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iFeatureOmegaGUI.py
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iFeatureOmegaGUI.py
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#!/usr/bin/env python
# _*_ coding: utf-8 _*_
import os, sys, re
from matplotlib.pyplot import plot
pPath = os.path.split(os.path.realpath(__file__))[0]
sys.path.append(pPath)
from PyQt5.QtWidgets import (QApplication, QTableWidgetItem, QWidget, QTabWidget, QPushButton, QFileDialog, QLabel, QHBoxLayout, QGroupBox, QTextEdit,
QVBoxLayout, QLineEdit, QTreeWidget, QTreeWidgetItem, QFormLayout, QTableWidget, QHeaderView, QAbstractItemView,
QSplitter, QGridLayout, QMessageBox, QInputDialog)
from PyQt5.QtGui import QIcon, QFont, QMovie
from PyQt5.QtCore import Qt, pyqtSignal
from util import (InputDialog, PlotWidgets, TableWidget, iSequence, iStructure, iChemical, DataAnalysis, CheckAccPseParameter)
from rdkit import Chem
import qdarkstyle
import threading
import numpy as np
import pandas as pd
import tempfile
import time
import sip
import copy
class IFeatureOmegaGui(QTabWidget):
# 信号定义为类属性，不能放在__init__里面
# global signal
display_error_signal = pyqtSignal(str)
display_warning_signal = pyqtSignal(str)
# protein signal
protein_message_signal = pyqtSignal(str)
protein_display_signal = pyqtSignal()
# dna signal
dna_message_signal = pyqtSignal(str)
dna_display_signal = pyqtSignal()
# rna signal
rna_message_signal = pyqtSignal(str)
rna_display_signal = pyqtSignal()
# structure signal
structure_message_signal = pyqtSignal(str)
structure_display_signal = pyqtSignal()
# chemical signal
chemical_message_signal = pyqtSignal(str)
chemical_display_signal = pyqtSignal()
# analysis signal
analysis_message_signal = pyqtSignal(str)
analysis_display_signal = pyqtSignal()
# plot signal
plot_message_signal = pyqtSignal(str)
plot_display_signal = pyqtSignal()
def __init__(self):
super(IFeatureOmegaGui, self).__init__()
# gif
self.gif = QMovie(os.path.join(pPath, 'images', 'progress_bar.gif'))
self.working_dir = tempfile.mkdtemp()
self.display_error_signal.connect(self.display_error_msg)
self.display_warning_signal.connect(self.display_warning_msg)
# all
self.sample_labels = []
# Protein
self.protein_sequence_file = None
self.protein_selected_descriptors = set([])
self.protein_para_dict = {
'EAAC': {'sliding_window': 5},
'CKSAAP type 1': {'kspace': 3},
'CKSAAP type 2': {'kspace': 3},
'EGAAC': {'sliding_window': 5},
'CKSAAGP type 1': {'kspace': 3},
'CKSAAGP type 2': {'kspace': 3},
'AAIndex': {'aaindex': 'ANDN920101;ARGP820101;ARGP820102;ARGP820103;BEGF750101;BEGF750102;BEGF750103;BHAR880101'},
'NMBroto': {'aaindex': 'ANDN920101;ARGP820101;ARGP820102;ARGP820103;BEGF750101;BEGF750102;BEGF750103;BHAR880101', 'nlag': 3,},
'Moran': {'aaindex': 'ANDN920101;ARGP820101;ARGP820102;ARGP820103;BEGF750101;BEGF750102;BEGF750103;BHAR880101', 'nlag': 3,},
'Geary': {'aaindex': 'ANDN920101;ARGP820101;ARGP820102;ARGP820103;BEGF750101;BEGF750102;BEGF750103;BHAR880101', 'nlag': 3,},
'KSCTriad': {'kspace': 3},
'SOCNumber': {'nlag': 3},
'QSOrder': {'nlag': 3, 'weight': 0.05},
'PAAC': {'weight': 0.05, 'lambdaValue': 3},
'APAAC': {'weight': 0.05, 'lambdaValue': 3},
'DistancePair': {'distance': 0, 'cp': 'cp(20)',},
'AC': {'aaindex': 'ANDN920101;ARGP820101;ARGP820102;ARGP820103;BEGF750101;BEGF750102;BEGF750103;BHAR880101', 'nlag': 3},
'CC': {'aaindex': 'ANDN920101;ARGP820101;ARGP820102;ARGP820103;BEGF750101;BEGF750102;BEGF750103;BHAR880101', 'nlag': 3},
'ACC': {'aaindex': 'ANDN920101;ARGP820101;ARGP820102;ARGP820103;BEGF750101;BEGF750102;BEGF750103;BHAR880101', 'nlag': 3},
'PseKRAAC type 1': {'lambdaValue': 3, 'PseKRAAC_model': 'g-gap', 'g-gap': 2, 'k-tuple': 2, 'RAAC_clust': 1},
'PseKRAAC type 2': {'lambdaValue': 3, 'PseKRAAC_model': 'g-gap', 'g-gap': 2, 'k-tuple': 2, 'RAAC_clust': 1},
'PseKRAAC type 3A': {'lambdaValue': 3, 'PseKRAAC_model': 'g-gap', 'g-gap': 2, 'k-tuple': 2, 'RAAC_clust': 1},
'PseKRAAC type 3B': {'lambdaValue': 3, 'PseKRAAC_model': 'g-gap', 'g-gap': 2, 'k-tuple': 2, 'RAAC_clust': 1},
'PseKRAAC type 4': {'lambdaValue': 3, 'PseKRAAC_model': 'g-gap', 'g-gap': 2, 'k-tuple': 2, 'RAAC_clust': 1},
'PseKRAAC type 5': {'lambdaValue': 3, 'PseKRAAC_model': 'g-gap', 'g-gap': 2, 'k-tuple': 2, 'RAAC_clust': 1},
'PseKRAAC type 6A': {'lambdaValue': 3, 'PseKRAAC_model': 'g-gap', 'g-gap': 2, 'k-tuple': 2, 'RAAC_clust': 1},
'PseKRAAC type 6B': {'lambdaValue': 3, 'PseKRAAC_model': 'g-gap', 'g-gap': 2, 'k-tuple': 2, 'RAAC_clust': 1},
'PseKRAAC type 6C': {'lambdaValue': 3, 'PseKRAAC_model': 'g-gap', 'g-gap': 2, 'k-tuple': 2, 'RAAC_clust': 1},
'PseKRAAC type 7': {'lambdaValue': 3, 'PseKRAAC_model': 'g-gap', 'g-gap': 2, 'k-tuple': 2, 'RAAC_clust': 1},
'PseKRAAC type 8': {'lambdaValue': 3, 'PseKRAAC_model': 'g-gap', 'g-gap': 2, 'k-tuple': 2, 'RAAC_clust': 1},
'PseKRAAC type 9': {'lambdaValue': 3, 'PseKRAAC_model': 'g-gap', 'g-gap': 2, 'k-tuple': 2, 'RAAC_clust': 1},
'PseKRAAC type 10': {'lambdaValue': 3, 'PseKRAAC_model': 'g-gap', 'g-gap': 2, 'k-tuple': 2, 'RAAC_clust': 1},
'PseKRAAC type 11': {'lambdaValue': 3, 'PseKRAAC_model': 'g-gap', 'g-gap': 2, 'k-tuple': 2, 'RAAC_clust': 1},
'PseKRAAC type 12': {'lambdaValue': 3, 'PseKRAAC_model': 'g-gap', 'g-gap': 2, 'k-tuple': 2, 'RAAC_clust': 1},
'PseKRAAC type 13': {'lambdaValue': 3, 'PseKRAAC_model': 'g-gap', 'g-gap': 2, 'k-tuple': 2, 'RAAC_clust': 1},
'PseKRAAC type 14': {'lambdaValue': 3, 'PseKRAAC_model': 'g-gap', 'g-gap': 2, 'k-tuple': 2, 'RAAC_clust': 1},
'PseKRAAC type 15': {'lambdaValue': 3, 'PseKRAAC_model': 'g-gap', 'g-gap': 2, 'k-tuple': 2, 'RAAC_clust': 1},
'PseKRAAC type 16': {'lambdaValue': 3, 'PseKRAAC_model': 'g-gap', 'g-gap': 2, 'k-tuple': 2, 'RAAC_clust': 1},
}
self.protein_default_para = { # default parameter for descriptors
'sliding_window': 5,
'kspace': 3,
'props': ['CIDH920105', 'BHAR880101', 'CHAM820101', 'CHAM820102', 'CHOC760101', 'BIGC670101', 'CHAM810101', 'DAYM780201'],
'nlag': 3,
'weight': 0.05,
'lambdaValue': 3,
'PseKRAAC_model': 'g-gap',
'g-gap': 2,
'k-tuple': 2,
'RAAC_clust': 1,
'aaindex': 'ANDN920101;ARGP820101;ARGP820102;ARGP820103;BEGF750101;BEGF750102;BEGF750103;BHAR880101',
}
self.protein_descriptor = None
self.protein_message_signal.connect(self.protein_display_message)
