htsworkflow/pipelines/summary.py

   1 """
   2 Analyze the Summary.htm file produced by GERALD
   3 """
   4 import logging
   5 import types
   6 from pprint import pprint
   7
   8 from htsworkflow.pipelines.runfolder import ElementTree
   9 from htsworkflow.util.ethelp import indent, flatten
  10
  11 nan = float('nan')
  12
  13 class Summary(object):
  14     """
  15     Extract some useful information from the Summary.htm file
  16     """
  17     XML_VERSION = 3
  18     SUMMARY = 'Summary'
  19
  20     class LaneResultSummary(object):
  21         """
  22         Parse the LaneResultSummary table out of Summary.htm
  23         Mostly for the cluster number
  24         """
  25         LANE_RESULT_SUMMARY = 'LaneResultSummary'
  26         TAGS = {
  27           'LaneYield': 'lane_yield',
  28           'Cluster': 'cluster', # Raw
  29           'ClusterPF': 'cluster_pass_filter',
  30           'AverageFirstCycleIntensity': 'average_first_cycle_intensity',
  31           'PercentIntensityAfter20Cycles': 'percent_intensity_after_20_cycles',
  32           'PercentPassFilterClusters': 'percent_pass_filter_clusters',
  33           'PercentPassFilterAlign': 'percent_pass_filter_align',
  34           'AverageAlignmentScore': 'average_alignment_score',
  35           'PercentErrorRate': 'percent_error_rate'
  36         }
  37         # These are tags that have mean/stdev as found in the GERALD Summary.xml file
  38         GERALD_TAGS = {
  39           #'laneYield': 'lane_yield', #this is just a number
  40           'clusterCountRaw': 'cluster', # Raw
  41           'clusterCountPF': 'cluster_pass_filter',
  42           'oneSig': 'average_first_cycle_intensity',
  43           'signal20AsPctOf1': 'percent_intensity_after_20_cycles',
  44           'percentClustersPF': 'percent_pass_filter_clusters',
  45           'percentUniquelyAlignedPF': 'percent_pass_filter_align',
  46           'averageAlignScorePF': 'average_alignment_score',
  47           'errorPF': 'percent_error_rate'
  48         }
  49
  50         def __init__(self, html=None, xml=None):
  51             self.lane = None
  52             self.end = 0
  53             self.lane_yield = None
  54             self.cluster = None
  55             self.cluster_pass_filter = None
  56             self.average_first_cycle_intensity = None
  57             self.percent_intensity_after_20_cycles = None
  58             self.percent_pass_filter_clusters = None
  59             self.percent_pass_filter_align = None
  60             self.average_alignment_score = None
  61             self.percent_error_rate = None
  62
  63             if html is not None:
  64                 self.set_elements_from_html(html)
  65             if xml is not None:
  66                 self.set_elements(xml)
  67
  68         def set_elements_from_html(self, data):
  69             if not len(data) in (8,10):
  70                 raise RuntimeError("Summary.htm file format changed, len(data)=%d" % (len(data),))
  71
  72             # same in pre-0.3.0 Summary file and 0.3 summary file
  73             self.lane = int(data[0])
  74
  75             if len(data) == 8:
  76                 parsed_data = [ parse_mean_range(x) for x in data[1:] ]
  77                 # this is the < 0.3 Pipeline version
  78                 self.cluster = parsed_data[0]
  79                 self.average_first_cycle_intensity = parsed_data[1]
  80                 self.percent_intensity_after_20_cycles = parsed_data[2]
  81                 self.percent_pass_filter_clusters = parsed_data[3]
  82                 self.percent_pass_filter_align = parsed_data[4]
  83                 self.average_alignment_score = parsed_data[5]
  84                 self.percent_error_rate = parsed_data[6]
  85             elif len(data) == 10:
  86                 parsed_data = [ parse_mean_range(x) for x in data[2:] ]
  87                 # this is the >= 0.3 summary file
  88                 self.lane_yield = data[1]
  89                 self.cluster = parsed_data[0]
  90                 self.cluster_pass_filter = parsed_data[1]
  91                 self.average_first_cycle_intensity = parsed_data[2]
  92                 self.percent_intensity_after_20_cycles = parsed_data[3]
  93                 self.percent_pass_filter_clusters = parsed_data[4]
  94                 self.percent_pass_filter_align = parsed_data[5]
