary profile ATB: Atom based binary profile BTB: Bond based binary profile PCB: Physico-chemical properties based binary profile AIB: Amino-acid indices based binary profile ALLBIN:All binary profiles together except ATB and BTB by default AAB -n N_TERMINAL, --n_terminal N_TERMINAL Window Length from N-terminal: by default 0 -c C_TERMINAL, --c_terminal C_TERMINAL Window Length from C-terminal: by default 0 -nct NC_TERMINAL, --nc_terminal NC_TERMINAL Residues from N- and C-terminal: by default 0 -rn REST_N, --rest_n REST_N Number of residues removed from N-terminal, by default 0 -rc REST_C, --rest_c REST_C Number of residues removed from C-terminal, by default 0 -s SPLIT, --split SPLIT Number of splits a sequence divided into, by default 0 -d LAG, --lag LAG This represents the order of gap, lag or dipeptide, by default 1
#Parameters Description:
Input File: It allow users to provide input in two format; i) FASTA format (standard) (e.g. protein.fa) ii) Simple Format, in this case, file should have sequences in a single line in single letter code (eg. protein.seq).
Output File: Program will save result in CSV format, in the provided filename. In case user do not provide output file name, it will be stored in pfeature_results.csv. In case user want to calculate all the features except ATB and BTB, the job name will be 'ALLBIN'. Reason to leave ATB and BTB is, the number of atoms and bonds are not equal in all amino acid residues.
Job name: It allows users to choose the type of composition, the user want to calculate, such as AAB which stands for Amino Acid based binary profile. In case user do not provide any job name, it will choose AAB by default.
N-terminal: It allows user to cut the specific number of residues from the N-terminal of the sequences.
C-terminal: It allows user to cut the specific number of residues from the C-terminal of the sequences.
NCT-terminal: It allows user to cut the specific number of residues from the N- and C-terminal of the sequences, and join them.
Rest_N : It allow users to drop the specific number of residues from N-terminal, and perform operations on the rest.
Rest_C : It allow users to drop the specific number of residues from C-terminal, and perform operations on the rest.
Split: It allow users to divided the sequence into number of sequences.
Lag : It defines the value for order of dipeptide, to calculate the dipeptide based binary profiles.
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3: Standalone for calculating PSSM profile
Important: To run this script a file with the file name 'envfile' is required.
This envfile contains paths for the following scripts/data: i) Path for blastpgp ii) Path for blast database iii) Path for makemat
Minimum USAGE: Minimum ussage is "pfeature_pssm.py -i protein.fa" where protein.fa is a input fasta file. This will calculate the PSSM profile of the seqeunces provided in the fasta file. It will use other parameters by default. It will save output in "pssm_profile.csv" in CSV (comma seperated variables).
-h, --help show this help message and exit -i INPUT, --input INPUT Input: protein or peptide sequence in FASTA format or single sequence per line in single letter code -o OUTPUT, --output OUTPUT Output: File for saving results by default pssm_profile.csv -n {N0,N1,N2,N3,N4}, --normalization_method {N0,N1,N2,N3,N4} Normalization Method: N0: It provides pssm profile without any normalization N1: It normalizes pssm profile based on 1/(1+e^-x) formula N2: It normalizes pssm profile based on (x-min)/(max-min) formula N3: It normalizes pssm profile based on ((x-min)/(max-min))*100 formula N4: It normalizes pssm profile based on 1/(1+e^-(x/100) formula By default it is N0
#Parameters Description:
Input File: It allow users to provide input in two format; i) FASTA format (standard) (e.g. protein.fa) ii) Simple Format, in this case, file should have sequences in a single line in single letter code (eg. protein.seq).
Output File: Program will save result in CSV format, in the provided filename. In case user do not provide output file name, it will be stored in pssm_profile.csv
Normalization methods: It allows user to normalize the PSSM profiles using four different formula. The description is as follows: N0: It provides pssm profile without any normalization N1: It normalizes pssm profile based on 1/(1+e^-x) formula N2: It normalizes pssm profile based on (x-min)/(max-min) formula N3: It normalizes pssm profile based on ((x-min)/(max-min))*100 formula N4: It normalizes pssm profile based on 1/(1+e^-(x/100) formula By default it is N0
Pfeature Package Files
It contantain following files, brief description of these files are given below:
LICENSE : License information
README.md : This file provide information about this package
pfeature_comp.py : Python program to calculate composition based features
pfeature_bin.py : Python program to calculate binary profile based features
pfeature_pssm.py : Python program to calculate pssm profile based features
protein.seq : Example file contain protein sequences in simple format
protein.fa : Example file contain protein sequences in FASTA format
Data : This folder contains the files required to calcuate the composition and binary profile based features.
envfile : This file contains the path information required to run the pfeature_pssm.py script.
Pfeature_Descriptors.pdf : This file comprises of description of the header of output files, which is generated using the aforementioned scripts.
Requirement.txt : This file consists of commands and pre-requisite to run the aforementioned scripts.
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