def map(article, file, text, result):
" go over words of text and check if they are in dict "
text = file.content
annots = list(fastFind.fastFindFlankWords(text, lex, wordDist=1))
newAnnots = []
for annot in annots:
start, end, id, leftWords, rightWords = annot
# get and clean word
word = text[start:end]
if not wordRe.match(word): # remove if garbage between words like ( or # etc
continue
word = " ".join(word.split()) # remove multi whitespace
# remove word if it contains more than one dash
letters = list(word)
if letters.count("-")>1:
continue
word = word.replace(" -", "-")
word = word.replace("- ", "-")
if word in blackList:
continue
result.setdefault( word, [0,0] ) # need to return it as a double-list
result[ word ][0] += 1
# check and inc count if flanking word is gene or protein
allFlanks = list(leftWords)
allFlanks.extend(rightWords)
allFlanks = [w.lower() for w in allFlanks]
if "protein" in allFlanks or "gene" in allFlanks or "locus" in allFlanks:
result[ word ][1] += 1
def map(article, file, text, result):
" go over words of text and check if they are in dict "
text = file.content
annots = list(fastFind.fastFindFlankWords(text, lex, wordDist=1))
newAnnots = []
for annot in annots:
start, end, id, leftWords, rightWords = annot
# get and clean word
word = text[start:end]
if not wordRe.match(
word): # remove if garbage between words like ( or # etc
continue
word = " ".join(word.split()) # remove multi whitespace
# remove word if it contains more than one dash
letters = list(word)
if letters.count("-") > 1:
continue
word = word.replace(" -", "-")
word = word.replace("- ", "-")
if word in blackList:
continue
result.setdefault(word, [0, 0]) # need to return it as a double-list
result[word][0] += 1
# check and inc count if flanking word is gene or protein
allFlanks = list(leftWords)
allFlanks.extend(rightWords)
allFlanks = [w.lower() for w in allFlanks]
if "protein" in allFlanks or "gene" in allFlanks or "locus" in allFlanks:
result[word][1] += 1
def map(article, file, text, result):
" go over words of text and check if they are in dict "
text = file.content
annots = list(fastFind.fastFindFlankWords(text, lex, wordDist=2))
newAnnots = []
for annot in annots:
start, end, id, leftWords, rightWords = annot
# get and clean word
word = text[start:end]
if not wordRe.match(
word): # remove if garbage between words like ( or # etc
continue
word = " ".join(word.split()) # remove multi whitespace
# remove word if it contains more than one dash
letters = list(word)
if letters.count("-") > 1:
continue
word = word.replace(" -", "-")
word = word.replace("- ", "-")
if word in blackList:
continue
result.setdefault(word, {
"l": {},
"r": {}
}) # need to return it as a double-list
addToResults(word, leftWords, "l", result)
addToResults(word, rightWords, "r", result)
def findGeneNames(text):
"""
look for gene names and symbols. Some symbols need flanking trigger words. If these
are not present, they are returned as "symbolMaybe"
Will always return the gene name matches before the symbol matches.
>>> initData(addOptional=True)
>>> list(findGeneNames("thyroid hormone receptor, beta"))
[(0, 30, 'geneName', '7068')]
>>> list(findGeneNames("FATE1"))
[(0, 5, 'symbolMaybe', '89885')]
>>> list(findGeneNames("FATE1 is overexpressed"))
[(0, 5, 'symbol', '89885')]
>>> list(findGeneNames("fate1 is overexpressed"))
[]
>>> list(findGeneNames("PITX2 overexpression"))
[(0, 5, 'symbol', '5308')]
# ignore genes that are immediately flanked by "pathway"
>>> list(findGeneNames("PITX2 pathway"))
[]
# XX need to correct this
>>> list(findGeneNames(" BLAST "))
[(1, 6, 'symbolMaybe', '962')]
"""
assert (geneSymLex != None)
textLower = text.lower()
for start, end, geneId in fastFind.fastFind(textLower,
geneNameLex,
toLower=False):
yield (start, end, 'geneName', geneId)
flankFindIter = fastFind.fastFindFlankWords(text,
geneSymLex,
wordDist=2,
wordRe=fastFind.SYMRE,
toLower=False)
for start, end, geneId, leftWords, rightWords in flankFindIter:
# if the symbol is marked as potentially ambiguous, check the flanking words
if geneId.startswith("?"):
leftWords = [w.lower() for w in leftWords]
rightWords = [w.lower() for w in rightWords]
geneId = geneId.strip("?")