  95                 self.average_alignment_score = parsed_data[6]
  96                 self.percent_error_rate = parsed_data[7]
  97
  98         def set_elements_from_gerald_xml(self, read, element):
  99             self.lane = int(element.find('laneNumber').text)
 100             self.end = read
 101             self.lane_yield = int(element.find('laneYield').text)
 102
 103             for GeraldName, LRSName in Summary.LaneResultSummary.GERALD_TAGS.items():
 104                 node = element.find(GeraldName)
 105                 if node is None:
 106                     logging.info("Couldn't find %s" % (GeraldName))
 107                 setattr(self, LRSName, parse_xml_mean_range(node))
 108
 109         def get_elements(self):
 110             lane_result = ElementTree.Element(
 111                             Summary.LaneResultSummary.LANE_RESULT_SUMMARY,
 112                             {'lane': unicode(self.lane), 'end': unicode(self.end)})
 113             for tag, variable_name in Summary.LaneResultSummary.TAGS.items():
 114                 value = getattr(self, variable_name)
 115                 if value is None:
 116                     continue
 117                 # it looks like a sequence
 118                 elif type(value) in (types.TupleType, types.ListType):
 119                     element = make_mean_range_element(
 120                       lane_result,
 121                       tag,
 122                       *value
 123                     )
 124                 else:
 125                     element = ElementTree.SubElement(lane_result, tag)
 126                     element.text = unicode(value)
 127             return lane_result
 128
 129         def set_elements(self, tree):
 130             if tree.tag != Summary.LaneResultSummary.LANE_RESULT_SUMMARY:
 131                 raise ValueError('Expected %s' % (
 132                         Summary.LaneResultSummary.LANE_RESULT_SUMMARY))
 133             self.lane = int(tree.attrib['lane'])
 134             # default to the first end, for the older summary files
 135             # that are single ended
 136             self.end = int(tree.attrib.get('end', 0))
 137             tags = Summary.LaneResultSummary.TAGS
 138             for element in list(tree):
 139                 try:
 140                     variable_name = tags[element.tag]
 141                     setattr(self, variable_name,
 142                             parse_summary_element(element))
 143                 except KeyError, e:
 144                     logging.warn('Unrecognized tag %s' % (element.tag,))
 145
 146     def __init__(self, filename=None, xml=None):
 147         # lane results is a list of 1 or 2 ends containing
 148         # a dictionary of all the lanes reported in this
 149         # summary file
 150         self.lane_results = [{}]
 151
 152         if filename is not None:
 153             self._extract_lane_results(filename)
 154         if xml is not None:
 155             self.set_elements(xml)
 156
 157     def __getitem__(self, key):
 158         return self.lane_results[key]
 159
 160     def __len__(self):
 161         return len(self.lane_results)
 162
 163     def _flattened_row(self, row):
 164         """
 165         flatten the children of a <tr>...</tr>
 166         """
 167         return [flatten(x) for x in row.getchildren() ]
 168
 169     def _parse_table(self, table):
 170         """
 171         assumes the first line is the header of a table,
 172         and that the remaining rows are data
 173         """
 174         rows = table.getchildren()
 175         data = []
 176         for r in rows:
 177             data.append(self._flattened_row(r))
 178         return data
 179
 180     def _extract_lane_results(self, pathname):
 181         """
 182         Extract just the lane results.
 183         Currently those are the only ones we care about.
 184         """
 185
 186         tables = self._extract_named_tables(pathname)
 187
 188
 189     def _extract_named_tables(self, pathname):
 190         """
 191         extract all the 'named' tables from a Summary.htm file
 192         and return as a dictionary
 193
 194         Named tables are <h2>...</h2><table>...</table> pairs
 195         The contents of the h2 tag is considered to the name
 196         of the table.
