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authorHui Lan <lanhui@zjnu.edu.cn>2019-12-04 19:03:19 +0800
committerHui Lan <lanhui@zjnu.edu.cn>2019-12-04 19:03:19 +0800
commit97fdefab064f63642fa3ece05b807d29b459df31 (patch)
treea058530023224f3e35b1783996f3530c80c04bc5 /Code/parse_ena_xml_test.py
brain: add python and R code to local repository.
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+# Usage: python parse_ena_xml.py > rnaseq_info_database.txt
+#
+# Search in this script for 'd_run', 'd_sample', 'd_experiment' and
+# 'd_study', and set their input files. The input files are generated
+# by download_ena_metadata.py (except for d_sample). It also
+# generates a json file called info_database.json, for displaying
+# experimental information in the scatterplot. If the input files are
+# for RNA-seq data, rename info_database.json to
+# rnaseq_info_database.json and move it to Data/information. Also move
+# rnaseq_info_database.txt to Data/information. They are used by
+# html_network.py.
+#
+# Purpose: Get description for RNA-seq data, one for each SRA Run ID.
+# Make rnaseq_info_database.txt and rnaseq_info_database.json. Each
+# line in rnaseq_info_database.txt contains information for a run id.
+#
+# NOTE: you might encounter UnicideEncodeError when running the
+# program. To avoid that, first type this command:
+# export PYTHONIOENCODING=UTF-8.
+#
+# 22 Feb 2017, slcu, hui
+# 12 Apr 2017, slcu, hui
+# 20 Apr 2017, slcu, hui
+# 30 May 2017, slcu, hui
+# 01 Jun 2017, slcu, hui [added a column sample_id]
+# 19 Jun 2017, slcu, hui [added SraRunTable_Ath_Tax3702.txt in d_run2. Search d_run2 for how to get SraRunTable_Ath_Tax3702.txt.]
+
+import os, json, re, operator
+import xml.etree.ElementTree
+import sys
+
+MAX_DESCRIPTION_LENGTH = 600 # max number to characters to keep in json file
+
+def parse_SraRunTable(fname):
+ d = {}
+ f = open(fname)
+ lines = f.readlines()
+ f.close()
+ for line in lines:
+ line = line.strip()
+ if not line.startswith('#') and not line.startswith('Assay_Type_s') and line.lower().startswith('rna-seq'):
+ lst = line.split('\t')
+ acc = lst[17]
+ if not acc in d:
+ d[acc] = {}
+ d[acc]['experiment_id'] = lst[6] if lst[6] != '' else '.'
+ d[acc]['sample_id'] = (lst[4] + '...' + lst[18] + ' ' + lst[20]) if lst[4] != '' else '.'
+ d[acc]['study_id'] = lst[19] if lst[19] != '' else '.'
+ d[acc]['study_id_PRJ'] = lst[3] if lst[3] != '' else '.'
+ d[acc]['alias'] = lst[11] if lst[11] != '' else '.'
+ d[acc]['title'] = lst[20] if lst[20] != '' else '.'
+ return d
+
+def parse_run(fname):
+ d = {}
+
+ root = xml.etree.ElementTree.parse(fname).getroot()
+
+ for c in root.findall('RUN'):
+ acc = c.get('accession')
+ d[acc] = {}
+
+ alias = c.get('alias')
+ d[acc]['alias'] = alias
+
+ experiment = c.find('EXPERIMENT_REF').get('accession')
+ d[acc]['experiment_id'] = experiment
+
+ title = c.find('TITLE').text
+ d[acc]['title'] = title
+
+ d[acc]['study_id'] = '.'
+ for i in c.findall('./RUN_LINKS/RUN_LINK/XREF_LINK/ID'):
+ s = i.text
+ #print(s)
+ if 'RP' in s: # run project
+ d[acc]['study_id'] = s
+ break
+ d[acc]['sample_id'] = '.'
+ for i in c.findall('./RUN_LINKS/RUN_LINK/XREF_LINK/ID'):
+ s = i.text
+ if 'RS' in s: # run project
+ d[acc]['sample_id'] = s
+ break
+
+ return d
+
+
+def parse_study(fname):
+ d = {}
+ root = xml.etree.ElementTree.parse(fname).getroot()
+
+
+ for c in root.findall('PROJECT'):
+ d2 = {}
+ acc = c.find('./IDENTIFIERS/SECONDARY_ID')
+ if acc != None:
+ d2['secondary_id'] = acc.text
+ else:
+ d2['secondary_id'] = '.'
