corrected foldx_outcome classification in combining_dfs.py as positive are Destabilising and neg as Stabilising
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1 changed files with 10 additions and 3 deletions
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@ -190,6 +190,10 @@ foldx_max = foldx_df['ddg_foldx'].max()
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foldx_min
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foldx_max
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# quick check
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len(foldx_df.loc[foldx_df['ddg_foldx'] >= 0])
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len(foldx_df.loc[foldx_df['ddg_foldx'] < 0])
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foldx_scale = lambda x : x/abs(foldx_min) if x < 0 else (x/foldx_max if x >= 0 else 'failed')
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foldx_df['foldx_scaled'] = foldx_df['ddg_foldx'].apply(foldx_scale)
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@ -216,13 +220,16 @@ else:
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, '\n======================================================')
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#-------------------------
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# foldx outcome category
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# foldx outcome category:
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# Remember, its inverse
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# +ve: Destabilising
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# -ve: Stabilising
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#--------------------------
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foldx_df['foldx_outcome'] = foldx_df['ddg_foldx'].apply(lambda x: 'Stabilising' if x >= 0 else 'Destabilising')
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foldx_df['foldx_outcome'] = foldx_df['ddg_foldx'].apply(lambda x: 'Destabilising' if x >= 0 else 'Stabilising')
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foldx_df[foldx_df['ddg_foldx']>=0].count()
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foc = foldx_df['foldx_outcome'].value_counts()
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if foc['Stabilising'] == foldx_pos and foc['Stabilising'] == foldx_pos2:
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if foc['Destabilising'] == foldx_pos and foc['Destabilising'] == foldx_pos2:
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print('\nPASS: Foldx outcome category created')
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else:
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print('\nFAIL: Foldx outcome category could NOT be created'
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