Mercurial > repos > davidvanzessen > shm_csr

annotate sequence_overview.py @ 92:cf8ad181628f draft

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planemo upload commit 36be3b053802693392f935e6619ba3f2b1704e3c
author rhpvorderman
date Mon, 12 Dec 2022 12:32:44 +0000
parents
children 8fcf31272f6e
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92
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1 #!/usr/bin/env/python3
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2
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3 """Create a HTML sequence overview"""
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4
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5 import argparse
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6 import os
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7 import typing
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8 from collections import defaultdict
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9 from pathlib import Path
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10 from typing import Dict, Iterable, List
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11
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12
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13 class SequenceTableRow(typing.NamedTuple):
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14 sequence_id: str
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15 sequence: str
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16 best_match: str
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17 functionality: str
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18
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19
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20 class SequenceStats:
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21 __slots__ = ("counts", "table_rows")
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22
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23 def __init__(self):
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24 self.counts: Dict[str, int] = {
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25 "IGA1": 0,
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26 "IGA2": 0,
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27 "IGE": 0,
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28 "IGG1": 0,
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29 "IGG2": 0,
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30 "IGG3": 0,
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31 "IGG4": 0,
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32 "IGM": 0,
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33 "unmatched": 0}
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34 self.table_rows: List[SequenceTableRow] = []
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35
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36
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37 def get_sequence_stats(before_unique: str,
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38 sequence_columns: List[str]):
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39 sequence_statistics = defaultdict(SequenceStats)
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40 with open(before_unique, "rt") as table:
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41 header = next(table)
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42 header_columns = header.strip("\n").split("\t")
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43 for line in table:
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44 values = line.strip("\n").split("\t")
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45 row_dict = dict(zip(header_columns, values))
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46 sequence = " ".join(row_dict[column] for column in sequence_columns)
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47 best_match = row_dict["best_match"]
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48 original_match = best_match
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49 if best_match.startswith("unmatched"):
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50 best_match = "unmatched"
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51 sequence_statistics[sequence].counts[best_match] += 1
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52 functionality = row_dict["Functionality"]
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53 sequence_statistics[sequence].table_rows.append(
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54 SequenceTableRow(row_dict["Sequence.ID"], sequence,
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55 original_match, functionality))
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56 return sequence_statistics
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57
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58
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59 def get_background_color(value: str):
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60 if value in ("TRUE", "T"):
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61 return "#eafaf1"
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62 elif value in ("FALSE", "F"):
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63 return "#f9ebea"
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64 try:
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65 flt = float(value)
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66 except ValueError:
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67 return "white"
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68 if flt > 0:
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69 return "#eaecee"
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70 return "white"
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71
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72
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73 def td(val):
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74 return f"<td bgcolor='{get_background_color(val)}'>{val}</td>"
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75
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76
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77 def tr(val: Iterable[str]):
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78 return f"<tr>{''.join(td(v) for v in val)}</tr>\n"
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79
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80
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81 def make_link(link, val):
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82 return f"<a href='{link}'>{val}</a>"
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83
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84
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85 def tbl(df: Iterable[Iterable[str]]):
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86 return f"<table border='1'>{''.join(tr(v) for v in df)}</table>\n"
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87
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88
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89 def to_bool_str(cond):
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90 return "TRUE" if cond else "FALSE"
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91
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92
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93 def sequence_overview(before_unique: str,
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94 outdir: str,
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95 empty_region_filter: str):
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96 os.makedirs(outdir, exist_ok=True)
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97 sequence_columns = [
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98 "FR1.IMGT.seq", "CDR1.IMGT.seq", "FR2.IMGT.seq", "CDR2.IMGT.seq",
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99 "FR3.IMGT.seq", "CDR3.IMGT.seq"]
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100 if empty_region_filter == "leader":