+ d2['primary_id'] = c.get('accession')
+
+ desc = c.find('DESCRIPTION')
+ d2['description'] = 'None'
+ if desc != None:
+ d2['description'] = desc.text
+
+ title = c.find('TITLE')
+ d2['title'] = 'None'
+ if title != None:
+ d2['title'] = title.text
+
+ run_id = ''
+ for i in c.findall('./PROJECT_LINKS/PROJECT_LINK/XREF_LINK/ID'):
+ s = i.text
+ if 'RR' in s:
+ run_id = s;
+ break
+ lst = run_id.split(',')
+ for x in lst:
+ lst2 = x.split('-')
+ if len(lst2) == 1 and lst2[0] != '':
+ k = lst2[0]
+ d[k] = d2 # k is run id, such as SRR, ERR or DRR
+ elif len(lst2) == 2:
+ ss = lst2[0]
+ ee = lst2[1]
+ first_three_letters = ss[0:3]
+ sz = len(ss) - 3
+ ss_t = int(ss[3:])
+ ee_t = int(ee[3:])
+ for j in range(ss_t, ee_t+1, 1):
+ k = first_three_letters + str(j).zfill(sz)
+ d[k] = d2
+ return d
+
+
+def parse_sample(fname):
+ d = {}
+ root = xml.etree.ElementTree.parse(fname).getroot()
+
+
+ for c in root.findall('SAMPLE'):
+ d2 = {}
+ acc = c.find('./IDENTIFIERS/EXTERNAL_ID')
+ if acc != None:
+ d2['external_id'] = acc.text
+ else:
+ d2['external_id'] = '.'
+ d2['primary_id'] = c.get('accession')
+
+ desc = c.find('DESCRIPTION')
+ d2['description'] = 'None'
+ if desc != None and desc.text != None:
+ d2['description'] = desc.text
+
+ title = c.find('TITLE')
+ d2['title'] = 'None'
+ if title != None and title.text != None:
+ d2['title'] = title.text
+
+ tissue_type = ''
+ for i in c.findall('./SAMPLE_ATTRIBUTES/SAMPLE_ATTRIBUTE/VALUE'):
+ if i != None and i.text != None:
+ tissue_type += i.text + ' '
+ d2['tissue'] = tissue_type.strip()
+
+ run_id = ''
+ for i in c.findall('./SAMPLE_LINKS/SAMPLE_LINK/XREF_LINK/ID'):
+ s = i.text
+ if 'RR' in s:
+ run_id = s;
+ break
+ lst = run_id.split(',')
+ for x in lst:
+ lst2 = x.split('-') # e.g., SRR520490-SRR520491
+ if len(lst2) == 1 and lst2[0] != '':
+ k = lst2[0]
+ d[k] = d2 # k is run id, such as SRR, ERR or DRR
+ elif len(lst2) == 2:
+ ss = lst2[0]
+ ee = lst2[1]
+ first_three_letters = ss[0:3]
+ sz = len(ss) - 3
+ ss_t = int(ss[3:])
+ ee_t = int(ee[3:])
+ for j in range(ss_t, ee_t+1, 1):
+ k = first_three_letters + str(j).zfill(sz)
+ d[k] = d2
+ return d
+
+
+def parse_experiment(fname):
+ d = {}
+
+ root = xml.etree.ElementTree.parse(fname).getroot()
+
+ for c in root.findall('EXPERIMENT'):
+ d2 = {}
+ d2['primary_id'] = c.get('accession')
+
+ title = c.find('TITLE')
+ d2['title'] = 'None'
+ if title != None and title.text != None:
+ d2['title'] = title.text
+
+ desc = c.find('./DESIGN/DESIGN_DESCRIPTION')
+ d2['description'] = 'None'
+ if desc != None and desc.text != None:
+ d2['description'] = desc.text
+
+ run_id = ''
+ for i in c.findall('./EXPERIMENT_LINKS/EXPERIMENT_LINK/XREF_LINK/ID'):
+ s = i.text
+ if 'RR' in s:
+ run_id = s;
+ break
+ lst = run_id.split(',')
+ for x in lst:
+ lst2 = x.split('-') # e.g., SRR520490-SRR520491
+ if len(lst2) == 1 and lst2[0] != '':
+ k = lst2[0]
+ d[k] = d2 # k is run id, such as SRR, ERR or DRR
+ elif len(lst2) == 2:
+ ss = lst2[0]
+ ee = lst2[1]
+ first_three_letters = ss[0:3]
+ sz = len(ss) - 3
+ ss_t = int(ss[3:])
+ ee_t = int(ee[3:])
+ for j in range(ss_t, ee_t+1, 1):
+ k = first_three_letters + str(j).zfill(sz)
+ d[k] = d2
+ return d
+
+
+def get_singular_form(w):
+ d = {'seedlings':'seedling', 'roots':'root', 'leaves':'leaf', 'flowers':'flower', 'floral':'flower', 'shoots':'shoot', 'apices':'apex', 'stems':'stem', 'seeds':'seed', 'petals':'petals', 'sepals':'sepal', 'embryos':'embryo', 'embryonic':'embryo', 'cotyledons':'cotyledon', 'hairs':'hair', 'meristems':'meristem', 'epidermal':'epidermis', 'apical':'apex', 'buds':'bud', 'vacuoles':'vacuole', 'vacuolar':'vacuole', 'tips':'tip', 'pollens':'pollen', 'hypocotyls':'hypocotyl', 'tubes':'tube', 'stomatal':'stomata', 'ovule':'ovules', 'pistils':'pistil', 'anthers':'anther', 'carpels':'carpel', 'pedicle':'pedicel', 'vascular':'vasculum'}
