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Goci 2865 ds fix window generation #1

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Goci 2865 ds fix window generation #1

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5d60150
Now the windowing is fixed.
Jan 20, 2020
dc2973c
Cleaning code
Jan 20, 2020
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21 changes: 13 additions & 8 deletions peak_finder.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,15 +20,17 @@ def get_log(pv):
return(math.log10(float(pv)))

# Function to find and annotate top association:
def find_top_association(chrom):
def find_top_association(chrom):
global input_df
global window
global threshold

# The dataframe is filtered by chromosome:
test_df = input_df.loc[input_df.chromosome == chrom]
# test_df.loc[:,'pvalue'] = test_df['pvalue'].astype(float) # changing type of p-value column <- too dangerous. Underflow hazard.

# Calculate the -log(pv) and update column type of the position:
test_df['mLogPv'] = test_df.pvalue.apply(get_log)
test_df.loc[:,'bp_location'] = test_df['bp_location'].astype(float) # changing type of position column
test_df.loc[:,'bp_location'] = test_df['bp_location'].astype(float)

# sorting rows by p-value:
for index in test_df.sort_values(['mLogPv']).index:
Expand All @@ -43,17 +45,20 @@ def find_top_association(chrom):
test_df.loc[index, 'isTopAssociation'] = 'false'
continue

# We have found a top snp!
# We have found a top snp!
else:
pos = test_df.loc[index]['bp_location']
pval = test_df.loc[index]['mLogPv']

# Setting false flag for ALL variants within the window.
test_df.loc[test_df[abs( test_df.bp_location - pos ) <= window].index,'isTopAssociation'] = 'false'

# If there are multiple variants with the same p-value, request review, othervise it's a true peak.
if len(test_df.loc[test_df['mLogPv'] == test_df.loc[index]['mLogPv']].chromosome) > 1:
test_df.loc[ test_df['mLogPv'] == test_df.loc[index]['mLogPv'], 'isTopAssociation'] = 'REQUIRES REVIEW'
# If there are multiple variants with the same p-value within the window they require review:
if len(test_df.loc[(test_df.mLogPv == pval) & (abs( test_df.bp_location - pos ) <= window)]) > 1:
test_df.loc[ (test_df.mLogPv == pval) & (abs( test_df.bp_location - pos ) <= window), 'isTopAssociation'] = 'REQUIRES REVIEW'
# Otherwise it's a true peak:
else:
test_df.loc[ test_df['mLogPv'] == test_df.loc[index]['mLogPv'], 'isTopAssociation'] = 'true'
test_df.loc[ index, 'isTopAssociation'] = 'true'

# Modifying the original dataframe:
input_df.loc[ test_df.index, 'isTopAssociation'] = test_df.isTopAssociation
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