 197         """
 198         # tree = ElementTree.parse(pathname).getroot()
 199         # hack for 1.1rc1, this should be removed when possible.
 200         file_body = open(pathname).read()
 201         file_body = file_body.replace('CHASTITY<=', 'CHASTITY&lt;=')
 202         tree = ElementTree.fromstring(file_body)
 203
 204         # are we reading the xml or the html version of the Summary file?
 205         if tree.tag.lower() == 'summary':
 206             # summary version
 207             tables = self._extract_named_tables_from_gerald_xml(tree)
 208         elif tree.tag.lower() == 'html':
 209             # html version
 210             tables = self._extract_named_tables_from_html(tree)
 211             table_names = [ ('Lane Results Summary', 0),
 212                             ('Lane Results Summary : Read 1', 0),
 213                             ('Lane Results Summary : Read 2', 1),]
 214             for name, end in table_names:
 215                 if tables.has_key(name):
 216                     self._extract_lane_results_for_end(tables, name, end)
 217
 218         if len(self.lane_results[0])  == 0:
 219             logging.warning("No Lane Results Summary Found in %s" % (pathname,))
 220
 221     def _extract_named_tables_from_gerald_xml(self, tree):
 222         """
 223         Extract useful named tables from a gerald created Summary.xml file
 224         """
 225         # using the function to convert to lower instead of just writing it
 226         # makes the tag easier to read (IMO)
 227         useful_tables = ['LaneResultsSummary'.lower(),]
 228
 229         tables ={}
 230         for child in tree.getchildren():
 231             if child.tag.lower() in  useful_tables:
 232                 read_tree = child.find('Read')
 233                 # we want 0 based.
 234                 read = int(read_tree.find('readNumber').text)-1
 235                 for element in read_tree.getchildren():
 236                     if element.tag.lower() == "lane":
 237                         lrs = Summary.LaneResultSummary()
 238                         lrs.set_elements_from_gerald_xml(read, element)
 239                         self.lane_results[lrs.end][lrs.lane] = lrs
 240         # probably not useful
 241         return tables
 242
 243     ###### START HTML Table Extraction ########
 244     def _extract_named_tables_from_html(self, tree):
 245         body = tree.find('body')
 246         tables = {}
 247         for i in range(len(body)):
 248             if body[i].tag == 'h2' and body[i+1].tag == 'table':
 249                 # we have an interesting table
 250                 name = flatten(body[i])
 251                 table = body[i+1]
 252                 data = self._parse_table(table)
 253                 tables[name] = data
 254         return tables
 255
 256     def _extract_lane_results_for_end(self, tables, table_name, end):
 257         """
 258         extract the Lane Results Summary table
 259         """
 260         # parse lane result summary
 261         lane_summary = tables[table_name]
 262         # this is version 1 of the summary file
 263         if len(lane_summary[-1]) == 8:
 264             # strip header
 265             headers = lane_summary[0]
 266             # grab the lane by lane data
 267             lane_summary = lane_summary[1:]
 268
 269         # len(lane_summary[-1] = 10 is version 2 of the summary file
 270         #                      = 9  is version 3 of the Summary.htm file
 271         elif len(lane_summary[-1]) in (9, 10):
 272             # lane_summary[0] is a different less specific header row
 273             headers = lane_summary[1]
 274             lane_summary = lane_summary[2:10]
 275             # after the last lane, there's a set of chip wide averages
 276
 277         # append an extra dictionary if needed
 278         if len(self.lane_results) < (end + 1):
 279           self.lane_results.append({})
 280
 281         for r in lane_summary:
 282             lrs = Summary.LaneResultSummary(html=r)