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101 sequence_columns = sequence_columns
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102 elif empty_region_filter == "FR1":
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103 sequence_columns = sequence_columns[1:]
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104 elif empty_region_filter == "CDR1":
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105 sequence_columns = sequence_columns[2:]
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106 elif empty_region_filter == "FR2":
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107 sequence_columns = sequence_columns[3:]
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108 else:
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109 raise ValueError(f"Unknown region filter: {empty_region_filter}")
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110 main_html_file = os.path.join(outdir, "index.html")
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111 by_id_file = os.path.join(outdir, "by_id.html")
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112 with open(main_html_file, "wt") as main_html, open(by_id_file, "wt") as by_id:
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113 main_html.write("<center><img src='data:image/png;base64,"
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114 "iVBORw0KGgoAAAANSUhEUgAAAA8AAAAPCAYAAAA71pVKAAAAzElEQ"
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115 "VQoka2TwQ2CQBBFpwTshw4ImW8ogJMlUIMmhNCDxgasAi50oSXA8X"
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116 "lAjCG7aqKTzGX/vsnM31mzR0gk7tTudO5MEizpzvQ4ryUSe408J3X"
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117 "n+grE0p1rnpOamVmWsZG4rS+dzzAMsN8Hi9yyjI1JNGtxu4VxBJgL"
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118 "RLpoTKIPiW0LlwtUVRTubW2OBGUJu92cZRmdfbKQMAw8o+vi5v0fL"
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119 "orZ7Y9waGYJjsf38DJz0O1PsEQffOcv4Sa6YYfDDJ5Obzbsp93+5Vf"
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120 "dATueO1fdLdI0AAAAAElFTkSuQmCC'"
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121 "> Please note that this tab is based on all "
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122 "sequences before filter unique sequences and the "
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123 "remove duplicates based on filters are applied. In "
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124 "this table only sequences occuring more than once "
cf8ad181628f planemo upload commit 36be3b053802693392f935e6619ba3f2b1704e3c
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125 "are included. </center>")
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126 main_html.write("<table border='1' class='pure-table pure-table-striped'>")
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127 main_html.write(f"<caption>"
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128 f"{'+'.join(column.split('.')[0] for column in sequence_columns)} sequences "
cf8ad181628f planemo upload commit 36be3b053802693392f935e6619ba3f2b1704e3c
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129 f"that show up more than once</caption>")
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130 main_html.write("<tr>")
cf8ad181628f planemo upload commit 36be3b053802693392f935e6619ba3f2b1704e3c
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131 main_html.write("<th>Sequence</th><th>Functionality</th><th>IGA1</th>"
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132 "<th>IGA2</th><th>IGG1</th><th>IGG2</th><th>IGG3</th>"
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133 "<th>IGG4</th><th>IGM</th><th>IGE</th><th>UN</th>")
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134 main_html.write("<th>total IGA</th><th>total IGG</th><th>total IGM</th>"
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135 "<th>total IGE</th><th>number of subclasses</th>"
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136 "<th>present in both IGA and IGG</th>"
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137 "<th>present in IGA, IGG and IGM</th>"
cf8ad181628f planemo upload commit 36be3b053802693392f935e6619ba3f2b1704e3c
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138 "<th>present in IGA, IGG and IGE</th>"
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139 "<th>present in IGA, IGG, IGM and IGE</th>"
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140 "<th>IGA1+IGA2</th>")
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141 main_html.write("<th>IGG1+IGG2</th><th>IGG1+IGG3</th>"
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142 "<th>IGG1+IGG4</th><th>IGG2+IGG3</th>"
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143 "<th>IGG2+IGG4</th><th>IGG3+IGG4</th>")
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144 main_html.write("<th>IGG1+IGG2+IGG3</th><th>IGG2+IGG3+IGG4</th>"
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145 "<th>IGG1+IGG2+IGG4</th><th>IGG1+IGG3+IGG4</th>"
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146 "<th>IGG1+IGG2+IGG3+IGG4</th>")
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147 main_html.write("</tr>\n")
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148 sequence_stats = get_sequence_stats(before_unique, sequence_columns)
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149 sorted_sequences = sorted(sequence_stats.keys())
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150
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151 single_sequences = 0 # sequence only found once, skipped
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152 in_multiple = 0 # same sequence across multiple subclasses
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153 multiple_in_one = 0 # same sequence multiple times in one subclass
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154 unmatched = 0 # all the sequences are unmatched
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155 some_unmatched = 0 # one or more sequences in a clone are unmatched
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156 matched = 0 # should be the same als matched sequences
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157
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158 for i, sequence in enumerate(sorted_sequences, start=1):
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159 sequence_stat: SequenceStats = sequence_stats[sequence]
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160 count_dict = sequence_stat.counts
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161 class_sum = sum(count_dict.values())
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162 if class_sum == 1:
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163 single_sequences += 1
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164 continue
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165 if count_dict["unmatched"] == class_sum:
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166 unmatched += 1
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167 continue
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168 in_classes = sum(1 for key, value in count_dict.items()
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169 if value > 0 and key != "unmatched")
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170 matched += in_classes
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171 if any(value == class_sum for value in count_dict.values()):
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172 multiple_in_one += 1
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173 elif count_dict["unmatched"] > 0:
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174 some_unmatched += 1
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175 else:
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176 in_multiple += 1
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177 # Use a dict so we can preserve the order and get all the unique
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178 # items. With a set the order is not preserved.