self.protein_display_signal.connect(self.set_protein_table_content)
self.protein_encodings = None
self.protein_html_dict = {
'heatmap': None,
'boxplot': None,
}
# DNA
self.dna_sequence_file = None
self.dna_selected_descriptors = set([])
self.dna_para_dict = {
'Kmer type 1': {'kmer': 3},
'Kmer type 2': {'kmer': 3},
'RCKmer type 1': {'kmer': 3},
'RCKmer type 2': {'kmer': 3},
'Mismatch': {'kmer': 3, 'mismatch': 1},
'Subsequence': {'kmer': 3, 'delta': 0},
'ENAC': {'sliding_window': 5},
'CKSNAP type 1': {'kspace': 3},
'CKSNAP type 2': {'kspace': 3},
'DPCP': {'Di-DNA-Phychem': 'Twist;Tilt;Roll;Shift;Slide;Rise'},
'DPCP type2': {'Di-DNA-Phychem': 'Twist;Tilt;Roll;Shift;Slide;Rise'},
'TPCP': {'Tri-DNA-Phychem': 'Dnase I;Bendability (DNAse)'},
'TPCP type2': {'Tri-DNA-Phychem': 'Dnase I;Bendability (DNAse)'},
'DAC': {'Di-DNA-Phychem': 'Twist;Tilt;Roll;Shift;Slide;Rise', 'nlag': 3},
'DCC': {'Di-DNA-Phychem': 'Twist;Tilt;Roll;Shift;Slide;Rise', 'nlag': 3},
'DACC': {'Di-DNA-Phychem': 'Twist;Tilt;Roll;Shift;Slide;Rise', 'nlag': 3},
'TAC': {'Tri-DNA-Phychem': 'Dnase I;Bendability (DNAse)', 'nlag': 3},
'TCC': {'Tri-DNA-Phychem': 'Dnase I;Bendability (DNAse)', 'nlag': 3},
'TACC': {'Tri-DNA-Phychem': 'Dnase I;Bendability (DNAse)', 'nlag': 3},
'PseDNC': {'Di-DNA-Phychem': 'Twist;Tilt;Roll;Shift;Slide;Rise', 'weight': 0.05, 'lambdaValue': 3},
'PseKNC': {'Di-DNA-Phychem': 'Twist;Tilt;Roll;Shift;Slide;Rise', 'weight': 0.05, 'lambdaValue': 3, 'kmer': 3},
'PCPseDNC': {'Di-DNA-Phychem': 'Twist;Tilt;Roll;Shift;Slide;Rise', 'weight': 0.05, 'lambdaValue': 3},
'PCPseTNC': {'Tri-DNA-Phychem': 'Dnase I;Bendability (DNAse)', 'weight': 0.05, 'lambdaValue': 3},
'SCPseDNC': {'Di-DNA-Phychem': 'Twist;Tilt;Roll;Shift;Slide;Rise', 'weight': 0.05, 'lambdaValue': 3},
'SCPseTNC': {'Tri-DNA-Phychem': 'Dnase I;Bendability (DNAse)', 'weight': 0.05, 'lambdaValue': 3},
'NMBroto': {'nlag': 3, 'Di-DNA-Phychem': 'Twist;Tilt;Roll;Shift;Slide;Rise',},
'Moran': {'nlag': 3, 'Di-DNA-Phychem': 'Twist;Tilt;Roll;Shift;Slide;Rise',},
'Geary': {'nlag': 3, 'Di-DNA-Phychem': 'Twist;Tilt;Roll;Shift;Slide;Rise',},
}
self.dna_default_para = { # default parameter for descriptors
'kmer': 3,
'sliding_window': 5,
'kspace': 3,
'mismatch': 1,
'delta': 0,
'Di-DNA-Phychem': 'Twist;Tilt;Roll;Shift;Slide;Rise',
'Tri-DNA-Phychem': 'Dnase I;Bendability (DNAse)',
'distance': 0,
'cp': 'cp(20)',
'nlag': 3,
'lambdaValue': 3,
'weight': 0.05,
}
self.dna_descriptor = None
self.dna_message_signal.connect(self.dna_display_message)
self.dna_display_signal.connect(self.set_dna_table_content)
self.dna_encodings = None
# RNA
self.rna_sequence_file = None
self.rna_selected_descriptors = set([])
self.rna_para_dict = {
'Kmer type 1': {'kmer': 3},
'Kmer type 2': {'kmer': 3},
'RCKmer': {'kmer': 3},
'Mismatch': {'kmer': 3, 'mismatch': 1},
'Subsequence': {'kmer': 3, 'delta': 0},
'ENAC': {'sliding_window': 5},
'CKSNAP type 1': {'kspace': 3},
'CKSNAP type 2': {'kspace': 3},
'DPCP': {'Di-RNA-Phychem': 'Rise (RNA);Roll (RNA);Shift (RNA);Slide (RNA);Tilt (RNA);Twist (RNA)'},
'DPCP type2': {'Di-RNA-Phychem': 'Rise (RNA);Roll (RNA);Shift (RNA);Slide (RNA);Tilt (RNA);Twist (RNA)'},
'DAC': {'Di-RNA-Phychem': 'Rise (RNA);Roll (RNA);Shift (RNA);Slide (RNA);Tilt (RNA);Twist (RNA)', 'nlag': 3},
'DCC': {'Di-RNA-Phychem': 'Rise (RNA);Roll (RNA);Shift (RNA);Slide (RNA);Tilt (RNA);Twist (RNA)', 'nlag': 3},
'DACC': {'Di-RNA-Phychem': 'Rise (RNA);Roll (RNA);Shift (RNA);Slide (RNA);Tilt (RNA);Twist (RNA)', 'nlag': 3},
'PseDNC': {'Di-RNA-Phychem': 'Rise (RNA);Roll (RNA);Shift (RNA);Slide (RNA);Tilt (RNA);Twist (RNA)', 'weight': 0.05, 'lambdaValue': 3},
'PseKNC': {'Di-RNA-Phychem': 'Rise (RNA);Roll (RNA);Shift (RNA);Slide (RNA);Tilt (RNA);Twist (RNA)', 'weight': 0.05, 'lambdaValue': 3, 'kmer': 3},
'PCPseDNC': {'Di-RNA-Phychem': 'Rise (RNA);Roll (RNA);Shift (RNA);Slide (RNA);Tilt (RNA);Twist (RNA)', 'weight': 0.05, 'lambdaValue': 3},
'SCPseDNC': {'Di-RNA-Phychem': 'Rise (RNA);Roll (RNA);Shift (RNA);Slide (RNA);Tilt (RNA);Twist (RNA)', 'weight': 0.05, 'lambdaValue': 3},
'NMBroto': {'nlag': 3, 'Di-RNA-Phychem': 'Rise (RNA);Roll (RNA);Shift (RNA);Slide (RNA);Tilt (RNA);Twist (RNA)'},
'Moran': {'nlag': 3, 'Di-RNA-Phychem': 'Rise (RNA);Roll (RNA);Shift (RNA);Slide (RNA);Tilt (RNA);Twist (RNA)'},
'Geary': {'nlag': 3, 'Di-RNA-Phychem': 'Rise (RNA);Roll (RNA);Shift (RNA);Slide (RNA);Tilt (RNA);Twist (RNA)'},
}
self.rna_default_para = { # default parameter for descriptors
'sliding_window': 5,
'kspace': 3,
'kmer': 3,
'mismatch': 1,
'delta': 0,
'Di-RNA-Phychem': 'Rise (RNA);Roll (RNA);Shift (RNA);Slide (RNA);Tilt (RNA);Twist (RNA)',
'distance': 0,
'cp': 'cp(20)',
'nlag': 3,
'lambdaValue': 3,
'weight': 0.05,
}
self.rna_descriptor = None
self.rna_message_signal.connect(self.rna_display_message)
self.rna_display_signal.connect(self.set_rna_table_content)
self.rna_encodings = None
# Structure
self.structure_file = None
self.structure_selected_descriptors = None
self.structure_para_dict = {}
self.structure_default_para = { # default parameter for descriptors
'residue_shell': (3, 30, 3),
'atom_shell': (1, 10, 1),
}
self.structure_descriptor = None
self.structure_message_signal.connect(self.structure_display_message)
self.structure_display_signal.connect(self.set_structure_table_content)
self.structure_encodings = None
self.structure_tmpdir = None
# Chemical
self.chemical_smiles_file = None
self.chemical_selected_descriptors = set([])
self.chemical_message_signal.connect(self.chemical_display_message)
self.chemical_display_signal.connect(self.set_chemical_table_content)
self.chemical_descriptor = None
self.chemical_encodings = None
self.chemical_default_parameters = {
'Constitution': ['nhyd', 'nhal', 'nhet', 'nhev', 'ncof', 'ncocl', 'ncobr', 'ncoi', 'ncarb', 'nphos', 'nsulph', 'noxy', 'nnitro', 'nring', 'nrot', 'ndonr', 'naccr', 'nsb', 'ndb', 'ntb', 'naro', 'nta', 'AWeight', 'PC1', 'PC2', 'PC3', 'PC4', 'PC5', 'PC6'],
'Topology': ['AW', 'J', 'Thara', 'Tsch', 'Tigdi', 'Platt', 'Xu', 'Pol', 'Dz', 'Ipc', 'BertzCT', 'GMTI', 'ZM1', 'ZM2', 'MZM1', 'MZM2', 'Qindex', 'diametert', 'radiust', 'petitjeant', 'Sito', 'Hato', 'Geto', 'Arto'],