 283             lrs.end = end
 284             self.lane_results[lrs.end][lrs.lane] = lrs
 285     ###### END HTML Table Extraction ########
 286
 287     def get_elements(self):
 288         summary = ElementTree.Element(Summary.SUMMARY,
 289                                       {'version': unicode(Summary.XML_VERSION)})
 290         for end in self.lane_results:
 291             for lane in end.values():
 292                 summary.append(lane.get_elements())
 293         return summary
 294
 295     def set_elements(self, tree):
 296         if tree.tag != Summary.SUMMARY:
 297             return ValueError("Expected %s" % (Summary.SUMMARY,))
 298         xml_version = int(tree.attrib.get('version', 0))
 299         if xml_version > Summary.XML_VERSION:
 300             logging.warn('Summary XML tree is a higher version than this class')
 301         for element in list(tree):
 302             lrs = Summary.LaneResultSummary()
 303             lrs.set_elements(element)
 304             if len(self.lane_results) < (lrs.end + 1):
 305               self.lane_results.append({})
 306             self.lane_results[lrs.end][lrs.lane] = lrs
 307
 308     def is_paired_end(self):
 309       return len(self.lane_results) == 2
 310
 311     def dump(self):
 312         """
 313         Debugging function, report current object
 314         """
 315         tree = self.get_elements()
 316         print ElementTree.tostring(tree)
 317
 318 def tonumber(v):
 319     """
 320     Convert a value to int if its an int otherwise a float.
 321     """
 322     try:
 323         v = int(v)
 324     except ValueError, e:
 325         v = float(v)
 326     return v
 327
 328 def parse_mean_range(value):
 329     """
 330     Parse values like 123 +/- 4.5
 331     """
 332     if value.strip() == 'unknown':
 333         return nan, nan
 334
 335     values = value.split()
 336     if len(values) == 1:
 337         if values[0] == '+/-':
 338             return nan,nan
 339         else:
 340             return tonumber(values[0])
 341
 342     average, pm, deviation = values
 343     if pm != '+/-':
 344         raise RuntimeError("Summary.htm file format changed")
 345     return tonumber(average), tonumber(deviation)
 346
 347 def make_mean_range_element(parent, name, mean, deviation):
 348     """
 349     Make an ElementTree subelement <Name mean='mean', deviation='deviation'/>
 350     """
 351     element = ElementTree.SubElement(parent, name,
 352                                      { 'mean': unicode(mean),
 353                                        'deviation': unicode(deviation)})
 354     return element
 355
 356 def parse_mean_range_element(element):
 357     """
 358     Grab mean/deviation out of element
 359     """
 360     return (tonumber(element.attrib['mean']),
 361             tonumber(element.attrib['deviation']))
 362
 363 def parse_summary_element(element):
 364     """
 365     Determine if we have a simple element or a mean/deviation element
 366     """
 367     if len(element.attrib) > 0:
 368         return parse_mean_range_element(element)
 369     else:
 370         return element.text
 371
 372 def parse_xml_mean_range(element):
 373     """
 374     Extract mean/stddev children from an element as a tuple
 375     """
 376     if element is None:
 377         return None
 378
 379     mean = element.find('mean')
 380     stddev = element.find('stdev')
 381     if mean is None or stddev is None:
 382         raise RuntimeError("Summary.xml file format changed, expected mean/stddev tags")
 383
 384     return (tonumber(mean.text), tonumber(stddev.text))
 385
 386 if __name__ == "__main__":
 387     # test code
 388     from optparse import OptionParser
 389     parser = OptionParser('%prog [Summary.xml/Summary.htm]+')
 390     opts, args = parser.parse_args()
 391     if len(args) == 0:
 392         parser.error('need at least one xml/html file')
 393     for fname in args:
 394         s = Summary(fname)
 395         s.dump()
 396