if len(symLeftReqWords.intersection(leftWords))!=0 or \
len(symRightReqWords.intersection(rightWords))!=0:
yield (start, end, 'symbol', geneId)
else:
yield (start, end, 'symbolMaybe', geneId)
# otherwise pass them though
else:
# ignore genes that are immediately flanked by "pathway"
flankWords = getFlankWords(start, end, textLower)
if "pathway" in flankWords:
logging.debug("ignored %s, flank words are %s" %
(text[start:end], flankWords))
continue
yield (start, end, 'symbol', geneId)
def findGeneNames(text):
"""
look for gene names and symbols. Some symbols need flanking trigger words. If these
are not present, they are returned as "symbolMaybe"
Will always return the gene name matches before the symbol matches.
>>> initData(addOptional=True)
>>> list(findGeneNames("thyroid hormone receptor, beta"))
[(0, 30, 'geneName', '7068')]
>>> list(findGeneNames("FATE1"))
[(0, 5, 'symbolMaybe', '89885')]
>>> list(findGeneNames("FATE1 is overexpressed"))
[(0, 5, 'symbol', '89885')]
>>> list(findGeneNames("fate1 is overexpressed"))
[]
>>> list(findGeneNames("PITX2 overexpression"))
[(0, 5, 'symbol', '5308')]
# ignore genes that are immediately flanked by "pathway"
>>> list(findGeneNames("PITX2 pathway"))
[]
# XX need to correct this
>>> list(findGeneNames(" BLAST "))
[(1, 6, 'symbolMaybe', '962')]
"""
assert(geneSymLex!=None)
textLower = text.lower()
for start, end, geneId in fastFind.fastFind(textLower, geneNameLex):
yield (start, end, 'geneName', geneId)
flankFindIter = fastFind.fastFindFlankWords(text, geneSymLex, wordDist=2, wordRe=fastFind.SYMRE)
for start, end, geneId, leftWords, rightWords in flankFindIter:
# if the symbol is marked as potentially ambiguous, check the flanking words
if geneId.startswith("?"):
leftWords = [w.lower() for w in leftWords]
rightWords = [w.lower() for w in rightWords]
geneId = geneId.strip("?")
if len(symLeftReqWords.intersection(leftWords))!=0 or \
len(symRightReqWords.intersection(rightWords))!=0:
yield (start, end, 'symbol', geneId)
else:
yield (start, end, 'symbolMaybe', geneId)
# otherwise pass them though
else:
# ignore genes that are immediately flanked by "pathway"
flankWords = getFlankWords(start, end, textLower)
if "pathway" in flankWords:
logging.debug("ignored %s, flank words are %s" % (text[start:end], flankWords))
continue
yield (start, end, 'symbol', geneId)
def map(article, file, text, result):
" go over words of text and check if they are in dict "
text = file.content
annots = list(fastFind.fastFindFlankWords(text, lex, wordDist=2))
newAnnots = []
for annot in annots:
start, end, id, leftWords, rightWords = annot
# get and clean word
word = text[start:end]
if not wordRe.match(word): # remove if garbage between words like ( or # etc
continue
word = " ".join(word.split()) # remove multi whitespace
# remove word if it contains more than one dash
letters = list(word)
if letters.count("-")>1:
continue
word = word.replace(" -", "-")
word = word.replace("- ", "-")
if word in blackList:
continue
result.setdefault( word, {"l" : {}, "r" : {} } ) # need to return it as a double-list
addToResults(word, leftWords, "l", result)
addToResults(word, rightWords, "r", result)