'Connectivity': ['Chi0', 'Chi1', 'mChi1', 'Chi2', 'Chi3', 'Chi4', 'Chi5', 'Chi6', 'Chi7', 'Chi8', 'Chi9', 'Chi10', 'Chi3c', 'Chi4c', 'Chi4pc', 'Chi3ch', 'Chi4ch', 'Chi5ch', 'Chi6ch', 'Chiv0', 'Chiv1', 'Chiv2', 'Chiv3', 'Chiv4', 'Chiv5', 'Chiv6', 'Chiv7', 'Chiv8', 'Chiv9', 'Chiv10', 'dchi0', 'dchi1', 'dchi2', 'dchi3', 'dchi4', 'Chiv3c', 'Chiv4c', 'Chiv4pc', 'Chiv3ch', 'Chiv4ch', 'Chiv5ch', 'Chiv6ch', 'knotpv', 'knotp'],
'Kappa': ['kappa1', 'kappa2', 'kappa3', 'kappam1', 'kappam2', 'kappam3', 'phi'],
'EState': ['value', 'max', 'min', 'Shev', 'Scar', 'Shal', 'Shet', 'Save', 'Smax', 'Smin', 'DS'],
'Autocorrelation-moran': ['MATSm1', 'MATSm2', 'MATSm3', 'MATSm4', 'MATSm5', 'MATSm6', 'MATSm7', 'MATSm8',
'MATSv1', 'MATSv2', 'MATSv3', 'MATSv4', 'MATSv5', 'MATSv6', 'MATSv7', 'MATSv8',
'MATSe1', 'MATSe2', 'MATSe3', 'MATSe4', 'MATSe5', 'MATSe6', 'MATSe7', 'MATSe8',
'MATSp1', 'MATSp2', 'MATSp3', 'MATSp4', 'MATSp5', 'MATSp6', 'MATSp7', 'MATSp8',],
'Autocorrelation-geary': ['GATSm1', 'GATSm2', 'GATSm3', 'GATSm4', 'GATSm5', 'GATSm6', 'GATSm7', 'GATSm8',
'GATSv1', 'GATSv2', 'GATSv3', 'GATSv4', 'GATSv5', 'GATSv6', 'GATSv7', 'GATSv8',
'GATSe1', 'GATSe2', 'GATSe3', 'GATSe4', 'GATSe5', 'GATSe6', 'GATSe7', 'GATSe8',
'GATSp1', 'GATSp2', 'GATSp3', 'GATSp4', 'GATSp5', 'GATSp6', 'GATSp7', 'GATSp8'],
'Autocorrelation-broto': ['ATSm1', 'ATSm2', 'ATSm3', 'ATSm4', 'ATSm5', 'ATSm6', 'ATSm7', 'ATSm8',
'ATSv1', 'ATSv2', 'ATSv3', 'ATSv4', 'ATSv5', 'ATSv6', 'ATSv7', 'ATSv8',
'ATSe1', 'ATSe2', 'ATSe3', 'ATSe4', 'ATSe5', 'ATSe6', 'ATSe7', 'ATSe8',
'ATSp1', 'ATSp2', 'ATSp3', 'ATSp4', 'ATSp5', 'ATSp6', 'ATSp7', 'ATSp8'],
'Molecular properties': ['LogP', 'MR', 'LabuteASA', 'TPSA', 'Hy', 'UI'],
'Charge': ['SPP', 'LDI', 'Rnc', 'Rpc', 'Mac', 'Tac', 'Mnc', 'Tnc', 'Mpc', 'Tpc', 'Qass', 'QOss', 'QNss', 'QCss', 'QHss', 'Qmin', 'QOmin', 'QNmin', 'QCmin', 'QHmin', 'Qmax', 'QOmax', 'QNmax', 'QCmax', 'QHmax'],
'Moe-Type descriptors': ['LabuteASA', 'TPSA', 'slogPVSA', 'MRVSA', 'PEOEVSA', 'EstateVSA', 'VSAEstate'],
'Daylight-type fingerprints': ['topological'],
'MACCS fingerprints': ['MACCS'],
'Atom pairs fingerprints': ['atompairs'],
'Morgan fingerprints': ['morgan'],
'TopologicalTorsion fingerprints': ['torsions'],
'E-state fingerprints': ['Estate'],
'Basak': ["CIC0", "CIC1", "CIC2", "CIC3", "CIC4", "CIC5", "CIC6", "SIC0", "SIC1", "SIC2", "SIC3", "SIC4", "SIC5", "SIC6", "IC0", "IC1", "IC2", "IC3", "IC4", "IC5", "IC6"],
'Burden': ['bcutp', 'bcute', 'bcutv', 'bcutm'],
'Pharmacophore': ['CalcCATS'],
'Morgan-ECFP4 fingerprints': ['ECFP4'],
'Morgan-ECFP6 fingerprints': ['ECFP6'],
'Morgan-FCFP4 fingerprints': ['FCFP4'],
'Morgan-FCFP6 fingerprints': ['FCFP6'],
}
# Analysis
self.analysis_data_file = None
self.analysis_data = None
self.analysis_type = None
self.analysis_selected_algorithm = None
self.analysis_status = False
self.analysis_default_para = {
'nclusters': 2,
'n_components': 2,
'expand_factor': 2,
'inflate_factor': 2.0,
'multiply_factor': 2.0,
'n_components': 5,
}
self.analysis_message_signal.connect(self.analysis_display_message)
self.analysis_display_signal.connect(self.set_analysis_table_content)
# Plot
self.plot_data_file = None
self.plot_data = None
self.selected_plot_type = None
# initialize UI
self.initUI()
def initUI(self):
self.setWindowTitle('iFeatureOmega')
self.resize(800, 600)
self.setWindowIcon(QIcon(os.path.join(pPath, 'images', 'logo.ico')))
self.setWindowState(Qt.WindowMaximized)
self.setFont(QFont('Arial', 12))
""" QWidget """
self.protein_widget = QWidget()
self.dna_widget = QWidget()
self.rna_widget = QWidget()
self.structure_widget = QWidget()
self.chemical_widget = QWidget()
self.analysis_widget = QWidget()
self.plot_widget = QWidget()
self.addTab(self.protein_widget, ' Protein ')
self.addTab(self.dna_widget, ' DNA ')
self.addTab(self.rna_widget, ' RNA ')
self.addTab(self.structure_widget, ' Structure ')
self.addTab(self.chemical_widget, ' Ligand ')
self.addTab(self.analysis_widget, ' Feature analysis ')
self.addTab(self.plot_widget, ' Plot ')
""" Initialize tab """
self.setup_protein_widgetUI()
self.setup_dna_widgetUI()
self.setup_rna_widgetUI()
self.setup_structure_widgetUI()
self.setup_chemical_widgetUI()
self.setup_analysis_widgetUI()
self.setup_plot_widgetUI()
""" setup tab UI """
def setup_protein_widgetUI(self):
# file
topGroupBox = QGroupBox('Choose file in FASTA format', self)
topGroupBox.setFont(QFont('Arial', 10))
topGroupBoxLayout = QHBoxLayout()
self.protein_file_lineEdit = QLineEdit()
self.protein_file_lineEdit.setFont(QFont('Arial', 8))
self.protein_file_button = QPushButton('Open')
self.protein_file_button.setFont(QFont('Arial', 10))
self.protein_file_button.clicked.connect(self.get_fasta_file_name)
topGroupBoxLayout.addWidget(self.protein_file_lineEdit)
topGroupBoxLayout.addWidget(self.protein_file_button)
topGroupBox.setLayout(topGroupBoxLayout)
# encoding list -> treeGroupBox
treeGroupBox = QGroupBox('Select descriptors', self)
treeGroupBox.setFont(QFont('Arial', 10))
treeLayout = QHBoxLayout()
self.protein_desc_treeWidget = QTreeWidget()
self.protein_desc_treeWidget.setColumnCount(2)
self.protein_desc_treeWidget.setMinimumWidth(300)
self.protein_desc_treeWidget.setColumnWidth(0, 250)
self.protein_desc_treeWidget.setFont(QFont('Arial', 8))
self.protein_desc_treeWidget.setHeaderLabels(['Codings', 'Definition'])
self.protein_desc_treeWidget.clicked.connect(self.protein_desc_tree_clicked)
""" Protein descriptors """
self.Protein = QTreeWidgetItem(self.protein_desc_treeWidget)
self.Protein.setExpanded(True) # set node expanded
self.Protein.setDisabled(True)
self.Protein.setText(0, 'Protein')
self.AAC = QTreeWidgetItem(self.Protein)
self.AAC.setText(0, 'AAC')
self.AAC.setText(1, 'Amino Acids Content')
self.AAC.setCheckState(0, Qt.Unchecked)
self.AAC.setToolTip(1, 'The AAC encoding calculates the frequency of each amino acid\n type in a protein or peptide sequence.')
self.EAAC = QTreeWidgetItem(self.Protein)
self.EAAC.setText(0, 'EAAC')
self.EAAC.setText(1, 'Enhanced Amino Acids Content')
self.EAAC.setCheckState(0, Qt.Unchecked)
self.EAAC.setToolTip(1, 'The EAAC feature calculates the AAC based on the sequence window\n of fixed length that continuously slides from the N- to\n C-terminus of each peptide and can be usually applied to\n encode the peptides with an equal length.')
