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annotate flexynesis_utils.py @ 3:0a8fe19cebeb draft

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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/flexynesis commit b2463fb68d0ae54864d87718ee72f5e063aa4587
author bgruening
date Tue, 24 Jun 2025 05:56:31 +0000
parents
children 9450286c42ab
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3
0a8fe19cebeb planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/flexynesis commit b2463fb68d0ae54864d87718ee72f5e063aa4587
bgruening
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1 #!/usr/bin/env python
0a8fe19cebeb planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/flexynesis commit b2463fb68d0ae54864d87718ee72f5e063aa4587
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3 import argparse
0a8fe19cebeb planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/flexynesis commit b2463fb68d0ae54864d87718ee72f5e063aa4587
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4 import os
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5 import sys
0a8fe19cebeb planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/flexynesis commit b2463fb68d0ae54864d87718ee72f5e063aa4587
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6 from pathlib import Path
0a8fe19cebeb planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/flexynesis commit b2463fb68d0ae54864d87718ee72f5e063aa4587
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8 import pandas as pd
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11 def read_data(data_input, index=False):
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12 """Load CSV or TSV data file."""
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13 try:
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14 file_ext = Path(data_input).suffix.lower()
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15 sep = ',' if file_ext == '.csv' else '\t'
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16 index_col = 0 if index else None
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18 if file_ext in ['.csv', '.tsv', '.txt', '.tab', '.tabular']:
0a8fe19cebeb planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/flexynesis commit b2463fb68d0ae54864d87718ee72f5e063aa4587
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19 return pd.read_csv(data_input, sep=sep, index_col=index_col)
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20 else:
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21 raise ValueError(f"Unsupported file extension: {file_ext}")
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22 except Exception as e:
0a8fe19cebeb planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/flexynesis commit b2463fb68d0ae54864d87718ee72f5e063aa4587
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23 raise ValueError(f"Error loading data from {data_input}: {e}") from e
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26 def binarize_mutations(df, gene_idx=1, sample_idx=2):
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27 """
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28 Binarize mutation data by creating a matrix of gene x sample with 1/0 values.
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29 """
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30 # galaxy index is 1-based, convert to zero-based
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31 gene_idx -= 1
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32 sample_idx -= 1
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33 # check idx
0a8fe19cebeb planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/flexynesis commit b2463fb68d0ae54864d87718ee72f5e063aa4587
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34 if gene_idx >= len(df.columns) or sample_idx >= len(df.columns):
0a8fe19cebeb planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/flexynesis commit b2463fb68d0ae54864d87718ee72f5e063aa4587
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35 raise ValueError(f"Column indices out of bounds. DataFrame has {len(df.columns)} columns, "
0a8fe19cebeb planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/flexynesis commit b2463fb68d0ae54864d87718ee72f5e063aa4587
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36 f"but requested indices are {gene_idx} and {sample_idx}")
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37 if gene_idx == sample_idx:
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38 raise ValueError("Gene and sample column indices must be different")
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39
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40 # Get column names by index
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41 gene_col = df.columns[gene_idx]
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42 print(f"Using gene column: {gene_col} (index {gene_idx})")
0a8fe19cebeb planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/flexynesis commit b2463fb68d0ae54864d87718ee72f5e063aa4587
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43 sample_col = df.columns[sample_idx]
0a8fe19cebeb planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/flexynesis commit b2463fb68d0ae54864d87718ee72f5e063aa4587
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44 print(f"Using sample column: {sample_col} (index {sample_idx})")
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45
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46 # Check if columns contain data
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47 if df[gene_col].isna().all():
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48 raise ValueError(f"Gene column (index {gene_idx}) contains only NaN values.")
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49 if df[sample_col].isna().all():
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50 raise ValueError(f"Sample column (index {sample_idx}) contains only NaN values.")
