def _read_genome_location_file(self, file_path):
"""
Read file with the file paths of gnomes
@param file_path: File genome id associated with the file path of a genome
@type file_path: str | unicode
@return: Dictionary of genome id to file path
@rtype: dict[str|unicode, str|unicode]
"""
self._logger.info('Reading genome location file')
assert self.validate_file(file_path)
dict_id_file_path = {}
metadata_table = MetadataTable(logfile=self._logfile,
verbose=self._verbose,
separator=self._separator)
iterator_distributions = metadata_table.parse_file(file_path,
as_list=True)
for genome_id, file_path_genome in iterator_distributions:
assert genome_id != '', "Invalid genomid: '{}'".format(genome_id)
assert file_path_genome != '', "Invalid file path: '{}'".format(
genome_id)
assert self.validate_file(
file_path_genome), "Invalid file path: '{}'".format(genome_id)
# check uniqueness
assert genome_id not in dict_id_file_path, "Genome '{}' not unique in the distribution file!".format(
genome_id)
dict_id_file_path[genome_id] = file_path_genome
return dict_id_file_path
def write_taxonomic_profile_from_abundance_files(self,
metadata_table,
list_of_file_paths,
directory_output,
sample_id=""):
"""
Write a taxonomic profile file for each relative abundance file
@param metadata_table: Contains metadata of all communities
@type metadata_table: MetadataTable
@param list_of_file_paths: List of abundance file paths
@type list_of_file_paths: list[str | unicode]
@param directory_output: Profiles are written in this directory
@type directory_output: str | unicode
@param sample_id: Identifier of a sample
@type sample_id: str | unicode
"""
metadata_table_tmp = MetadataTable(logfile=self._logfile,
verbose=self._verbose)
for index_abundance, file_path in enumerate(list_of_file_paths):
community_abundance = metadata_table_tmp.parse_file(
file_path, column_names=False)
file_path_output = os.path.join(
directory_output,
self._filename_taxonomic_profile.format(
sample_index=index_abundance))
with open(file_path_output, 'w') as stream_output:
self.write_taxonomic_profile(community_abundance,
stream_output, metadata_table,
sample_id)
def _read_distribution_file(self, file_path):
"""
Read file with the distribution of a sample
@param file_path: File genome id associated with the abundance of a genome
@type file_path: str | unicode
@return: Dictionary of genome id to file path
@rtype: dict[str|unicode, float]
"""
self._logger.info('Reading distribution file')
assert self.validate_file(file_path)
dict_id_abundance = {}
# dict_id_file_path = {}
metadata_table = MetadataTable(logfile=self._logfile, verbose=self._verbose, separator=self._separator)
iterator_distributions = metadata_table.parse_file(file_path, as_list=True)
# for genome_id, abundance, genome_length, file_path_genome in iterator_distributions:
abundance_sum = 0.
for genome_id, abundance in iterator_distributions:
assert genome_id != '', "Invalid genom id: '{}'".format(genome_id)
assert abundance != '', "Invalid abundance: '{}'".format(genome_id)
abundance = float(abundance)
assert self.validate_number(abundance, zero=True), "Invalid abundance: '{}'".format(genome_id)
assert genome_id not in dict_id_abundance, "Genome '{}' not unique in the distribution file!".format(genome_id)
dict_id_abundance[genome_id] = abundance
abundance_sum += abundance
dict_id_abundance = {x : dict_id_abundance[x]/abundance_sum for x in dict_id_abundance} # normalise to 1
return dict_id_abundance
def merge_communities(self, list_of_communities,
list_of_comunity_distribution_file_paths,
index_sample, file_path_output):
"""
Combine distributions of communities and adjust them according to their ratio.
@param list_of_communities: List of community inputs
@type list_of_communities: list[Community]
@param list_of_comunity_distribution_file_paths: List of distributions
@type list_of_comunity_distribution_file_paths: list[str | unicode]
@param index_sample: Index of sample
@type index_sample: int | long
@param file_path_output: Sample distribution file path
@type file_path_output: str | unicode
@return: Nothing
@rtype: None
"""
assert isinstance(list_of_communities, list)
for community in list_of_communities:
assert isinstance(community, Community)
# assert isinstance(metadata_table, MetadataTable)
# read communities and adapt to ratio
list_of_community_total_abundance = [0] * len(list_of_communities)
sample_total_abundance = 0
genomes = set()
metadata_table_community = MetadataTable(logfile=self._logfile,
verbose=self._verbose)
for index_community, file_path in enumerate(
list_of_comunity_distribution_file_paths):
community_distribution = metadata_table_community.parse_file(
file_path, column_names=False)
for row in community_distribution:
genome_id = row[0]
if genome_id in genomes:
raise ValueError(
"Genome id '{}' not unique".format(genome_id))
genomes.add(genome_id)
abundance = row[index_sample + 1]
list_of_community_total_abundance[index_community] += float(
abundance) # * float(sequence_info[4])
community_distribution.close()
for index_community, _ in enumerate(
list_of_comunity_distribution_file_paths):
sample_total_abundance += list_of_community_total_abundance[
index_community]
# out.append(read_communities[0][0])
list_of_community_factor = [0.0] * len(list_of_communities)
for index_community, _ in enumerate(
list_of_comunity_distribution_file_paths):
ratio = float(list_of_communities[index_community].ratio)
community_total_abundance = float(
list_of_community_total_abundance[index_community])
current_proportion_in_sample = community_total_abundance / float(
sample_total_abundance)
list_of_community_factor[
index_community] = ratio / current_proportion_in_sample
# self.update_community(communities[index_community], factor)
# join communities
communities = []
for index_community, file_path in enumerate(
list_of_comunity_distribution_file_paths):
communities.append(
metadata_table_community.parse_file(file_path,
column_names=False))
# print_ratios(communities)
with open(file_path_output, 'w') as stream_output:
self._write_joined_community(communities, list_of_community_factor,
index_sample, stream_output)