CKSAAP = QTreeWidgetItem(self.Protein)
CKSAAP.setText(0, 'CKSAAP type 1')
CKSAAP.setText(1, 'Composition of k-spaced Amino Acid Pairs type 1 - normalized')
CKSAAP.setCheckState(0, Qt.Unchecked)
CKSAAP.setToolTip(1, 'The CKSAAP type 1 feature encoding calculates the frequency of amino\n acid pairs separated by any k residues.')
self.CKSAAP2 = QTreeWidgetItem(self.Protein)
self.CKSAAP2.setText(0, 'CKSAAP type 2')
self.CKSAAP2.setText(1, 'Composition of k-spaced Amino Acid Pairs type 2 - raw count')
self.CKSAAP2.setCheckState(0, Qt.Unchecked)
self.CKSAAP2.setToolTip(1, 'The CKSAAP type 2 feature encoding calculates the raw count of amino\n acid pairs separated by any k residues.')
self.DPC = QTreeWidgetItem(self.Protein)
self.DPC.setText(0, 'DPC type 1')
self.DPC.setText(1, 'Di-Peptide Composition type 1 - normalized')
self.DPC.setCheckState(0, Qt.Unchecked)
self.DPC.setToolTip(1, 'The DPC type 1 descriptor calculate the frequency of di-peptides.')
self.DPC2 = QTreeWidgetItem(self.Protein)
self.DPC2.setText(0, 'DPC type 2')
self.DPC2.setText(1, 'Di-Peptide Composition type 2 - raw count')
self.DPC2.setCheckState(0, Qt.Unchecked)
self.DPC2.setToolTip(1, 'The DPC type 2 descriptor calculate the raw count of di-peptides.')
DDE = QTreeWidgetItem(self.Protein)
DDE.setText(0, 'DDE')
DDE.setText(1, 'Dipeptide Deviation from Expected Mean')
DDE.setCheckState(0, Qt.Unchecked)
DDE.setToolTip(1, 'The Dipeptide Deviation from Expected Mean feature vector is\n constructed by computing three parameters, i.e. dipeptide composition (Dc),\n theoretical mean (Tm), and theoretical variance (Tv).')
self.TPC = QTreeWidgetItem(self.Protein)
self.TPC.setText(0, 'TPC type 1')
self.TPC.setText(1, 'Tripeptide Composition type 1 - normalized')
self.TPC.setCheckState(0, Qt.Unchecked)
self.TPC.setToolTip(1, 'The TPC type 1 descriptor calculate the frequency of tri-peptides.')
self.TPC2 = QTreeWidgetItem(self.Protein)
self.TPC2.setText(0, 'TPC type 2')
self.TPC2.setText(1, 'Tripeptide Composition type 2 - raw count')
self.TPC2.setCheckState(0, Qt.Unchecked)
self.TPC2.setToolTip(1, 'The TPC type 2 descriptor calculate the raw count of tri-peptides.')
self.binary = QTreeWidgetItem(self.Protein)
self.binary.setText(0, 'binary')
self.binary.setText(1, 'binary')
self.binary.setCheckState(0, Qt.Unchecked)
self.binary.setToolTip(1, 'In the binary encoding, each amino acid is represented by a 20-dimensional binary vector.')
self.binary_6bit = QTreeWidgetItem(self.Protein)
self.binary_6bit.setToolTip(1, 'The descriptor need fasta sequences with equal length.')
self.binary_6bit.setText(0, 'binary_6bit')
self.binary_6bit.setText(1, 'binary (6 bit)')
self.binary_6bit.setCheckState(0, Qt.Unchecked)
self.binary_6bit.setToolTip(1, 'In the binary encoding, each amino acid is represented by a 6-dimensional binary vector.')
self.binary_5bit_type1 = QTreeWidgetItem(self.Protein)
self.binary_5bit_type1.setToolTip(1, 'The descriptor need fasta sequences with equal length.')
self.binary_5bit_type1.setText(0, 'binary_5bit type 1')
self.binary_5bit_type1.setText(1, 'binary (5 bit type 1)')
self.binary_5bit_type1.setCheckState(0, Qt.Unchecked)
self.binary_5bit_type1.setToolTip(1, 'In the binary encoding, each amino acid is represented by a 5-dimensional binary vector.')
self.binary_5bit_type2 = QTreeWidgetItem(self.Protein)
self.binary_5bit_type2.setToolTip(1, 'The descriptor need fasta sequences with equal length.')
self.binary_5bit_type2.setText(0, 'binary_5bit type 2')
self.binary_5bit_type2.setText(1, 'binary (5 bit type 2)')
self.binary_5bit_type2.setCheckState(0, Qt.Unchecked)
self.binary_5bit_type2.setToolTip(1, 'In the binary encoding, each amino acid is represented by a 5-dimensional binary vector.')
self.binary_3bit_type1 = QTreeWidgetItem(self.Protein)
self.binary_3bit_type1.setToolTip(1, 'The descriptor need fasta sequences with equal length.')
self.binary_3bit_type1.setText(0, 'binary_3bit type 1')
self.binary_3bit_type1.setText(1, 'binary (3 bit type 1 - Hydrophobicity)')
self.binary_3bit_type1.setCheckState(0, Qt.Unchecked)
self.binary_3bit_type1.setToolTip(1, 'In the binary encoding, each amino acid is represented by a 3-dimensional binary vector.')
self.binary_3bit_type2 = QTreeWidgetItem(self.Protein)
self.binary_3bit_type2.setToolTip(1, 'The descriptor need fasta sequences with equal length.')
self.binary_3bit_type2.setText(0, 'binary_3bit type 2')
self.binary_3bit_type2.setText(1, 'binary (3 bit type 2 - Normalized Van der Waals volume)')
self.binary_3bit_type2.setCheckState(0, Qt.Unchecked)
self.binary_3bit_type2.setToolTip(1, 'In the binary encoding, each amino acid is represented by a 3-dimensional binary vector.')
self.binary_3bit_type3 = QTreeWidgetItem(self.Protein)
self.binary_3bit_type3.setToolTip(1, 'The descriptor need fasta sequences with equal length.')
self.binary_3bit_type3.setText(0, 'binary_3bit type 3')
self.binary_3bit_type3.setText(1, 'binary (3 bit type 3 - Polarity)')
self.binary_3bit_type3.setCheckState(0, Qt.Unchecked)
self.binary_3bit_type3.setToolTip(1, 'In the binary encoding, each amino acid is represented by a 3-dimensional binary vector.')
self.binary_3bit_type4 = QTreeWidgetItem(self.Protein)
self.binary_3bit_type4.setToolTip(1, 'The descriptor need fasta sequences with equal length.')
self.binary_3bit_type4.setText(0, 'binary_3bit type 4')
self.binary_3bit_type4.setText(1, 'binary (3 bit type 4 - Polarizibility)')
self.binary_3bit_type4.setCheckState(0, Qt.Unchecked)
self.binary_3bit_type4.setToolTip(1, 'In the binary encoding, each amino acid is represented by a 3-dimensional binary vector.')
self.binary_3bit_type5 = QTreeWidgetItem(self.Protein)
self.binary_3bit_type5.setToolTip(1, 'The descriptor need fasta sequences with equal length.')
self.binary_3bit_type5.setText(0, 'binary_3bit type 5')
self.binary_3bit_type5.setText(1, 'binary (3 bit type 5 - Charge)')
self.binary_3bit_type5.setCheckState(0, Qt.Unchecked)
self.binary_3bit_type5.setToolTip(1, 'In the binary encoding, each amino acid is represented by a 3-dimensional binary vector.')
self.binary_3bit_type6 = QTreeWidgetItem(self.Protein)
self.binary_3bit_type6.setToolTip(1, 'The descriptor need fasta sequences with equal length.')
self.binary_3bit_type6.setText(0, 'binary_3bit type 6')
self.binary_3bit_type6.setText(1, 'binary (3 bit type 6 - Secondary structures)')
self.binary_3bit_type6.setCheckState(0, Qt.Unchecked)
self.binary_3bit_type6.setToolTip(1, 'In the binary encoding, each amino acid is represented by a 3-dimensional binary vector.')
self.binary_3bit_type7 = QTreeWidgetItem(self.Protein)
self.binary_3bit_type7.setToolTip(1, 'The descriptor need fasta sequences with equal length.')
self.binary_3bit_type7.setText(0, 'binary_3bit type 7')
self.binary_3bit_type7.setText(1, 'binary (3 bit type 7 - Solvent accessibility)')
self.binary_3bit_type7.setCheckState(0, Qt.Unchecked)
self.binary_3bit_type7.setToolTip(1, 'In the binary encoding, each amino acid is represented by a 3-dimensional binary vector.')
self.AESNN3 = QTreeWidgetItem(self.Protein)
self.AESNN3.setText(0, 'AESNN3')
self.AESNN3.setText(1, 'Learn from alignments')
self.AESNN3.setCheckState(0, Qt.Unchecked)
self.AESNN3.setToolTip(1, 'For this descriptor, each amino acid type is described using\n a three-dimensional vector. Values are taken from the three\n hidden units from the neural network trained on structure alignments.')
self.GAAC = QTreeWidgetItem(self.Protein)
self.GAAC.setText(0, 'GAAC')
self.GAAC.setText(1, 'Grouped Amino Acid Composition')
self.GAAC.setCheckState(0, Qt.Unchecked)
self.GAAC.setToolTip(1, 'In the GAAC encoding, the 20 amino acid types are further categorized\n into five classes according to their physicochemical properties. It calculate the frequency for each class.')
self.EGAAC = QTreeWidgetItem(self.Protein)
self.EGAAC.setText(0, 'EGAAC')
self.EGAAC.setText(1, 'Enhanced Grouped Amino Acid Composition')
self.EGAAC.setCheckState(0, Qt.Unchecked)
self.EGAAC.setToolTip(1, 'It calculates GAAC in windows of fixed length continuously sliding\n from the N- to C-terminal of each peptide and is usually applied\n to peptides with an equal length.')
