exporter-pediatric.py

#!/usr/bin/python3
# vim:ts=4:sw=4:tw=0:et

import pprint
import re
import argparse
import logging as log
from builtins import str, isinstance, len, set, int
from typing import List

import pandas as pd

from directory import Directory
from orphacodes import OrphaCodes
from icd10codeshelper import ICD10CodesHelper
import pddfutils

cachesList = ['directory', 'emails', 'geocoding', 'URLs']

pp = pprint.PrettyPrinter(indent=4)


class ExtendAction(argparse.Action):

    def __call__(self, parser, namespace, values, option_string=None):
        from builtins import getattr, setattr
        items = getattr(namespace, self.dest) or []
        items.extend(values)
        setattr(namespace, self.dest, items)


parser = argparse.ArgumentParser()
parser.register('action', 'extend', ExtendAction)
parser.add_argument('-v', '--verbose', dest='verbose', action='store_true',
                    help='verbose information on progress of the data checks')
parser.add_argument('-d', '--debug', dest='debug', action='store_true',
                    help='debug information on progress of the data checks')
parser.add_argument('-X', '--output-XLSX', dest='outputXLSX', nargs=1,
                    help='output of results into XLSX with filename provided as parameter')
parser.add_argument('-O', '--orphacodes-mapfile', dest='orphacodesfile', nargs=1,
                    help='file name of Orpha code mappings from http://www.orphadata.org/cgi-bin/ORPHAnomenclature.html')
parser.add_argument('-N', '--output-no-stdout', dest='nostdout', action='store_true',
                    help='no output of results into stdout (default: enabled)')
parser.add_argument('--purge-all-caches', dest='purgeCaches', action='store_const', const=cachesList,
                    help='disable all long remote checks (email address testing, geocoding, URLs')
parser.add_argument('--purge-cache', dest='purgeCaches', nargs='+', action='extend', choices=cachesList,
                    help='disable particular long remote checks')
parser.set_defaults(disableChecksRemote=[], disablePlugins=[], purgeCaches=[])
args = parser.parse_args()

if args.debug:
    log.basicConfig(format="%(levelname)s: %(message)s", level=log.DEBUG)
elif args.verbose:
    log.basicConfig(format="%(levelname)s: %(message)s", level=log.INFO)
else:
    log.basicConfig(format="%(levelname)s: %(message)s")

# Main code

dir = Directory(purgeCaches=args.purgeCaches, debug=args.debug, pp=pp)

log.info('Total biobanks: ' + str(dir.getBiobanksCount()))
log.info('Total collections: ' + str(dir.getCollectionsCount()))

orphacodes = OrphaCodes(args.orphacodesfile)

pediatricExistingDiagnosed = []
pediatricOnlyExistingDiagnosed = []
pediatricBiobanksExistingDiagnosed = set()
pediatricOnlyBiobanksExistingDiagnosed = set()
pediatricBiobanks = set()
pediatricOnlyBiobanks = set()
pediatricCollectionSamplesExplicit = 0
pediatricCollectionDonorsExplicit = 0
pediatricCollectionSamplesIncOoM = 0
pediatricOnlyCollectionSamplesExplicit = 0
pediatricOnlyCollectionDonorsExplicit = 0
pediatricOnlyCollectionSamplesIncOoM = 0

for collection in dir.getCollections():
    log.debug("Analyzing collection " + collection['id'])
    biobankId = dir.getCollectionBiobankId(collection['id'])
    biobank = dir.getBiobankById(biobankId)
    biobank_capabilities = []
    if 'capabilities' in biobank:
        for c in biobank['capabilities']:
            biobank_capabilities.append(c['id'])
    biobank_covid = []
    if 'covid19biobank' in biobank:
        for c in biobank['covid19biobank']:
            biobank_covid.append(c['id'])
    biobank_networks = []
    if 'network' in biobank:
        for n in biobank['network']:
            biobank_networks.append(n['id'])

