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3 changed files with 40 additions and 13 deletions
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@ -450,15 +450,15 @@ def getmldata(gene, drug
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if gene.lower() in geneL_na:
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gene_affinity_colnames = ['mcsm_na_affinity']
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gene_affinity_colnames = ['mcsm_na_affinity', 'nca_distance']
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#X_stabilityN = common_cols_stabiltyN + geneL_na_st_cols
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cols_to_mask = ['ligand_affinity_change']#, 'mcsm_na_affinity']
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cols_to_mask_ppi2 = []
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cols_to_mask_na = ['mcsm_na_affinity']
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# both
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if gene.lower() in geneL_na_ppi2:
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gene_affinity_colnames = ['mcsm_na_affinity'] + ['mcsm_ppi2_affinity', 'interface_dist']
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gene_affinity_colnames = ['mcsm_na_affinity','nca_distance', 'mcsm_ppi2_affinity', 'interface_dist']
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#X_stabilityN = common_cols_stabiltyN + geneL_na_ppi2_st_cols
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#cols_to_mask = ['ligand_affinity_change', 'mcsm_na_affinity', 'mcsm_ppi2_affinity']
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cols_to_mask = ['ligand_affinity_change']#, 'mcsm_na_affinity']
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@ -481,27 +481,40 @@ def getmldata(gene, drug
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# mask the mcsm ligand affinity AND mcsm_na affinity columns where ligand distance > 10
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my_df_ml.loc[(my_df_ml['ligand_distance'] > 10), cols_to_mask] = 0
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#mask_check = my_df_ml[['mutationinformation', 'ligand_distance'] + cols_to_mask]
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mask_check_cols = ['mutationinformation', 'ligand_distance'] + cols_to_mask
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#---------------------------
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# mask the mcsm_ppi2_affinity column where interface_dist > 10
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#---------------------------
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if len(cols_to_mask_ppi2) > 0:
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my_df_ml.loc[(my_df_ml['interface_dist'] > 10), cols_to_mask_ppi2] = 0
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add_cols_mask = ['interface_dist'] + cols_to_mask_ppi2
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mask_check = my_df_ml[['mutationinformation', 'ligand_distance'] + cols_to_mask + add_cols_mask]
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else:
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mask_check = my_df_ml[['mutationinformation', 'ligand_distance'] + cols_to_mask ]
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#mask_check = my_df_ml[['mutationinformation', 'ligand_distance'] + cols_to_mask + add_cols_mask]
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mask_check_cols = mask_check_cols + add_cols_mask
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#---------------------------
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# mask the na_affinity column where nca_distance > 10
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#---------------------------
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if len(cols_to_mask_na) > 0:
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my_df_ml.loc[(my_df_ml['nca_distance'] > 10), cols_to_mask_na] = 0
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add_cols_mask = ['nca_distance'] + cols_to_mask_na
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mask_check = my_df_ml[['mutationinformation', 'ligand_distance'] + cols_to_mask + add_cols_mask]
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else:
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mask_check = my_df_ml[['mutationinformation', 'ligand_distance'] + cols_to_mask ]
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#mask_check = my_df_ml[['mutationinformation', 'ligand_distance'] + cols_to_mask + add_cols_mask]
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mask_check_cols = mask_check_cols + add_cols_mask
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# if gene.lower() in geneL_na_ppi2:
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# #---------------------------
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# # RPOB: mask ppi2 + na + lig cols
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# #---------------------------
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# mask_check = my_df_ml[['mutationinformation',
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# 'ligand_distance', 'ligand_affinity_change',
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# 'nca_distance','mcsm_na_affinity',
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# 'mcsm_ppi2_affinity','interface_dist']]
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# GET mask data
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mask_check = my_df_ml[mask_check_cols]
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# sanity check: check script SANITY_CHECK_mask.py
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if write_maskfile:
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# write mask file for sanity check
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14
scripts/ml/ml_functions/TEST_GetMLData.py
Normal file
14
scripts/ml/ml_functions/TEST_GetMLData.py
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@ -0,0 +1,14 @@
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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Created on Thu Sep 1 12:22:27 2022
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@author: tanu
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"""
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getmldata(gene = "katG"
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, drug = "isoniazid"
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, data_combined_model = False
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, use_or = False
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, omit_all_genomic_features = False
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, write_maskfile = True
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, write_outfile = False)
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