CKSAAGP = QTreeWidgetItem(self.Protein)
CKSAAGP.setText(0, 'CKSAAGP type 1')
CKSAAGP.setText(1, 'Composition of k-Spaced Amino Acid Group Pairs type 1 - normalized')
CKSAAGP.setCheckState(0, Qt.Unchecked)
CKSAAGP.setToolTip(1, ' It calculates the frequency of amino acid group pairs separated by any k residues.')
self.CKSAAGP2 = QTreeWidgetItem(self.Protein)
self.CKSAAGP2.setText(0, 'CKSAAGP type 2')
self.CKSAAGP2.setText(1, 'Composition of k-Spaced Amino Acid Group Pairs type 2 - raw count')
self.CKSAAGP2.setCheckState(0, Qt.Unchecked)
self.CKSAAGP2.setToolTip(1, ' It calculates the raw count of amino acid group pairs separated by any k residues.')
self.GDPC = QTreeWidgetItem(self.Protein)
self.GDPC.setText(0, 'GDPC type 1')
self.GDPC.setText(1, 'Grouped Di-Peptide Composition type 1 - normalized')
self.GDPC.setCheckState(0, Qt.Unchecked)
self.GDPC.setToolTip(1, 'GDPC type 1 calculate the frequency of amino acid group pairs.')
self.GDPC2 = QTreeWidgetItem(self.Protein)
self.GDPC2.setText(0, 'GDPC type 2')
self.GDPC2.setText(1, 'Grouped Di-Peptide Composition type 2 - raw count')
self.GDPC2.setCheckState(0, Qt.Unchecked)
self.GDPC2.setToolTip(1, 'GDPC type 2 calculate the raw count of amino acid group pairs.')
self.GTPC = QTreeWidgetItem(self.Protein)
self.GTPC.setText(0, 'GTPC type 1')
self.GTPC.setText(1, 'Grouped Tri-Peptide Composition type 1 - normalized')
self.GTPC.setCheckState(0, Qt.Unchecked)
self.GTPC.setToolTip(1, 'GTPC type 1 calculate the frequency of grouped tri-peptides.')
self.GTPC2 = QTreeWidgetItem(self.Protein)
self.GTPC2.setText(0, 'GTPC type 2')
self.GTPC2.setText(1, 'Grouped Tri-Peptide Composition type 2 - raw count')
self.GTPC2.setCheckState(0, Qt.Unchecked)
self.GTPC2.setToolTip(1, 'GTPC type 2 calculate the raw count of grouped tri-peptides.')
self.AAIndex = QTreeWidgetItem(self.Protein)
self.AAIndex.setText(0, 'AAIndex')
self.AAIndex.setText(1, 'AAIndex')
self.AAIndex.setCheckState(0, Qt.Unchecked)
self.AAIndex.setToolTip(1, 'The amino acids is respresented by the physicochemical property value in AAindex database.')
self.ZScale = QTreeWidgetItem(self.Protein)
self.ZScale.setText(0, 'ZScale')
self.ZScale.setText(1, 'ZScale')
self.ZScale.setCheckState(0, Qt.Unchecked)
self.ZScale.setToolTip(1, 'Each amino acid is characterized by five physicochemical descriptor variables, which were developed by Sandberg et al. in 1998.')
self.BLOSUM62 = QTreeWidgetItem(self.Protein)
self.BLOSUM62.setText(0, 'BLOSUM62')
self.BLOSUM62.setText(1, 'BLOSUM62')
self.BLOSUM62.setCheckState(0, Qt.Unchecked)
self.BLOSUM62.setToolTip(1, 'In this descriptor, the BLOSUM62 matrix is employed to represent the\n protein primary sequence information as the basic feature set.')
NMBroto = QTreeWidgetItem(self.Protein)
NMBroto.setText(0, 'NMBroto')
NMBroto.setText(1, 'Normalized Moreau-Broto Autocorrelation')
NMBroto.setCheckState(0, Qt.Unchecked)
NMBroto.setToolTip(1, 'The autocorrelation descriptors are defined based on the distribution\n of amino acid properties along the sequence.')
Moran = QTreeWidgetItem(self.Protein)
Moran.setText(0, 'Moran')
Moran.setText(1, 'Moran correlation')
Moran.setCheckState(0, Qt.Unchecked)
Moran.setToolTip(1, 'The autocorrelation descriptors are defined based on the distribution\n of amino acid properties along the sequence.')
Geary = QTreeWidgetItem(self.Protein)
Geary.setText(0, 'Geary')
Geary.setText(1, 'Geary correlation')
Geary.setCheckState(0, Qt.Unchecked)
Geary.setToolTip(1, 'The autocorrelation descriptors are defined based on the distribution\n of amino acid properties along the sequence.')
CTDC = QTreeWidgetItem(self.Protein)
CTDC.setText(0, 'CTDC')
CTDC.setText(1, 'Composition')
CTDC.setCheckState(0, Qt.Unchecked)
CTDC.setToolTip(1, 'The Composition, Transition and Distribution (CTD) features represent\n the amino acid distribution patterns of a specific structural\n or physicochemical property in a protein or peptide sequence.')
CTDT = QTreeWidgetItem(self.Protein)
CTDT.setText(0, 'CTDT')
CTDT.setText(1, 'Transition')
CTDT.setCheckState(0, Qt.Unchecked)
CTDT.setToolTip(1, 'The Composition, Transition and Distribution (CTD) features represent\n the amino acid distribution patterns of a specific structural\n or physicochemical property in a protein or peptide sequence.')
CTDD = QTreeWidgetItem(self.Protein)
CTDD.setText(0, 'CTDD')
CTDD.setText(1, 'Distribution')
CTDD.setCheckState(0, Qt.Unchecked)
CTDD.setToolTip(1, 'The Composition, Transition and Distribution (CTD) features represent\n the amino acid distribution patterns of a specific structural\n or physicochemical property in a protein or peptide sequence.')
CTriad = QTreeWidgetItem(self.Protein)
CTriad.setText(0, 'CTriad')
CTriad.setText(1, 'Conjoint Triad')
CTriad.setCheckState(0, Qt.Unchecked)
CTriad.setToolTip(1, 'The CTriad considers the properties of one amino acid and its\n vicinal amino acids by regarding any three continuous amino\n acids as a single unit.')
self.KSCTriad = QTreeWidgetItem(self.Protein)
self.KSCTriad.setText(0, 'KSCTriad')
self.KSCTriad.setText(1, 'k-Spaced Conjoint Triad')
self.KSCTriad.setCheckState(0, Qt.Unchecked)
self.KSCTriad.setToolTip(1, 'The KSCTriad descriptor is based on the Conjoint CTriad descriptor,\n which not only calculates the numbers of three continuous amino acid units,\n but also considers the continuous amino acid units that are separated by any k residues.')
SOCNumber = QTreeWidgetItem(self.Protein)
SOCNumber.setText(0, 'SOCNumber')
SOCNumber.setText(1, 'Sequence-Order-Coupling Number')
SOCNumber.setCheckState(0, Qt.Unchecked)
SOCNumber.setToolTip(1, 'The SOCNumber descriptor consider the sequence order coupling number information.')
QSOrder = QTreeWidgetItem(self.Protein)
QSOrder.setText(0, 'QSOrder')
QSOrder.setText(1, 'Quasi-sequence-order')
QSOrder.setCheckState(0, Qt.Unchecked)
QSOrder.setToolTip(1, 'Qsorder descriptor coonsider the quasi sequence order information.')
PAAC = QTreeWidgetItem(self.Protein)
PAAC.setText(0, 'PAAC')
PAAC.setText(1, 'Pseudo-Amino Acid Composition')
PAAC.setCheckState(0, Qt.Unchecked)
PAAC.setToolTip(1, 'The PAAC descriptor is a combination of a set of discrete sequence correlation\n factors and the 20 components of the conventional amino acid composition.')
APAAC = QTreeWidgetItem(self.Protein)
APAAC.setText(0, 'APAAC')
APAAC.setText(1, 'Amphiphilic Pseudo-Amino Acid Composition')
APAAC.setCheckState(0, Qt.Unchecked)
APAAC.setToolTip(1, 'The descriptor contains 20 + 2 lambda discrete numbers:\n the first 20 numbers are the components of the conventional amino acid composition;\n the next 2 lambda numbers are a set of correlation factors that reflect different\n hydrophobicity and hydrophilicity distribution patterns along a protein chain.')
self.OPF_10bit = QTreeWidgetItem(self.Protein)
self.OPF_10bit.setText(0, 'OPF_10bit')
self.OPF_10bit.setText(1, 'Overlapping Property Features (10 bit)')
self.OPF_10bit.setCheckState(0, Qt.Unchecked)
self.OPF_10bit.setToolTip(1, 'For this descriptor, the amino acids are classified into 10 groups based their physicochemical properties.')
self.OPF_7bit_type1 = QTreeWidgetItem(self.Protein)
self.OPF_7bit_type1.setText(0, 'OPF_7bit type 1')
self.OPF_7bit_type1.setText(1, 'Overlapping Property Features (7 bit type 1)')
self.OPF_7bit_type1.setCheckState(0, Qt.Unchecked)
self.OPF_7bit_type1.setToolTip(1, 'For this descriptor, the amino acids are classified into 7 groups based their physicochemical properties.')
self.OPF_7bit_type2 = QTreeWidgetItem(self.Protein)
self.OPF_7bit_type2.setText(0, 'OPF_7bit type 2')
self.OPF_7bit_type2.setText(1, 'Overlapping Property Features (7 bit type 2)')
self.OPF_7bit_type2.setCheckState(0, Qt.Unchecked)
self.OPF_7bit_type2.setToolTip(1, 'For this descriptor, the amino acids are classified into 7 groups based their physicochemical properties.')
self.OPF_7bit_type3 = QTreeWidgetItem(self.Protein)
self.OPF_7bit_type3.setText(0, 'OPF_7bit type 3')
self.OPF_7bit_type3.setText(1, 'Overlapping Property Features (7 bit type 3)')
self.OPF_7bit_type3.setCheckState(0, Qt.Unchecked)
self.OPF_7bit_type3.setToolTip(1, 'For this descriptor, the amino acids are classified into 7 groups based their physicochemical properties.')
pASDC = QTreeWidgetItem(self.Protein)
pASDC.setText(0, 'ASDC')
pASDC.setText(1, 'Adaptive skip dipeptide composition')
pASDC.setCheckState(0, Qt.Unchecked)
pASDC.setToolTip(1, 'The adaptive skip dipeptide composition is a modified dipeptide composition,\n which sufficiently considers the correlation information present not only between\n adjacent residues but also between intervening residues.')
