Mercurial > repos > jay > pdaug_fishers_plot
annotate PDAUG_Peptide_Sequence_Analysis/PDAUG_Peptide_Sequence_Analysis.py @ 0:668434d3fc8a draft
"planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
author | jay |
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date | Wed, 28 Oct 2020 01:45:32 +0000 |
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668434d3fc8a
"planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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1 import modlamp |
668434d3fc8a
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2 from modlamp.analysis import * |
668434d3fc8a
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3 |
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4 from plotly.subplots import make_subplots |
668434d3fc8a
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5 import plotly.graph_objects as go |
668434d3fc8a
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6 from modlamp.analysis import GlobalAnalysis |
668434d3fc8a
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7 from modlamp.analysis import * |
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8 |
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9 import pandas as pd |
668434d3fc8a
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10 import os, sys |
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11 import argparse |
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12 |
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13 parser = argparse.ArgumentParser(description='Deployment tool') |
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14 subparsers = parser.add_subparsers() |
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16 CalcAAFreq = subparsers.add_parser('CalcAAFreq') |
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17 CalcAAFreq.add_argument("-I","--InFile", required=True, default=None, help="") |
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18 CalcAAFreq.add_argument("-T","--PlotFile", required=False, default='out.pdf', help="out.pdf") |
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19 CalcAAFreq.add_argument("--OutFile", required=False, default='Out.tsv', help="Out.tsv") |
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20 |
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21 H = subparsers.add_parser('H') |
668434d3fc8a
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22 H.add_argument("-I","--InFile", required=True, default=None, help="") |
668434d3fc8a
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23 H.add_argument("-S","--Scale", required=False, default='eisenberg', help="hydrophobicity scale to use. For available scales, see modlamp.descriptors.PeptideDescriptor.") |
668434d3fc8a
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24 H.add_argument("--OutFile", required=False, default='Out.tsv', help="Out.tsv") |
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25 |
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26 uH = subparsers.add_parser('uH') |
668434d3fc8a
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27 uH.add_argument("-I","--InFile", required=True, default=None, help="") |
668434d3fc8a
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28 uH.add_argument("-S","--Scale", required=False, default='eisenberg', help="hydrophobicity scale to use. For available scales, see modlamp.descriptors.PeptideDescriptor.") |
668434d3fc8a
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29 uH.add_argument("-W", "--Window", required=False, default=1000, help="") |
668434d3fc8a
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30 uH.add_argument("-A", "--Angle", required=False, default=100, help="") |
668434d3fc8a
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31 uH.add_argument("-M", "--Modality", required=False, default='max', help="") |
668434d3fc8a
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32 uH.add_argument("--OutFile", required=False, default='Out.tsv', help="Out.tsv") |
668434d3fc8a
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33 |
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34 charge = subparsers.add_parser('charge') |
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35 charge.add_argument("-I","--InFile", required=True, default=None, help="") |
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36 charge.add_argument("-p", "--ph", required=False, default=7.0, help="") |
668434d3fc8a
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37 charge.add_argument("-A", "--Amide", required=False, default=True, help="") |
668434d3fc8a
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38 charge.add_argument("--OutFile", required=False, default='Out.tsv', help="Out.tsv") |
668434d3fc8a
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39 |
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40 Len = subparsers.add_parser('Len') |
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41 Len.add_argument("-I","--InFile", required=True, default=None, help="") |
668434d3fc8a
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42 Len.add_argument("--OutFile", required=False, default='Out.tsv', help="Out.tsv") |
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43 |
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44 PlotSaummary = subparsers.add_parser('PlotSummary') |
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45 PlotSaummary.add_argument("-I1","--InFile1", required=True, default=None, help="") |
668434d3fc8a
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46 PlotSaummary.add_argument("-I2", "--InFile2", required=True, default=None, help="Out.tsv") |
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47 PlotSaummary.add_argument("--PlotFile", required=False, default='Out.pdf', help="out.pdf") |
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48 PlotSaummary.add_argument("--htmlFname", required="False", default='report.html', help="Output file") |
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49 PlotSaummary.add_argument("-O","--htmlOutDir", required=False, default=os.path.join(os.getcwd(),'report_dir'), help="HTML Out Dir") |
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50 PlotSaummary.add_argument("-Wp","--Workdirpath", required=False, default=os.getcwd(), help="Working Directory Path") |
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51 PlotSaummary.add_argument("-fn", "--First_lib_name", required=True, help="Name of the fist peptide data") |
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52 PlotSaummary.add_argument("-sn", "--Second_lib_name", required=True, help="Name of the second peptide data") |
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55 args = parser.parse_args() |
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59 def SummaryPlot(Lib_1, Lib_2, First_lib_name, Second_lib_Name, Workdirpath, htmlOutDir, htmlFname): |
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61 if not os.path.exists(htmlOutDir): |
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62 os.makedirs(htmlOutDir) |
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65 AA = ['A','C','D','E','F','G','H','I','K','L','M','N','P','Q','R','S','T','V','W','Y'] |
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66 |
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67 Pep1, Index1 = ReturnPeptide(Lib_1) |
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68 Pep2, Index2 = ReturnPeptide(Lib_2) |
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69 |
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70 fig = make_subplots( |
