path: root/Code/parse_ena_xml.py

# 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_sample     = parse_sample('../Data/information/ena_sample.xml')                         # SAMPLE.  We can download RUN, STUDY, EXPERIMENT using download_ena_metadata.py, but not for SAMPLE (weired).  So we need manually download ena_sample.xml. Enter http://www.ebi.ac.uk/ena/data/search?query=arabidopsis%20thaliana, click Sample (31,042) in the left panel of the displayed page, then click XML link in the right panel.  The XML link is very small, so take time to find it or search for XML.
d_run        = parse_run('../Data/information/ena_rnaseq_read_run.xml')                   # RUN
d_run2       = parse_SraRunTable('../Data/information/SraRunTable_Ath_Tax3702.txt')       # Go to https://www.ncbi.nlm.nih.gov/sra.  Type (arabidopsis thaliana) AND "Arabidopsis thaliana"[orgn:__txid3702].  Click "Send results to Run selector".  Click "RunInfo Table".  Save SraRunTable.txt
d_study      = parse_study('../Data/information/ena_rnaseq_read_study.xml')               # STUDY
d_experiment = parse_experiment('../Data/information/ena_rnaseq_read_experiment.xml')     # EXPERIMENT


cmd = 'export PYTHONIOENCODING=UTF-8'  # since xml files contains non-ascii characters, use this command to avoid encoding error during redirection
os.system(cmd)

print('%s' % ('\t'.join(['run_id', 'sample_id', 'experiment_id', 'study_id', 'study_id_PRJ', 'title', 'alias', 'description']))) # description comes from three sources, STUDY, SAMPLE and EXPERIMENT
d_run_keys = d_run.keys()
d_run_keys.extend(d_run2.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:
        if k in d_sample:
            if d_sample[k]['external_id'] != '.':
                lst.append(d_sample[k]['external_id'] + '...' + d_sample[k]['tissue'])            
            else:
                lst.append(d_sample[k]['primary_id'] + '...' + d_sample[k]['tissue'])
        else:
            lst.append('.')
        lst.append( d_run[k]['experiment_id'])
        lst.append( d_run[k]['study_id'] )
        if k in d_study:
            lst.append( d_study[k]['primary_id'] )
        else:
            lst.append( '.' )
        lst.append( d_run[k]['title'] )
        lst.append( d_run[k]['alias'] )

        s = '' # description string

        if k in d_study:
            s += ' <br><br>[Study title] '  + d_study[k]['title'] + ' <br><br>[Study description] ' + d_study[k]['description'] # <br> is used for breaking lines in html

        if k in d_sample:
            s += ' <br><br>[Sample title] ' + d_sample[k]['title'] + ' <br><br>[Sample description] ' + d_sample[k]['description']

        if k in d_experiment:
            s += ' <br><br>[Experiment title] ' + d_experiment[k]['title'] + ' <br><br>[Experiment description] ' + d_experiment[k]['description']

        if s == '':
            s = '.'

        lst.append(s)
    elif k in d_run2:
        lst.append(d_run2[k]['sample_id'])
        lst.append(d_run2[k]['experiment_id'])
        lst.append(d_run2[k]['study_id'])
        lst.append(d_run2[k]['study_id_PRJ'])
        lst.append(d_run2[k]['title'])
        lst.append(d_run2[k]['alias'])        
        lst.append('.')
        
    print('%s' % ('\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:
        s = 'Title: ' + d_run[k]['title'] + '. Alias: ' + d_run[k]['alias'] + '.  More info:'
        if k in d_study:
            s += ' ' + d_study[k]['title'] + ' ' + d_study[k]['description']
        if k in d_sample:
            s += ' ' + d_sample[k]['title'] + ' ' + d_sample[k]['description']
        if k in d_experiment:
            s += ' ' + d_experiment[k]['title'] + ' ' + d_experiment[k]['description']

        s = s.strip()
        d = {}
        d['tissue'] = get_tissue(s)
        d['detail'] = s[0:min(MAX_DESCRIPTION_LENGTH, len(s))] + ' ...'

    elif k in d_run2:
        s = d_run2[k]['title'] + ' ' + d_run2[k]['alias']
        s = s.strip()
        d = {}
        d['tissue'] = get_tissue(s)
        d['detail'] = s[0:min(MAX_DESCRIPTION_LENGTH, len(s))] + ' ...'

    json_dict[k] = d

fname = '../Data/information/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))