# self.proteinKNN = QTreeWidgetItem(self.Protein)
# self.proteinKNN.setText(0, 'KNN')
# self.proteinKNN.setText(1, 'K-nearest neighbor')
# self.proteinKNN.setCheckState(0, Qt.Unchecked)
# self.proteinKNN.setToolTip(1, 'The KNN descriptor depicts how much one query sample resembles other samples.')
DistancePair = QTreeWidgetItem(self.Protein)
DistancePair.setText(0, 'DistancePair')
DistancePair.setText(1, 'PseAAC of Distance-Pairs and Reduced Alphabet')
DistancePair.setCheckState(0, Qt.Unchecked)
DistancePair.setToolTip(1, 'The descriptor incorporates the amino acid distance pair coupling information \nand the amino acid reduced alphabet profile into the general pseudo amino acid composition vector.')
self.proteinAC = QTreeWidgetItem(self.Protein)
self.proteinAC.setText(0, 'AC')
self.proteinAC.setText(1, 'Auto covariance')
self.proteinAC.setCheckState(0, Qt.Unchecked)
self.proteinAC.setToolTip(1, 'The AC descriptor measures the correlation of the same physicochemical \nindex between two amino acids separated by a distance of lag along the sequence. ')
self.proteinCC = QTreeWidgetItem(self.Protein)
self.proteinCC.setText(0, 'CC')
self.proteinCC.setText(1, 'Cross covariance')
self.proteinCC.setCheckState(0, Qt.Unchecked)
self.proteinCC.setToolTip(1, 'The CC descriptor measures the correlation of two different physicochemical \nindices between two amino acids separated by lag nucleic acids along the sequence.')
self.proteinACC = QTreeWidgetItem(self.Protein)
self.proteinACC.setText(0, 'ACC')
self.proteinACC.setText(1, 'Auto-cross covariance')
self.proteinACC.setCheckState(0, Qt.Unchecked)
self.proteinACC.setToolTip(1, 'The Dinucleotide-based Auto-Cross Covariance (ACC) encoding is a combination of AC and CC encoding.')
PseKRAAC_type1 = QTreeWidgetItem(self.Protein)
PseKRAAC_type1.setText(0, 'PseKRAAC type 1')
PseKRAAC_type1.setText(1, 'Pseudo K-tuple Reduced Amino Acids Composition - type 1')
PseKRAAC_type1.setCheckState(0, Qt.Unchecked)
PseKRAAC_type1.setToolTip(1, 'Pseudo K-tuple Reduced Amino Acids Composition.')
self.PseKRAAC_type2 = QTreeWidgetItem(self.Protein)
self.PseKRAAC_type2.setText(0, 'PseKRAAC type 2')
self.PseKRAAC_type2.setText(1, 'Pseudo K-tuple Reduced Amino Acids Composition - type 2')
self.PseKRAAC_type2.setCheckState(0, Qt.Unchecked)
self.PseKRAAC_type2.setToolTip(1, 'Pseudo K-tuple Reduced Amino Acids Composition.')
self.PseKRAAC_type3A = QTreeWidgetItem(self.Protein)
self.PseKRAAC_type3A.setText(0, 'PseKRAAC type 3A')
self.PseKRAAC_type3A.setText(1, 'Pseudo K-tuple Reduced Amino Acids Composition - type 3A')
self.PseKRAAC_type3A.setCheckState(0, Qt.Unchecked)
self.PseKRAAC_type3A.setToolTip(1, 'Pseudo K-tuple Reduced Amino Acids Composition.')
self.PseKRAAC_type3B = QTreeWidgetItem(self.Protein)
self.PseKRAAC_type3B.setText(0, 'PseKRAAC type 3B')
self.PseKRAAC_type3B.setText(1, 'Pseudo K-tuple Reduced Amino Acids Composition - type 3B')
self.PseKRAAC_type3B.setCheckState(0, Qt.Unchecked)
self.PseKRAAC_type3B.setToolTip(1, 'Pseudo K-tuple Reduced Amino Acids Composition.')
self.PseKRAAC_type4 = QTreeWidgetItem(self.Protein)
self.PseKRAAC_type4.setText(0, 'PseKRAAC type 4')
self.PseKRAAC_type4.setText(1, 'Pseudo K-tuple Reduced Amino Acids Composition - type 4')
self.PseKRAAC_type4.setCheckState(0, Qt.Unchecked)
self.PseKRAAC_type4.setToolTip(1, 'Pseudo K-tuple Reduced Amino Acids Composition.')
self.PseKRAAC_type5 = QTreeWidgetItem(self.Protein)
self.PseKRAAC_type5.setText(0, 'PseKRAAC type 5')
self.PseKRAAC_type5.setText(1, 'Pseudo K-tuple Reduced Amino Acids Composition - type 5')
self.PseKRAAC_type5.setCheckState(0, Qt.Unchecked)
self.PseKRAAC_type5.setToolTip(1, 'Pseudo K-tuple Reduced Amino Acids Composition.')
self.PseKRAAC_type6A = QTreeWidgetItem(self.Protein)
self.PseKRAAC_type6A.setText(0, 'PseKRAAC type 6A')
self.PseKRAAC_type6A.setText(1, 'Pseudo K-tuple Reduced Amino Acids Composition - type 6A')
self.PseKRAAC_type6A.setCheckState(0, Qt.Unchecked)
self.PseKRAAC_type6A.setToolTip(1, 'Pseudo K-tuple Reduced Amino Acids Composition.')
self.PseKRAAC_type6B = QTreeWidgetItem(self.Protein)
self.PseKRAAC_type6B.setText(0, 'PseKRAAC type 6B')
self.PseKRAAC_type6B.setText(1, 'Pseudo K-tuple Reduced Amino Acids Composition - type 6B')
self.PseKRAAC_type6B.setCheckState(0, Qt.Unchecked)
self.PseKRAAC_type6B.setToolTip(1, 'Pseudo K-tuple Reduced Amino Acids Composition.')
self.PseKRAAC_type6C = QTreeWidgetItem(self.Protein)
self.PseKRAAC_type6C.setText(0, 'PseKRAAC type 6C')
self.PseKRAAC_type6C.setText(1, 'Pseudo K-tuple Reduced Amino Acids Composition - type 6C')
self.PseKRAAC_type6C.setCheckState(0, Qt.Unchecked)
self.PseKRAAC_type6C.setToolTip(1, 'Pseudo K-tuple Reduced Amino Acids Composition.')
self.PseKRAAC_type7 = QTreeWidgetItem(self.Protein)
self.PseKRAAC_type7.setText(0, 'PseKRAAC type 7')
self.PseKRAAC_type7.setText(1, 'Pseudo K-tuple Reduced Amino Acids Composition - type 7')
self.PseKRAAC_type7.setCheckState(0, Qt.Unchecked)
self.PseKRAAC_type7.setToolTip(1, 'Pseudo K-tuple Reduced Amino Acids Composition.')
self.PseKRAAC_type8 = QTreeWidgetItem(self.Protein)
self.PseKRAAC_type8.setText(0, 'PseKRAAC type 8')
self.PseKRAAC_type8.setText(1, 'Pseudo K-tuple Reduced Amino Acids Composition - type 8')
self.PseKRAAC_type8.setCheckState(0, Qt.Unchecked)
self.PseKRAAC_type8.setToolTip(1, 'Pseudo K-tuple Reduced Amino Acids Composition.')
self.PseKRAAC_type9 = QTreeWidgetItem(self.Protein)
self.PseKRAAC_type9.setText(0, 'PseKRAAC type 9')
self.PseKRAAC_type9.setText(1, 'Pseudo K-tuple Reduced Amino Acids Composition - type 9')
self.PseKRAAC_type9.setCheckState(0, Qt.Unchecked)
self.PseKRAAC_type9.setToolTip(1, 'Pseudo K-tuple Reduced Amino Acids Composition.')
self.PseKRAAC_type10 = QTreeWidgetItem(self.Protein)
self.PseKRAAC_type10.setText(0, 'PseKRAAC type 10')
self.PseKRAAC_type10.setText(1, 'Pseudo K-tuple Reduced Amino Acids Composition - type 10')
self.PseKRAAC_type10.setCheckState(0, Qt.Unchecked)
self.PseKRAAC_type10.setToolTip(1, 'Pseudo K-tuple Reduced Amino Acids Composition.')