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179 functionality_dict = {row.functionality: None
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180 for row in sequence_stat.table_rows}
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181 functionality = ",".join(functionality_dict.keys())
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182 links: Dict[str, str] = {}
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183 for key, value in count_dict.items():
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184 name_key = "un" if key == "unmatched" else key
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185 html_file = f"{name_key}_{i}.html"
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186 links[key] = html_file
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187 if value > 0:
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188 rows = [row for row in sequence_stat.table_rows
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189 # Startswith to also get unmatched columns
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190 if row.best_match.startswith(key)]
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191 Path(outdir, html_file).write_text(tbl(rows))
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192 for row in rows:
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193 by_id.write(make_link(html_file, row.sequence_id) + "<br />\n")
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194 iga_count = count_dict["IGA1"] + count_dict["IGA2"]
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195 igg_count = count_dict["IGG1"] + count_dict["IGG2"] + \
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196 count_dict["IGG3"] + count_dict["IGG4"]
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197
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198 contained_classes = set(key for key, value
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199 in count_dict.items() if value > 0)
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200 if iga_count:
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201 contained_classes.add("IGA")
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202 if igg_count:
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203 contained_classes.add("IGG")
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204 main_row = [
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205 sequence, functionality,
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206 make_link(links["IGA1"], count_dict["IGA1"]),
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207 make_link(links["IGA2"], count_dict["IGA2"]),
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208 make_link(links["IGG1"], count_dict["IGG1"]),
cf8ad181628f planemo upload commit 36be3b053802693392f935e6619ba3f2b1704e3c
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209 make_link(links["IGG2"], count_dict["IGG2"]),
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210 make_link(links["IGG3"], count_dict["IGG3"]),
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211 make_link(links["IGG4"], count_dict["IGG4"]),
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212 make_link(links["IGM"], count_dict["IGM"]),
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213 make_link(links["IGE"], count_dict["IGE"]),
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214 make_link(links["unmatched"], count_dict["unmatched"]),
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215 iga_count,
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216 igg_count,
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217 count_dict["IGM"],
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218 count_dict["IGE"],
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219 in_classes,
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220 to_bool_str({"IGA", "IGG"}.issubset(contained_classes)),
cf8ad181628f planemo upload commit 36be3b053802693392f935e6619ba3f2b1704e3c
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221 to_bool_str({"IGA", "IGG", "IGM"}.issubset(contained_classes)),
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222 to_bool_str({"IGA", "IGG", "IGE"}.issubset(contained_classes)),
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223 to_bool_str({"IGA", "IGG", "IGM", "IGE"}.issubset(contained_classes)),
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224 to_bool_str({"IGA1", "IGA2"}.issubset(contained_classes)),
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225 to_bool_str({"IGG1", "IGG2"}.issubset(contained_classes)),
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226 to_bool_str({"IGG1", "IGG3"}.issubset(contained_classes)),
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227 to_bool_str({"IGG1", "IGG4"}.issubset(contained_classes)),
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228 to_bool_str({"IGG2", "IGG3"}.issubset(contained_classes)),
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229 to_bool_str({"IGG2", "IGG4"}.issubset(contained_classes)),
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230 to_bool_str({"IGG3", "IGG4"}.issubset(contained_classes)),
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231 to_bool_str({"IGG1", "IGG2", "IGG3"}.issubset(contained_classes)),
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232 to_bool_str({"IGG2", "IGG3", "IGG4"}.issubset(contained_classes)),
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233 to_bool_str({"IGG1", "IGG2", "IGG4"}.issubset(contained_classes)),
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234 to_bool_str({"IGG1", "IGG3", "IGG4"}.issubset(contained_classes)),
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235 to_bool_str({"IGG1", "IGG2", "IGG3", "IGG4"}.issubset(contained_classes)),
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236 ]
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237 main_html.write(tr(main_row))
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238 main_html.write("</table>")
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239
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240
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241 def argument_parser() -> argparse.ArgumentParser:
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242 parser = argparse.ArgumentParser()
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243 parser.add_argument("--before-unique", help="File with the overview before unique filters")
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244 parser.add_argument("--outdir", help="Output directory")
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245 parser.add_argument("--empty-region-filter")
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246 return parser
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247
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248
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249 def main():
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250 args = argument_parser().parse_args()
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251 sequence_overview(args.before_unique,
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252 args.outdir,
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253 args.empty_region_filter)
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254
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255
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256 if __name__ == "__main__":
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257 main()