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71 rows=2, cols=3, |
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72 specs=[[{"type": "xy"}, {"type": "histogram"}, {"type": "box"} ],[{"type": "violin"}, {"type": "violin"}, {"type": "scatter3d"} ]], |
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73 subplot_titles=(" Amino Acid Fraction", "Global Charge", "Length Distribution", "Global Hydrophobicity", "Global Hydrophobic Movement", "Scatter Plot")) |
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74 |
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75 |
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76 ######################################### |
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77 g = GlobalAnalysis([Pep1, Pep2]) |
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78 df = g.calc_aa_freq(plot=False) |
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79 |
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80 data1 = g.aafreq[0] |
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81 data2 = g.aafreq[1] |
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82 |
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83 fig.add_trace(go.Bar(x=AA, y=data1, name=First_lib_name, marker_color='#1F77B4'), row=1, col=1) |
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84 fig.add_trace(go.Bar( x=AA, y=data2,name=Second_lib_Name, marker_color='#FF7F0E'), row=1, col=1) |
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85 fig.update_layout(showlegend=True) |
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86 ########################################## |
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87 |
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88 |
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89 ######################################### |
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90 d1 = GlobalDescriptor(Pep1) |
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91 d1.calculate_charge(ph=7.4, amide=True) |
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92 charge1 = [x[0] for x in d1.descriptor] |
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93 |
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94 d2 = GlobalDescriptor(Pep2) |
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95 d2.calculate_charge(ph=7.4, amide=True) |
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96 charge2 = [x[0] for x in d2.descriptor] |
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97 |
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98 fig.add_trace(go.Histogram(x=charge1, histnorm='probability', marker_color='#1F77B4', name=First_lib_name, xbins=dict( start=min(charge1), end=max(charge1), ), opacity=0.75), row=1, col=2) |
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99 fig.add_trace(go.Histogram( x=charge2, histnorm='probability', marker_color='#FF7F0E', name=Second_lib_Name, xbins=dict( start=min(charge2), end=max(charge2), ), opacity=0.75), row=1, col=2 ) |
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100 #fig.update_layout( , xaxis_title_text='Charge', yaxis_title_text='Fraction', bargap=0.1, bargroupgap=0.1 ) |
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101 ########################################### |
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102 |
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103 ############################################################################## |
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104 Length1 = [len(x) for x in Pep1] |
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105 Length2 = [len(x) for x in Pep2] |
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106 |
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107 fig.add_trace(go.Box(y=Length1, name=First_lib_name, marker_color='#1F77B4'), row=1, col=3) |
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108 fig.add_trace(go.Box(y=Length2, name=Second_lib_Name, marker_color='#FF7F0E'), row=1, col=3) |
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109 ############################################################################# |
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110 |
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111 ######################################################################## |
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112 g = GlobalAnalysis([Pep1, Pep2]) |
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113 |
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114 g.calc_H() |
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115 |
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116 h1 = g.H[0] |
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117 h2 = g.H[1] |
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118 |
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119 fig.add_trace(go.Violin( y=h1,box_visible=True, name =First_lib_name, marker_color='#1F77B4', meanline_visible=True), row=2, col=1) |
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120 fig.add_trace(go.Violin(y=h2,box_visible=True, name=Second_lib_Name, marker_color='#FF7F0E', meanline_visible=True), row=2, col=1) |
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121 ################################################################# |
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122 |
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123 ##################################### |
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124 uH = GlobalAnalysis([Pep1, Pep2]) |
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125 uH.calc_uH() |
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126 |
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127 uh1 = uH.uH[0] |
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128 uh2 = uH.uH[1] |
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129 |
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130 fig.add_trace(go.Violin( y=uh1,box_visible=True, name =First_lib_name, marker_color='#1F77B4', meanline_visible=True), row=2, col=2) |
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131 fig.add_trace(go.Violin(y=uh2,box_visible=True, name=Second_lib_Name, marker_color='#FF7F0E', meanline_visible=True), row=2, col=2) |
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132 ####################################### |
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133 |
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134 |
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135 ############################################ |
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136 fig.add_trace(go.Scatter3d(x=h1, y=uh1, z=charge1, marker_color='#1F77B4', mode='markers', name=First_lib_name, marker_size=3.0),row=2, col=3) |
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137 fig.add_trace(go.Scatter3d(x=h2, y=uh2, z=charge2, marker_color='#FF7F0E', mode='markers', name=Second_lib_Name, marker_size=3.0), row=2, col=3) |
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138 fig.update_layout(scene = dict(xaxis_title='Hydrophobicity', yaxis_title='Hydrophobic Movement', zaxis_title='Charge'),uniformtext_minsize=4, font=dict( |
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139 family="Times New Roman", |
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140 size=12, |
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141 color="black")) |
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142 ########################################### |