    OoM = collection['order_of_magnitude']['id']

    materials = []
    if 'materials' in collection:
        for m in collection['materials']:
            materials.append(m['id'])

    data_categories = []
    if 'data_categories' in collection:
        for c in collection['data_categories']:
            data_categories.append(c['id'])

    types = []
    if 'type' in collection:
        for t in collection['type']:
            types.append(t['id'])
    log.debug("Types: " + str(types))

    diags = []
    diag_ranges = []
    cancer_diag = False
    cancer_control = False
    cancer_prospective = False
    non_cancer = False

    for d in collection['diagnosis_available']:
        if re.search('-', d['id']):
            diag_ranges.append(d['id'])
        else:
            diags.append(d['id'])

    if diag_ranges:
        log.warning("There are diagnosis ranges provided for collection " + collection['id'] + ": " + str(diag_ranges))

    log.debug(str(collection['diagnosis_available']))

    for d in diags + diag_ranges:
        if re.search(r'^urn:miriam:icd:', d):
            d = re.sub(r'^urn:miriam:icd:', '', d)
            isCancer = ICD10CodesHelper.isCancerCode(d)
            if isCancer is not None:
                if isCancer:
                    log.debug(
                        "Collection %s identified as cancer collection due to ICD-10 code %s" % (collection['id'], d))
                    cancer_diag = True
                else:
                    log.debug("Collection %s identified as non-cancer collection due to ICD-10 code %s" % (
                    collection['id'], d))
                    non_cancer = True
            else:
                isCancerChapter = ICD10CodesHelper.isCancerChapter(d)
                if isCancerChapter is not None:
                    if isCancerChapter:
                        log.debug("Collection %s identified as cancer collection due to ICD-10 chapter %s" % (
                        collection['id'], d))
                        cancer_diag = True
                    else:
                        log.debug("Collection %s identified as non-cancer collection due to ICD-10 chapter %s" % (
                        collection['id'], d))
                        non_cancer = True
                else:
                    log.warning("Cannot match ICD-10 diagnosis %s" % (d))

        if re.search(r'^ORPHA:', d):
            d = re.sub(r'^ORPHA:', '', d)
            if orphacodes.isValidOrphaCode(d):
                isCancer = orphacodes.isCancerOrphaCode(d)
                if isCancer:
                    log.debug("Collection %s identified as cancer collection due to ORPHA code %s" % (collection['id'], d))
                    cancer_diag = True
                else:
                    log.debug("Collection %s identified as non-cancer collection due to ORPHA code %s" % (collection['id'], d))
                    non_cancer = True
            else:
                log.warning("Collection %s has invalid ORPHA code %s" % (d))

    pediatric = False
    pediatricOnly = False

    age_unit = None
    if 'age_unit' in collection:
        age_units = collection['age_unit']
        if len(age_units) > 1:
            log.warning("Ambiguous age units provided for %s: %s"%(collection['id'],age_units))
        if len(age_units) < 1:
            log.warning("Age units missing for %s"%(collection['id']))
        else:
            age_unit = age_units[0]['id']

    age_max = 18
    if age_unit == "MONTH":
        age_max = age_max*12
    elif age_unit == "WEEK":
        age_max = age_max*52.1775
    elif age_unit == "DAY":
        age_max = age_max*365.25

    if 'age_high' in collection and collection['age_high'] == 0:
        if 'age_low' in collection and collection['age_low'] < 0:
            pediatric = True
            pediatricOnly = True
            log.debug("Prenatal collection detected: %s (%s), age range: %d-%d, diags: %s"%(collection['id'], collection['name'], collection.get('age_low'), collection.get('age_high'), diags + diag_ranges))
        else:
            log.warning("Age range mismatch detected for collection: %s (%s), age range: %d-%d"%(collection['id'], collection['name'], collection.get('age_low'), collection.get('age_high')))
    elif 'age_high' in collection and collection['age_high'] < 0:
        log.warning("Age range mismatch detected for collection: %s (%s), age range: %d-%d"%(collection['id'], collection['name'], collection.get('age_low'), collection.get('age_high')))
    else:
        if 'age_low' in collection and 'age_high' in collection and collection['age_low'] > collection['age_high']:
            log.warning("Age range mismatch detected for collection: %s (%s), age range: %d-%d"%(collection['id'], collection['name'], collection.get('age_low'), collection.get('age_high')))
        else:
            if (('age_low' in collection and collection['age_low'] < age_max ) or ('age_high' in collection and collection['age_high'] < age_max)):
                pediatric = True
            if 'age_high' in collection and collection['age_high'] < age_max:
                pediatricOnly = True
                log.debug("Pediatric-only collection detected: %s, age range: %d-%d, diags: %s"%(collection['id'], collection.get('age_low'), collection.get('age_high'), diags + diag_ranges))