self.PseKRAAC_type11 = QTreeWidgetItem(self.Protein)
self.PseKRAAC_type11.setText(0, 'PseKRAAC type 11')
self.PseKRAAC_type11.setText(1, 'Pseudo K-tuple Reduced Amino Acids Composition - type 11')
self.PseKRAAC_type11.setCheckState(0, Qt.Unchecked)
self.PseKRAAC_type11.setToolTip(1, 'Pseudo K-tuple Reduced Amino Acids Composition.')
self.PseKRAAC_type12 = QTreeWidgetItem(self.Protein)
self.PseKRAAC_type12.setText(0, 'PseKRAAC type 12')
self.PseKRAAC_type12.setText(1, 'Pseudo K-tuple Reduced Amino Acids Composition - type 12')
self.PseKRAAC_type12.setCheckState(0, Qt.Unchecked)
self.PseKRAAC_type12.setToolTip(1, 'Pseudo K-tuple Reduced Amino Acids Composition.')
self.PseKRAAC_type13 = QTreeWidgetItem(self.Protein)
self.PseKRAAC_type13.setText(0, 'PseKRAAC type 13')
self.PseKRAAC_type13.setText(1, 'Pseudo K-tuple Reduced Amino Acids Composition - type 13')
self.PseKRAAC_type13.setCheckState(0, Qt.Unchecked)
self.PseKRAAC_type13.setToolTip(1, 'Pseudo K-tuple Reduced Amino Acids Composition.')
self.PseKRAAC_type14 = QTreeWidgetItem(self.Protein)
self.PseKRAAC_type14.setText(0, 'PseKRAAC type 14')
self.PseKRAAC_type14.setText(1, 'Pseudo K-tuple Reduced Amino Acids Composition - type 14')
self.PseKRAAC_type14.setCheckState(0, Qt.Unchecked)
self.PseKRAAC_type14.setToolTip(1, 'Pseudo K-tuple Reduced Amino Acids Composition.')
self.PseKRAAC_type15 = QTreeWidgetItem(self.Protein)
self.PseKRAAC_type15.setText(0, 'PseKRAAC type 15')
self.PseKRAAC_type15.setText(1, 'Pseudo K-tuple Reduced Amino Acids Composition - type 15')
self.PseKRAAC_type15.setCheckState(0, Qt.Unchecked)
self.PseKRAAC_type15.setToolTip(1, 'Pseudo K-tuple Reduced Amino Acids Composition.')
self.PseKRAAC_type16 = QTreeWidgetItem(self.Protein)
self.PseKRAAC_type16.setText(0, 'PseKRAAC type 16')
self.PseKRAAC_type16.setText(1, 'Pseudo K-tuple Reduced Amino Acids Composition - type 16')
self.PseKRAAC_type16.setCheckState(0, Qt.Unchecked)
self.PseKRAAC_type16.setToolTip(1, 'Pseudo K-tuple Reduced Amino Acids Composition.')
proteinKNN = QTreeWidgetItem(self.Protein)
proteinKNN.setText(0, 'KNN')
proteinKNN.setText(1, 'K-nearest neighbor')
proteinKNN.setCheckState(0, Qt.Unchecked)
proteinKNN.setToolTip(1, 'The KNN descriptor depicts how much one query sample resembles other samples.')
treeLayout.addWidget(self.protein_desc_treeWidget)
treeGroupBox.setLayout(treeLayout)
# operation
startGroupBox = QGroupBox('Operator', self)
startGroupBox.setFont(QFont('Arial', 10))
startLayout = QHBoxLayout(startGroupBox)
self.protein_start_button = QPushButton('Start')
self.protein_start_button.setFont(QFont('Arial', 10))
self.protein_start_button.clicked.connect(self.run_calculating_protein_descriptors)
self.protein_desc_slim_button = QPushButton('Show descriptor slims')
self.protein_desc_slim_button.clicked.connect(self.show_protein_slims)
self.protein_desc_slim_button.setFont(QFont('Arial', 10))
startLayout.addWidget(self.protein_start_button)
startLayout.addWidget(self.protein_desc_slim_button)
# layout
left_vertical_layout = QVBoxLayout()
left_vertical_layout.addWidget(topGroupBox)
left_vertical_layout.addWidget(treeGroupBox)
left_vertical_layout.addWidget(startGroupBox)
# widget
leftWidget = QWidget()
leftWidget.setLayout(left_vertical_layout)
# QTableWidget
self.protein_viewWidget = QTabWidget()
# self.protein_viewWidget.currentChanged.connect(self.protein_displayHtml)
self.protein_desc_tableWidget = TableWidget.TableWidget()
# density plot
self.protein_desc_histWidget = QWidget()
self.protein_desc_hist_layout = QVBoxLayout(self.protein_desc_histWidget)
self.protein_desc_histogram = PlotWidgets.HistogramWidget()
self.protein_desc_hist_layout.addWidget(self.protein_desc_histogram)
# heatmap
self.protein_heatmap_widget = QWidget()
self.protein_heatmap_layout = QVBoxLayout(self.protein_heatmap_widget)
self.protein_heatmap = PlotWidgets.HeatMapSpanSelector()
self.protein_heatmap_layout.addWidget(self.protein_heatmap)
# boxplot
self.protein_boxplot_widget = QWidget()
self.protein_boxplot_layout = QVBoxLayout(self.protein_boxplot_widget)
self.protein_boxplot = PlotWidgets.BoxplotSpanSelector()
self.protein_boxplot_layout.addWidget(self.protein_boxplot)
# relations plot
self.protein_relation_widget = QWidget()
self.protein_relation_layout = QVBoxLayout(self.protein_relation_widget)
self.protein_relation = PlotWidgets.CircosWidget()
self.protein_relation_layout.addWidget(self.protein_relation)
# similarity matrix
self.protein_similarity_widget = QWidget()
self.protein_similarity_layout = QVBoxLayout(self.protein_similarity_widget)
self.protein_similarity = PlotWidgets.HeatmapWidgetSub()
self.protein_similarity_layout.addWidget(self.protein_similarity)
self.protein_viewWidget.addTab(self.protein_desc_tableWidget, ' Data ')
self.protein_viewWidget.addTab(self.protein_desc_histWidget, ' Data distribution ')
self.protein_viewWidget.addTab(self.protein_heatmap_widget, ' Heatmap ')
self.protein_viewWidget.addTab(self.protein_boxplot_widget, ' Boxplot ')
self.protein_viewWidget.addTab(self.protein_relation_widget, ' Circular plot ')
self.protein_viewWidget.addTab(self.protein_similarity_widget, ' Similarity matrix ')
# splitter
splitter_1 = QSplitter(Qt.Horizontal)
splitter_1.addWidget(leftWidget)
splitter_1.addWidget(self.protein_viewWidget)
splitter_1.setSizes([100, 1200])
# vertical layout
vLayout = QVBoxLayout()
# status bar
statusGroupBox = QGroupBox('Status', self)
statusGroupBox.setFont(QFont('Arial', 10))
statusLayout = QHBoxLayout(statusGroupBox)
self.protein_status_label = QLabel('Welcome to iFeatureOmega.')
self.protein_progress_bar = QLabel()
self.protein_progress_bar.setMaximumWidth(230)
statusLayout.addWidget(self.protein_status_label)
statusLayout.addWidget(self.protein_progress_bar)
splitter_2 = QSplitter(Qt.Vertical)
splitter_2.addWidget(splitter_1)
splitter_2.addWidget(statusGroupBox)
splitter_2.setSizes([1000, 100])
vLayout.addWidget(splitter_2)
self.protein_widget.setLayout(vLayout)
def setup_dna_widgetUI(self):
# file
topGroupBox = QGroupBox('Choose file in FASTA format', self)
topGroupBox.setFont(QFont('Arial', 10))
topGroupBoxLayout = QHBoxLayout()
self.dna_file_lineEdit = QLineEdit()
self.dna_file_lineEdit.setFont(QFont('Arial', 8))
self.dna_file_button = QPushButton('Open')
self.dna_file_button.clicked.connect(self.get_dna_file_name)
self.dna_file_button.setFont(QFont('Arial', 10))
topGroupBoxLayout.addWidget(self.dna_file_lineEdit)
topGroupBoxLayout.addWidget(self.dna_file_button)
topGroupBox.setLayout(topGroupBoxLayout)
# encoding list -> treeGroupBox
treeGroupBox = QGroupBox('Select descriptors', self)
treeGroupBox.setFont(QFont('Arial', 10))
treeLayout = QHBoxLayout()
self.dna_desc_treeWidget = QTreeWidget()
self.dna_desc_treeWidget.setColumnCount(2)
self.dna_desc_treeWidget.setMinimumWidth(300)
self.dna_desc_treeWidget.setColumnWidth(0, 200)
self.dna_desc_treeWidget.setFont(QFont('Arial', 8))
self.dna_desc_treeWidget.setHeaderLabels(['Codings', 'Definition'])
self.dna_desc_treeWidget.clicked.connect(self.dna_desc_tree_clicked)
""" DNA descriptors """
# DNA
self.DNA = QTreeWidgetItem(self.dna_desc_treeWidget)
self.DNA.setExpanded(True)
self.DNA.setDisabled(True)
self.DNA.setText(0, 'DNA')
Kmer = QTreeWidgetItem(self.DNA)
Kmer.setText(0, 'Kmer type 1')
Kmer.setText(1, 'The occurrence frequencies of k neighboring nucleic acids type 1 - normalized')
Kmer.setCheckState(0, Qt.Unchecked)
Kmer.setToolTip(1, 'For kmer type 1 descriptor, the DNA or RNA sequences are represented\n as the occurrence frequencies of k neighboring nucleic acids.')
self.Kmer2 = QTreeWidgetItem(self.DNA)
self.Kmer2.setText(0, 'Kmer type 2')
self.Kmer2.setText(1, 'The occurrence frequencies of k neighboring nucleic acids type 2 - raw count')
self.Kmer2.setCheckState(0, Qt.Unchecked)
self.Kmer2.setToolTip(1, 'For kmer type 2 descriptor, the DNA or RNA sequences are represented\n as the raw count of k neighboring nucleic acids.')
