Options for dealing with tax information

Setting "--include-missing-functions" represents organisms that are not in KEGG Genomes
Setting "--map-all" ignores KEGG Genomes completely, and represents all functions identified, regardless of information that the function is not available for the organism
closes #11

keggcharter.py

@@ -18,7 +18,7 @@
 
 from keggpathway_map import KEGGPathwayMap, expand_by_list_column
 
-__version__ = "0.5.1"
+__version__ = "0.6.0"
 
 
 def get_arguments():
@@ -42,21 +42,29 @@ def get_arguments():
  parser.add_argument("-keggc", "--kegg-column", help="Column with KEGG IDs.")
  parser.add_argument("-koc", "--ko-column", help="Column with KOs.")
  parser.add_argument("-ecc", "--ec-column", help="Column with EC numbers.")
+ # TODO - test this argument without UniProt shenanigans
+ parser.add_argument(
+ "-tc", "--taxa-column", default='Taxonomic lineage (GENUS)',
+ help="Column with the taxa designations to represent with KEGGCharter."
+ " NOTE - for valid taxonomies, check: https://www.genome.jp/kegg/catalog/org_list.html")
  parser.add_argument(
  "-iq", "--input-quantification", action="store_true",
  help="If input table has no quantification, will create a mock quantification column")
  parser.add_argument(
  "-it", "--input-taxonomy", default=None,
  help="If no taxonomy column exists and there is only one taxon in question.")
- # TODO - test this argument without UniProt shenanigans
  parser.add_argument(
- "-tc", "--taxa-column", default='Taxonomic lineage (GENUS)',
- help="Column with the taxa designations to represent with KEGGCharter")
+ "--step", default=40, type=int, help="Number of IDs to submit per request through the KEGG API [40]")
+ parser.add_argument(
+ "--map-all", default=False, action="store_true",
+ help="Ignore KEGG taxonomic information. All functions for all KOs will be represented,"
+ " even if they aren't attributed by KEGG to the specific species.")
+ parser.add_argument(
+ "--include-missing-genomes", default=False, action="store_true",
+ help="Map the functions for KOs identified for organisms not present in KEGG Genomes.")
  parser.add_argument(
  "--resume", action="store_true", default=False,
  help="If data inputed has already been analyzed by KEGGCharter.")
- parser.add_argument(
- "--step", default=40, type=int, help="Number of IDs to submit per request through the KEGG API [40]")
  parser.add_argument('-v', '--version', action='version', version='KEGGCharter ' + __version__)
 
  required_named = parser.add_argument_group('required named arguments')
@@ -247,6 +255,10 @@ def kegg_metabolic_maps():
 
 
 def write_kgml(mmap, output, organism='ko'):
+ """
+ This function is confusing, in that it both writes the KGML, and parses it.
+ Still, it works, and for now that's enough.
+ """
  data = kegg_get(f"{organism}{mmap}", "kgml").read()
  with open(output, 'w') as f:
  if len(data) > 1:
@@ -320,30 +332,39 @@ def parse_organism(file):
  return pd.read_csv(file, sep='\t', usecols=[1, 2], header=None, index_col=1, names=['prefix', 'name'])
 