    if pediatric:
        log.info(f"Pediatric collection detected: {collection['id']}, age range: {collection.get('age_low')}-{collection.get('age_high')}, diags: {diags + diag_ranges}")
        pediatricExistingDiagnosed.append(collection)
        pediatricBiobanksExistingDiagnosed.add(biobankId)
        pediatricBiobanks.add(biobankId)
        if 'size' in collection and isinstance(collection['size'], int):
            pediatricCollectionSamplesExplicit += collection['size']
            pediatricCollectionSamplesIncOoM += collection['size']
    if pediatricOnly:
        log.info(f"Pediatric-only collection detected: {collection['id']}, age range: {collection.get('age_low')}-{collection.get('age_high')}, diags: {diags + diag_ranges}")
        pediatricOnlyExistingDiagnosed.append(collection)
        pediatricOnlyBiobanksExistingDiagnosed.add(biobankId)
        pediatricOnlyBiobanks.add(biobankId)
        if 'size' in collection and isinstance(collection['size'], int):
            pediatricOnlyCollectionSamplesExplicit += collection['size']
            pediatricOnlyCollectionSamplesIncOoM += collection['size']
    if 'number_of_donors' in collection and isinstance(collection['number_of_donors'], int):
        if pediatric:
            pediatricCollectionDonorsExplicit += collection['number_of_donors']
        if pediatricOnly:
            pediatricOnlyCollectionDonorsExplicit += collection['number_of_donors']

pd_pediatricExistingDiagnosed = pd.DataFrame(pediatricExistingDiagnosed)
pd_pediatricOnlyExistingDiagnosed = pd.DataFrame(pediatricOnlyExistingDiagnosed)


def printCollectionStdout(collectionList: List, headerStr: str):
    print(headerStr + " - " + str(len(collectionList)) + " collections")
    for collection in collectionList:
        biobankId = dir.getCollectionBiobankId(collection['id'])
        biobank = dir.getBiobankById(biobankId)
        log.info("   Collection: " + collection['id'] + " - " + collection['name'] + ". Parent biobank: " + biobankId + " - " + biobank['name'])


if not args.nostdout:
    print("Biobanks/collections totals:")
    print("- total of pediatric biobanks: %d" % (len(pediatricBiobanks)))
    print("- total of pediatric collections with existing samples: %d in %d biobanks" % (
    len(pediatricExistingDiagnosed), len(pediatricBiobanksExistingDiagnosed)))
    print("- total of pediatric collections with existing samples: %d in %d biobanks" % (
    len(pediatricOnlyExistingDiagnosed), len(pediatricOnlyBiobanksExistingDiagnosed)))
    print("- total of pediatric-only biobanks: %d" % (len(pediatricOnlyBiobanks)))
    print("- total of pediatric-only collections with existing samples: %d in %d biobanks" % (
    len(pediatricOnlyExistingDiagnosed), len(pediatricOnlyBiobanksExistingDiagnosed)))
    print("\n")
    print("Estimated sample totals:")
    print("- total of samples/donors advertised explicitly in pediatric collections: %d / %d" % (
        pediatricCollectionSamplesExplicit, pediatricCollectionDonorsExplicit))
    print("- total of samples advertised in pediatric collections including OoM estimates: %d" % (
        pediatricCollectionSamplesIncOoM))
    print("- total of samples/donors advertised explicitly in pediatric-only collections: %d / %d" % (
        pediatricOnlyCollectionSamplesExplicit, pediatricOnlyCollectionDonorsExplicit))
    print("- total of samples advertised in pediatric-only collections including OoM estimates: %d" % (
        pediatricOnlyCollectionSamplesIncOoM))

for df in (pd_pediatricExistingDiagnosed, pd_pediatricOnlyExistingDiagnosed):
    pddfutils.tidyCollectionDf(df)

if args.outputXLSX is not None:
    log.info("Outputting warnings in Excel file " + args.outputXLSX[0])
    writer = pd.ExcelWriter(args.outputXLSX[0], engine='xlsxwriter')
    pd_pediatricExistingDiagnosed.to_excel(writer, sheet_name='Pediatric')
    pd_pediatricOnlyExistingDiagnosed.to_excel(writer, sheet_name='Pediatric-only')
    writer.save()