RCKmer = QTreeWidgetItem(self.DNA)
RCKmer.setText(0, 'RCKmer type 1')
RCKmer.setText(1, 'Reverse Compliment Kmer type 1 - normalized')
RCKmer.setCheckState(0, Qt.Unchecked)
RCKmer.setToolTip(1, 'The RCKmer type 1 descriptor is a variant of kmer descriptor,\n in which the kmers are not expected to be strand-specific. ')
self.RCKmer2 = QTreeWidgetItem(self.DNA)
self.RCKmer2.setText(0, 'RCKmer type 2')
self.RCKmer2.setText(1, 'Reverse Compliment Kmer type 2 - raw count')
self.RCKmer2.setCheckState(0, Qt.Unchecked)
self.RCKmer2.setToolTip(1, 'The RCKmer type 2 descriptor is a variant of kmer descriptor,\n in which the kmers are not expected to be strand-specific.')
dnaMismatch = QTreeWidgetItem(self.DNA)
dnaMismatch.setText(0, 'Mismatch')
dnaMismatch.setText(1, 'Mismatch profile')
dnaMismatch.setCheckState(0, Qt.Unchecked)
dnaMismatch.setToolTip(1, 'The mismatch profile also calculates the occurrences of kmers,\n but allows max m inexact matching (m < k).')
dnaSubsequence = QTreeWidgetItem(self.DNA)
dnaSubsequence.setText(0, 'Subsequence')
dnaSubsequence.setText(1, 'Subsequence profile')
dnaSubsequence.setCheckState(0, Qt.Unchecked)
dnaSubsequence.setToolTip(1, 'The subsequence descriptor allows non-contiguous matching.')
self.NAC = QTreeWidgetItem(self.DNA)
self.NAC.setText(0, 'NAC')
self.NAC.setText(1, 'Nucleic Acid Composition')
self.NAC.setCheckState(0, Qt.Unchecked)
self.NAC.setToolTip(1, 'The NAC encoding calculates the frequency of each nucleic acid type in a nucleotide sequence.')
self.ANF = QTreeWidgetItem(self.DNA)
self.ANF.setText(0, 'ANF')
self.ANF.setText(1, 'Accumulated Nucleotide Frequency')
self.ANF.setCheckState(0, Qt.Unchecked)
self.ANF.setToolTip(1, 'The ANF encoding include the nucleotide frequency information and the distribution of each nucleotide in the RNA sequence.')
self.ENAC = QTreeWidgetItem(self.DNA)
self.ENAC.setText(0, 'ENAC')
self.ENAC.setText(1, 'Enhanced Nucleic Acid Composition')
self.ENAC.setCheckState(0, Qt.Unchecked)
self.ENAC.setToolTip(1, 'The ENAC descriptor calculates the NAC based on the sequence window\n of fixed length that continuously slides from the 5\' to 3\' terminus\n of each nucleotide sequence and can be usually applied to encode the\n nucleotide sequence with an equal length.')
self.DNAbinary = QTreeWidgetItem(self.DNA)
self.DNAbinary.setText(0, 'binary')
self.DNAbinary.setText(1, 'DNA binary')
self.DNAbinary.setCheckState(0, Qt.Unchecked)
self.DNAbinary.setToolTip(1, 'In the Binary encoding, each amino acid is represented by a 4-dimensional binary vector.')
self.dnaPS2 = QTreeWidgetItem(self.DNA)
self.dnaPS2.setText(0, 'PS2')
self.dnaPS2.setText(1, 'Position-specific of two nucleotides')
self.dnaPS2.setCheckState(0, Qt.Unchecked)
self.dnaPS2.setToolTip(1, 'There are 4 x 4 = 16 pairs of adjacent pairwise nucleotides, \nthus a single variable representing one such pair gets one-hot\n (i.e. binary) encoded into 16 binary variables.')
self.dnaPS3 = QTreeWidgetItem(self.DNA)
self.dnaPS3.setText(0, 'PS3')
self.dnaPS3.setText(1, 'Position-specific of three nucleotides')
self.dnaPS3.setCheckState(0, Qt.Unchecked)
self.dnaPS3.setToolTip(1, 'The PS3 descriptor is encoded for three adjacent nucleotides in a similar way with PS2.')
self.dnaPS4 = QTreeWidgetItem(self.DNA)
self.dnaPS4.setText(0, 'PS4')
self.dnaPS4.setText(1, 'Position-specific of four nucleotides')
self.dnaPS4.setCheckState(0, Qt.Unchecked)
self.dnaPS4.setToolTip(1, 'The PS4 descriptor is encoded for four adjacent nucleotides in a similar way with PS2.')
CKSNAP = QTreeWidgetItem(self.DNA)
CKSNAP.setText(0, 'CKSNAP type 1')
CKSNAP.setText(1, 'Composition of k-spaced Nucleic Acid Pairs type 1 - normalized')
CKSNAP.setCheckState(0, Qt.Unchecked)
CKSNAP.setToolTip(1, 'The CKSNAP type 1 feature encoding calculates the frequency of nucleic acid pairs separated by any k nucleic acid.')
self.CKSNAP2 = QTreeWidgetItem(self.DNA)
self.CKSNAP2.setText(0, 'CKSNAP type 2')
self.CKSNAP2.setText(1, 'Composition of k-spaced Nucleic Acid Pairs 2 - raw count')
self.CKSNAP2.setCheckState(0, Qt.Unchecked)
self.CKSNAP2.setToolTip(1, 'The CKSNAP type 2 feature encoding calculates the raw count of nucleic acid pairs separated by any k nucleic acid.')
self.NCP = QTreeWidgetItem(self.DNA)
self.NCP.setText(0, 'NCP')
self.NCP.setText(1, 'Nucleotide Chemical Property')
self.NCP.setCheckState(0, Qt.Unchecked)
self.NCP.setToolTip(1, 'Based on chemical properties, A can be represented by coordinates (1, 1, 1), \nC can be represented by coordinates (0, 1, 0), G can be represented by coordinates (1, 0, 0), \nU can be represented by coordinates (0, 0, 1). ')
self.PSTNPss = QTreeWidgetItem(self.DNA)
self.PSTNPss.setText(0, 'PSTNPss')
self.PSTNPss.setText(1, 'Position-specific trinucleotide propensity based on single-strand')
self.PSTNPss.setCheckState(0, Qt.Unchecked)
self.PSTNPss.setToolTip(1, 'The PSTNPss descriptor usie a statistical strategy based on single-stranded characteristics of DNA or RNA.')
self.PSTNPds = QTreeWidgetItem(self.DNA)
self.PSTNPds.setText(0, 'PSTNPds')
self.PSTNPds.setText(1, 'Position-specific trinucleotide propensity based on double-strand')
self.PSTNPds.setCheckState(0, Qt.Unchecked)
self.PSTNPds.setToolTip(1, 'The PSTNPds descriptor use a statistical strategy based on double-stranded characteristics of DNA according to complementary base pairing.')
self.EIIP = QTreeWidgetItem(self.DNA)
self.EIIP.setText(0, 'EIIP')
self.EIIP.setText(1, 'Electron-ion interaction pseudopotentials of trinucleotide')
self.EIIP.setCheckState(0, Qt.Unchecked)
self.EIIP.setToolTip(1, 'The EIIP directly use the EIIP value represent the nucleotide in the DNA sequence.')
PseEIIP = QTreeWidgetItem(self.DNA)
PseEIIP.setText(0, 'PseEIIP')
PseEIIP.setText(1, 'Electron-ion interaction pseudopotentials of trinucleotide')
PseEIIP.setCheckState(0, Qt.Unchecked)
PseEIIP.setToolTip(1, 'Electron-ion interaction pseudopotentials of trinucleotide.')
DNAASDC = QTreeWidgetItem(self.DNA)
DNAASDC.setText(0, 'ASDC')
DNAASDC.setText(1, 'Adaptive skip dinucleotide composition')
DNAASDC.setCheckState(0, Qt.Unchecked)
DNAASDC.setToolTip(1, 'The adaptive skip dipeptide composition is a modified dinucleotide composition, \nwhich sufficiently considers the correlation information present not only between \nadjacent residues but also between intervening residues.')
self.dnaDBE = QTreeWidgetItem(self.DNA)
self.dnaDBE.setText(0, 'DBE')
self.dnaDBE.setText(1, 'Dinucleotide binary encoding')
self.dnaDBE.setCheckState(0, Qt.Unchecked)
self.dnaDBE.setToolTip(1, 'The DBE descriptor encapsulates the positional information of the dinucleotide at each position in the sequence.')
self.dnaLPDF = QTreeWidgetItem(self.DNA)
self.dnaLPDF.setText(0, 'LPDF')
self.dnaLPDF.setText(1, 'Local position-specific dinucleotide frequency')
self.dnaLPDF.setCheckState(0, Qt.Unchecked)
self.dnaLPDF.setToolTip(1, 'The LPDF descriptor calculate the local position-specific dinucleotide frequency.')
dnaDPCP = QTreeWidgetItem(self.DNA)