 
-def download_resources(data, resources_directory, taxa_column, metabolic_maps):
+def download_resources(
+ data, resources_directory, taxa_column, metabolic_maps, map_all=False, map_non_kegg_genomes=True):
  """
  Download all resources for a given dataframe
  :param data: pandas.DataFrame - dataframe with taxa names in taxa_column
  :param resources_directory: str - directory where to save the resources
  :param taxa_column: str - column name in dataframe with taxa names
  :param metabolic_maps: list - metabolic maps to download
+ :param map_all: bool - if True, attribute all maps and all functions to all taxa, only limit by the identifications
+ :param map_non_kegg_genomes: bool - if True, map non-KEGG genomes to KEGG orthologs
  :return: taxon_to_mmap_to_orthologs - dic with taxon name as key and dic with metabolic maps as values
  """
  download_organism(resources_directory)
  taxa = ['ko'] + list(set(data[data[taxa_column].notnull()][taxa_column]))
  taxa_df = parse_organism(f'{resources_directory}/organism')
- i = 1
  taxon_to_mmap_to_orthologs = {} # {'Keratinibaculum paraultunense' : {'00190': ['1', '2']}}
- for taxon in tqdm(taxa, desc=f'Getting information for {len(taxa) - 1} taxa'):
- kegg_prefix = taxon2prefix(taxon, taxa_df)
- if kegg_prefix is not None:
- taxon_mmaps = get_taxon_maps(kegg_prefix)
- taxon_mmaps = [mmap for mmap in taxon_mmaps if mmap in metabolic_maps] # select only inputted maps
- taxon_to_mmap_to_orthologs[taxon] = write_kgmls(
- taxon_mmaps, f'{resources_directory}/kc_kgmls', org=kegg_prefix)
- else:
- taxon_to_mmap_to_orthologs[taxon] = {}
- i += 1
+ if map_all: # attribute all maps and all functions to all taxa, only limit by the data
+ taxon_to_mmap_to_orthologs = {taxon: write_kgmls(
+ metabolic_maps, f'{resources_directory}/kc_kgmls', org='ko') for taxon in taxa}
+ else:
+ for taxon in tqdm(taxa, desc=f'Getting information for {len(taxa) - 1} taxa'):
+ kegg_prefix = taxon2prefix(taxon, taxa_df)
+ if kegg_prefix is not None:
+ taxon_mmaps = get_taxon_maps(kegg_prefix)
+ taxon_mmaps = [mmap for mmap in taxon_mmaps if mmap in metabolic_maps] # select only inputted maps
+ taxon_to_mmap_to_orthologs[taxon] = write_kgmls(
+ taxon_mmaps, f'{resources_directory}/kc_kgmls', org=kegg_prefix)
+ else:
+ if map_non_kegg_genomes:
+ taxon_to_mmap_to_orthologs[taxon] = write_kgmls(
+ metabolic_maps, f'{resources_directory}/kc_kgmls', org='ko')
+ else:
+ taxon_to_mmap_to_orthologs[taxon] = {}
  with open(f'{resources_directory}/taxon_to_mmap_to_orthologs.json', 'w') as f:
  json.dump(taxon_to_mmap_to_orthologs, f)
  return taxon_to_mmap_to_orthologs
@@ -459,7 +480,8 @@ def main():
  data.to_csv(f'{args.output}/data_for_charting.tsv', sep='\t', index=False)
  if not args.input_taxonomy:
  taxon_to_mmap_to_orthologs = download_resources(
- data, args.resources_directory, args.taxa_column, args.metabolic_maps)
+ data, args.resources_directory, args.taxa_column, args.metabolic_maps, map_all=args.map_all,
+ map_non_kegg_genomes=args.include_missing_genomes)
  h = open(f"{args.output}/taxon_to_mmap_to_orthologs.json", "w")
  json.dump(taxon_to_mmap_to_orthologs, h)
  else:

keggpathway_map.py

@@ -267,7 +267,7 @@ def pathway_box_list(self, taxa_in_box, dic_colors, maxshared=10):
  if nrboxes > maxshared:
  nrboxes = maxshared
 
- paired = True if nrboxes % 2 == 0 else False
+ paired = nrboxes % 2 == 0
  for i in range(nrboxes):
  newrecord = create_box_heatmap(
  self.orthologs[boxidx], nrboxes, i * 2 - (nrboxes - 1) if paired else i - int(nrboxes / 2),
@@ -291,7 +291,6 @@ def pathway_boxes_differential(self, dataframe, log=True, colormap="coolwarm"):
  :param log: bol providing the option for a log transformation of data
  :param colormap: str representing a costum matplotlib colormap to be used
  """
-
  if log:
  norm = cm.colors.LogNorm(vmin=dataframe.min().min(), vmax=dataframe.max().max())
  else:
@@ -308,7 +307,7 @@ def pathway_boxes_differential(self, dataframe, log=True, colormap="coolwarm"):
  for box in dataframe.index.tolist():
  boxidx = self.ortho_ids_to_pos[box] # get box index
  colors = dataframe.loc[box].tolist()
- paired = True if nrboxes % 2 == 0 else False
+ paired = nrboxes % 2 == 0
  for i in range(nrboxes):
  newrecord = create_box_heatmap(
  self.orthologs[boxidx], nrboxes, i * 2 - (nrboxes - 1) if paired else i - int(nrboxes / 2),