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143 |
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144 fig.update_xaxes(title_text="Amino Acid", row=1, col=1) |
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145 fig.update_xaxes(title_text="Global Charge", row=1, col=2) |
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146 fig.update_xaxes(title_text="Peptide dataset", showgrid=False, row=1, col=3) |
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147 fig.update_xaxes(title_text="Peptide dataset", row=2, col=1) |
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148 fig.update_xaxes(title_text="Peptide dataset", row=2, col=2) |
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149 |
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150 fig.update_yaxes(title_text="Fraction", row=1, col=1) |
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151 fig.update_yaxes(title_text="Fraction", row=1, col=2) |
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152 fig.update_yaxes(title_text="Length", row=1, col=3) |
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153 fig.update_yaxes(title_text="Global hydrophobicity", row=2, col=1) |
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154 fig.update_yaxes(title_text="Global hydrophobic Movement", row=2, col=2) |
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155 fig.write_html(os.path.join(Workdirpath, htmlOutDir, htmlFname)) |
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156 #fig.show() |
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157 |
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158 def ReturnPeptide(Infile): |
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159 |
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160 file = open(Infile) |
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161 lines = file.readlines() |
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162 |
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163 Index = [] |
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164 Pep = [] |
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165 |
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166 for line in lines: |
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167 if '>' in line: |
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168 line = line.strip('\n') |
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169 line = line.strip('\r') |
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170 Index.append(line.strip('\n')) |
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171 else: |
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172 line = line.strip('\n') |
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173 line = line.strip('\r') |
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174 Pep.append(line) |
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175 return Pep, Index |
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176 |
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177 if sys.argv[1] == 'CalcAAFreq': |
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178 |
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179 Pep, Index = ReturnPeptide(args.InFile) |
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180 g = GlobalAnalysis(Pep) |
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181 g.calc_aa_freq(plot=False, color='#83AF9B') |
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182 df1 = pd.DataFrame(g.aafreq[0], columns=['aa_freq']) |
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183 df1.to_csv(args.OutFile, sep='\t', index=None) |
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184 |
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185 elif sys.argv[1] == 'H': |
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186 |
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187 Pep, _ = ReturnPeptide(args.InFile) |
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188 g = GlobalAnalysis(Pep) |
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189 g.calc_H(args.Scale) |
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190 df1 = pd.DataFrame(g.H[0].T, columns=['H']) |
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191 df1.to_csv(args.OutFile, sep='\t', index=None) |
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192 |
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193 elif sys.argv[1] == 'uH': |
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194 |
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195 Pep, _ = ReturnPeptide(args.InFile) |
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196 |
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197 g = GlobalAnalysis(Pep) |
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198 g.calc_uH(int(args.Window), int(args.Angle), args.Modality) |
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199 df1 = pd.DataFrame(g.uH[0].T, columns=['uH']) |
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200 df1.to_csv(args.OutFile, sep='\t', index=None) |
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201 |
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202 elif sys.argv[1] == 'charge': |
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203 |
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204 Pep, _ = ReturnPeptide(args.InFile) |
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205 |
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206 g = GlobalAnalysis(Pep) |
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207 |
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208 if args.Amide == 'true': |
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209 amide = True |
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210 else: |
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211 amide = False |
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212 |
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213 g.calc_charge(float(args.ph), amide) |
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214 df1 = pd.DataFrame(g.charge[0].T, columns=['charge']) |
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215 df1.to_csv(args.OutFile, sep='\t', index=None) |
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216 |
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217 elif sys.argv[1] == 'Len': |
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218 |
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219 Pep, _ = ReturnPeptide(args.InFile) |
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220 df1 = pd.DataFrame([len(x) for x in Pep], columns=['c']) |
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221 df1.to_csv( args.OutFile, sep='\t', index=None) |
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222 |
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223 elif sys.argv[1] == "PlotSummary": |
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224 |
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225 SummaryPlot(args.InFile1, args.InFile2, args.First_lib_name, args.Second_lib_name, args.Workdirpath, args.htmlOutDir, args.htmlFname) |
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226 |
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227 |
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228 |
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229 |
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230 |
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231 |