+ if w in d:
+ return d[w]
+ return w
+
+def get_tissue(s):
+ ''' Extract tissue name from s. s may contain several tissue names, return them ordered by frequency. '''
+
+
+ lst = ['seedling', 'seedlings', 'root', 'roots', 'leaves', 'leaf', 'flower', 'flowers', 'floral', 'shoot', 'shoots', 'apex', 'apices', 'stamen', 'stem', 'stems', 'seed', 'seeds', 'petal', 'petals', 'sepal', 'sepals', 'embryo', 'embryos', 'embryonic', 'cotyledon', 'cotyledons', 'xylem', 'hair', 'hairs', 'phloem', 'pericycle', 'primordia', 'columella', 'cortex', 'meristem', 'meristems', 'cambium', 'epidermis', 'epidermal', 'phloem', 'mesophyll', 'apical', 'lateral', 'intercalary', 'parenchyma', 'collenchyma', 'sclerenchyma', 'bud', 'buds', 'endosperm', 'colletotrichum', 'stele', 'vacuoles', 'vacuole', 'vacuolar', 'tip', 'tips', 'pollen', 'hypocotyl', 'hypocotyls', 'tube', 'tubes', 'basal', 'stomatal', 'stomata', 'surface', 'progeny', 'ovules', 'carpel', 'carpels', 'gynoecium', 'pistil', 'pistils', 'anthers', 'anther', 'endodermis', 'dicotyledonous', 'hyphae', 'adabaxial', 'axial', 'cauline', 'rosette', 'pedicle', 'pedicel', 'inflorescence', 'petiole', 'lamina', 'vascular', 'bundle', 'sheath'] # possible tissue names, lower case. refer to /home/hui/network/test/rnaseq.word.count.txt for distinct words in rna seq. rnaseq.word.count.txt is generated by /home/hui/network/test/count_word.py
+
+ # build a count dictionary, where key is a word
+ d = {}
+ s = s.lower()
+ wlst = re.sub("[^\w]", " ", s).split() # a list of words in s. http://stackoverflow.com/questions/6181763/converting-a-string-to-a-list-of-words
+ for w in wlst:
+ if w in lst:
+ w2 = get_singular_form(w)
+ if not w2 in d:
+ d[w2] = 1
+ else:
+ d[w2] += 1
+ if len(d) == 0:
+ return 'unknown'
+
+ tlst = sorted(d.items(), key=operator.itemgetter(1), reverse=True)
+ result = ''
+ for t in tlst:
+ result += '%s(%d);' % (t[0], t[1])
+ return result.rstrip(';')
+
+
+## main
+
+# ENA xml meta files do not differentiate between different types of Seq, but are organised by RUN, STUDY, EXPERIMENT. So each
+# of the following function is for each type of xml file.
+d_run = parse_run('ena_rnaseq_read_run.xml') # RUN
+
+cmd = 'export PYTHONIOENCODING=UTF-8' # since xml files contains non-ascii characters, use this command to avoid encoding error during redirection
+os.system(cmd)
+
+d_run_keys = d_run.keys()
+d_run_keys = list(set(d_run_keys))
+for k in sorted(d_run_keys):
+ lst = []
+ lst.append(k)
+ if k in d_run and 'illumina hiseq' in d_run[k]['title'].lower() and 'rna-seq' in d_run[k]['title'].lower():
+ lst.append( d_run[k]['experiment_id'])
+ lst.append( d_run[k]['study_id'] )
+ lst.append( d_run[k]['title'] )
+ lst.append( d_run[k]['alias'] )
+ print('\t'.join(lst))
+
+# make a json file as well. this file is used to display rna-seq information in scatterplots.
+json_dict = {}
+for k in sorted(d_run_keys):
+ if k in d_run and 'illumina hiseq' in d_run[k]['title'].lower() and 'rna-seq' in d_run[k]['title'].lower():
+ s = 'Title: ' + d_run[k]['title'] + '. Alias: ' + d_run[k]['alias'] + '. More info:'
+ s = s.strip()
+ d = {}
+ d['tissue'] = get_tissue(s)
+ d['detail'] = s[0:min(MAX_DESCRIPTION_LENGTH, len(s))] + ' ...'
+
+ json_dict[k] = d
+
+fname = 'rnaseq_info_database.json'
+with open(fname, 'w') as f:
+ json.dump(json_dict, f, indent=4)
+
+#sys.stderr.write('Check %s. Use this file to display RNA-seq information in the scatterplots. Copy it to Data/information and rename it to rnaseq_info_database.json.\n' % (fname))