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51
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52 # Group by gene and sample, count mutations
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53 mutation_counts = df.groupby([gene_col, sample_col]).size().reset_index(name='count')
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54
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55 # Create pivot table
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56 mutation_matrix = mutation_counts.pivot(index=gene_col, columns=sample_col, values='count').fillna(0)
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57
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58 # Binarize: convert any count > 0 to 1
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59 mutation_matrix[mutation_matrix > 0] = 1
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60
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61 return mutation_matrix
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63
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64 def make_data_dict(clin_path, omics_paths):
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65 """Read clinical and omics data files into a dictionary."""
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66 data = {}
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67
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68 # Read clinical data
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69 print(f"Reading clinical data from {clin_path}")
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70 try:
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71 clin = read_data(clin_path, index=True)
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72
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73 if clin.empty:
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74 raise ValueError(f"Clinical file {clin_path} is empty")
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75 data['clin'] = clin
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76 print(f"Loaded clinical data: {clin.shape[0]} samples, {clin.shape[1]} features")
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77 except Exception as e:
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78 raise ValueError(f"Error reading clinical file {clin_path}: {e}")
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79
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80 # Read omics data
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81 print(f"Reading omics data from {', '.join(omics_paths)}")
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82 for path in omics_paths:
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83 try:
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84 name = os.path.splitext(os.path.basename(path))[0]
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85 df = read_data(path, index=True)
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86 if df.empty:
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87 print(f"Warning: Omics file {path} is empty, skipping")
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88 continue
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89 data[name] = df
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90 print(f"Loaded {name}: {df.shape[0]} features, {df.shape[1]} samples")
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91 except Exception as e:
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92 print(f"Warning: Error reading omics file {path}: {e}")
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93 continue
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94
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95 if len(data) == 1: # Only clinical data loaded
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96 raise ValueError("No omics data was successfully loaded")
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97
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98 return data
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99
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100
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101 def validate_data_consistency(data):
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102 """Validate that clinical and omics data have consistent samples."""
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103 clin_samples = set(data['clin'].index)
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104
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105 for name, df in data.items():
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106 if name == 'clin':
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107 continue
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108
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109 omics_samples = set(df.columns)
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110
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111 # Check for sample overlap
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112 common_samples = clin_samples.intersection(omics_samples)
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113 if len(common_samples) == 0:
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114 raise ValueError(f"No common samples between clinical data and {name}")
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115
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116 missing_in_omics = clin_samples - omics_samples
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117 missing_in_clin = omics_samples - clin_samples
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118
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119 if missing_in_omics:
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120 print(f"Warning: {len(missing_in_omics)} clinical samples not found in {name}")
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121 if missing_in_clin:
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122 print(f"Warning: {len(missing_in_clin)} samples in {name} not found in clinical data")
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123
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124 return True
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125
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126
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127 def split_and_save_data(data, ratio=0.7, output_dir='.'):
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128 """Split data into train/test sets and save to files."""
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129 # Validate data consistency first
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130 validate_data_consistency(data)
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131
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132 samples = data['clin'].index.tolist()
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133
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134 train_samples = list(pd.Series(samples).sample(frac=ratio, random_state=42))
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135 test_samples = list(set(samples) - set(train_samples))
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136
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137 train_data = {}
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138 test_data = {}
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139
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140 for key, df in data.items():
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141 try:
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142 if key == 'clin':
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143 train_data[key] = df.loc[df.index.intersection(train_samples)]
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144 test_data[key] = df.loc[df.index.intersection(test_samples)]
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145 else:
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146 train_data[key] = df.loc[:, df.columns.intersection(train_samples)]
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147 test_data[key] = df.loc[:, df.columns.intersection(test_samples)]
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148 except Exception as e:
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149 print(f"Error splitting data {key}: {e}")
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150 continue
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151
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152 # Create output directories
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153 os.makedirs(os.path.join(output_dir, 'train'), exist_ok=True)
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154 os.makedirs(os.path.join(output_dir, 'test'), exist_ok=True)
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155
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156 # Save train and test data
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157 for key in data.keys():
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158 try:
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159 train_data[key].to_csv(os.path.join(output_dir, 'train', f'{key}.csv'))
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160 test_data[key].to_csv(os.path.join(output_dir, 'test', f'{key}.csv'))
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161 except Exception as e:
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162 print(f"Error saving {key}: {e}")
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163 continue
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164
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165
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166 def main():
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167 parser = argparse.ArgumentParser(description='Flexynesis extra utilities')
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168
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169 parser.add_argument("--util", type=str, required=True,
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170 choices=['split', 'binarize'],
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171 help="Utility function: 'split' for spiting data to train and test, 'binarize' for creating a binarized matrix from a mutation data")
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172
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173 # Arguments for split
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174 parser.add_argument('--clin', required=False,
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175 help='Path to clinical data CSV file (samples in rows)')
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176 parser.add_argument('--omics', required=False,
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177 help='Comma-separated list of omics CSV files (samples in columns)')
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178 parser.add_argument('--split', type=float, default=0.7,
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179 help='Train split ratio (default: 0.7)')
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180
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181 # Arguments for binarize
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182 parser.add_argument('--mutations', type=str, required=False,
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183 help='Path to mutation data CSV file (samples in rows, genes in columns)')
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184 parser.add_argument('--gene_idx', type=int, default=0,
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185 help='Column index for genes in mutation data (default: 0)')
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186 parser.add_argument('--sample_idx', type=int, default=1,
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187 help='Column index for samples in mutation data (default: 1)')
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188
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189 # common arguments
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190 parser.add_argument('--out', default='.',
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191 help='Output directory (default: current directory)')
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192
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193 args = parser.parse_args()
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194
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195 try:
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196 # validate utility function
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197 if not args.util:
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198 raise ValueError("Utility function must be specified")
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199 if args.util not in ['split', 'binarize']:
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200 raise ValueError(f"Invalid utility function: {args.util}")
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201
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202 if args.util == 'split':
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203 # Validate inputs
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204 if not args.clin:
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205 raise ValueError("Clinical data file must be provided")
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206 if not args.omics:
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207 raise ValueError("At least one omics file must be provided")
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208 if not os.path.isfile(args.clin):
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209 raise FileNotFoundError(f"Clinical file not found: {args.clin}")
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210 # Validate split ratio
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211 if not 0 < args.split < 1:
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212 raise ValueError(f"Split ratio must be between 0 and 1, got {args.split}")
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213
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214 elif args.util == 'binarize':
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215 # Validate mutation data file
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216 if not args.mutations:
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217 raise ValueError("Mutation data file must be provided")
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218 if not os.path.isfile(args.mutations):
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219 raise FileNotFoundError(f"Mutation data file not found: {args.mutations}")
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220 # Validate gene and sample indices
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221 if args.gene_idx < 0 or args.sample_idx < 0:
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222 raise ValueError("Gene and sample indices must be non-negative integers")
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223
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224 # Create output directory if it doesn't exist
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225 if not os.path.exists(args.out):
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226 os.makedirs(args.out)
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227
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228 if args.util == 'split':
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229 # Parse omics files
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230 omics_files = [f.strip() for f in args.omics.split(',') if f.strip()]
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231 if not omics_files:
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232 raise ValueError("At least one omics file must be provided")
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233 # Check omics files exist
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234 for f in omics_files:
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235 if not os.path.isfile(f):
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236 raise FileNotFoundError(f"Omics file not found: {f}")
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237 data = make_data_dict(args.clin, omics_files)
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238 split_and_save_data(data, ratio=args.split, output_dir=args.out)
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239
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240 elif args.util == 'binarize':
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241 mutations_df = read_data(args.mutations, index=False)
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242 if mutations_df.empty:
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243 raise ValueError("Mutation data file is empty")
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244
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245 binarized_matrix = binarize_mutations(mutations_df, gene_idx=args.gene_idx, sample_idx=args.sample_idx)
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246 # Save binarized matrix
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247 output_file = os.path.join(args.out, 'binarized_mutations.csv')
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248 binarized_matrix.to_csv(output_file)
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249 print(f"Binarized mutation matrix saved to {output_file}")
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250
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251 except Exception as e:
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252 print(f"Error: {e}", file=sys.stderr)
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253 sys.exit(1)
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254
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255
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256 if __name__ == "__main__":
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257 main()