Update20231025

.github/workflows/heatcluster.yml

@@ -8,7 +8,7 @@ jobs:
         uses: actions/checkout@v3
 
       - name: install dependencies
-        run: pip install argparse pandas numpy pathlib seaborn matplotlib
+        run: pip install argparse pandas numpy pathlib seaborn matplotlib scipy
 
       - name: test (tab-delimited)
         run: ./HeatCluster.py -i test/small_matrix.csv

HeatCluster.py

@@ -1,34 +1,76 @@
 #!/usr/bin/python3
 
 ###########################################
-# HeatCluster-0.4.10                      #
+# HeatCluster-0.4.11                      #
 # written by Stephen Beckstrom-Sternberg  #
 # Creates SNP heat/cluster maps           #
 # from SNP matrices                       #
+# - modularized                           #
 ###########################################
 
 import argparse
+import logging
 import pandas as pd
 import numpy as np
 import seaborn as sns
 import matplotlib.pyplot as plt
+import scipy
 from pathlib import Path
 
+logging.basicConfig(format='%(asctime)s - %(message)s', datefmt='%y-%b-%d %H:%M:%S', level=logging.INFO)
+
 parser = argparse.ArgumentParser()
 parser.add_argument('-i', '--input', type=str, help='input SNP matrix file name', default='snp-dists.txt')
 parser.add_argument('-o', '--out', type=str, help='final file name', default='SNP_matrix')
 parser.add_argument('-t', '--type', type=str, help='file extension for final image', default = 'pdf')
-parser.add_argument('-v', '--version', help='print version and exit', action='version', version='%(prog)s ' + '0.4.10')
+parser.add_argument('-v', '--version', help='print version and exit', action='version', version='%(prog)s ' + '0.4.11')
 args = parser.parse_args()
 
+def main():
+    """
+    Creates image for SNP matrix.
+    """
+
+    SNPmatrix=args.input
+    logging.info('Creating figure for ' + SNPmatrix)
+
+    df = read_snp_matrix(SNPmatrix)
+    logging.debug('The input SNP matrix:')
+    logging.debug(df)
+
+    if len(df.index) > len(df.columns):
+        logging.fatal('This matrix has been melted. Sorry!')
+        exit(0)
+
+    df = clean_and_read_df(df)
+    logging.debug('The clean SNP matrix:')
+    logging.debug(df)
+
+    (df, fontSize) = determine_heatmap_size(df, SNPmatrix)
+
+    create_heatmap(df, fontSize)
+#
+    print("Done")
 def read_snp_matrix(file):
+    """
+    Reads the SNP matrix into a pandas dataframe.
+
+    Args:
+        file (str): SNP dist output file that should be converted to pandas dataframe
+
+    Returns:
+        df (DataFrame): Pandas dataframe of SNP matrix.
+    """
+    logging.debug('Determining if file is comma or tab delimited')
     tabs   = pd.read_csv(file, nrows=1, sep='\t').shape[1]
     commas = pd.read_csv(file, nrows=1, sep=',').shape[1]
     if tabs > commas:
+        logging.debug('The file is probably tab-delimited')
         df = pd.read_csv(file, sep='\t', index_col= False)
     else:
+        logging.debug('The file is probably comma-delimited')
         df = pd.read_csv(file, sep=',', index_col= False)
-
+        
     return df
 
 def clean_and_read_df(df):
@@ -41,36 +83,32 @@ def clean_and_read_df(df):
     Returns:
         df (DataFrame): Cleaned DataFrame.
     """
-     # Define consensus patterns
+    logging.debug('Dropping the first column')
+    df = df.iloc[: , 1:]
+
+    # Convert column names to strings
+    df.columns = df.columns.map(str)
+
+         # Define consensus patterns
     consensus_patterns = ['snp-dists 0.8.2', '.consensus_threshold_0.6_quality_20', 'Consensus_', 'Unnamed: 0']
 
     # Replace consensus patterns in column names
     df.columns = df.columns.str.replace('|'.join(consensus_patterns), '', regex=True)
-    # Replace consensus patterns in entire dataframe to change row names
-    df = df.replace(consensus_patterns, '', regex=True) 
 
-    # Keep only numeric columns
-    df = df.set_index(df.columns[0])
-    df.dropna(axis=0, inplace=True)
-    df.dropna(axis=1, inplace=True)  
-    return df
+    # Setting the index
+    df = df.set_index(df.columns)
 
-def main():
-    if args.input:
-        path = args.input
-    else:
-        try:
-            path = Path('./snp-dists.txt')
-            path.resolve(strict=True)
-        except FileNotFoundError:
-            path = Path('./snp_matrix.txt')
+    return df
 
-    print("Using file path:", path)
-    lines = read_snp_matrix(path)
-    numSamples = len(lines) - 1
+def determine_heatmap_size(df, SNPmatrix):
+    numSamples = len(df.columns)
+    logging.info('Found ' + str(numSamples) + ' samples in ' + SNPmatrix)
 
-    df = clean_and_read_df(lines)
+    if numSamples <= 3:
+        logging.fatal('This matrix must have 4+ samples. Sorry!')
+        exit(0)
 
+    # Set output figure size tuple based on number of samples
     if (numSamples) >= 140:
         fontSize = 2
     elif (numSamples) >=100:
@@ -79,13 +117,20 @@ def main():
         fontSize = 6
     else:
         fontSize=8    
-
+
+    logging.debug('The fontSize will be ' + str(fontSize))
+
+    logging.debug('Sorting dataframe and removing empty rows/columns')
     df = df.loc[df.sum(axis=1).sort_values(ascending=True).index]
     df.replace([np.inf, -np.inf], np.nan)
     df.dropna()
 
     df = df.reindex(columns=df.index)
-    print("df after re-indexing columns:\n\n",df,"\n\n")
+
+    return (df, fontSize)
+
+def create_heatmap(df, fontSize):
+    logging.debug('Creating heatmap')
     heatmap = sns.clustermap(
         df,
         xticklabels=True,
@@ -107,16 +152,18 @@ def main():
 # Set orientation of axes labels
     plt.setp(heatmap.ax_heatmap.get_xticklabels(), rotation=45, ha='right',fontsize=fontSize)
     plt.setp(heatmap.ax_heatmap.get_yticklabels(), rotation='horizontal', fontsize=fontSize)
-    
+
     plt.title('SNP matrix visualized via HeatCluster')
-        
+
     heatmap.ax_row_dendrogram.set_visible(False)
     heatmap.ax_col_dendrogram.set_visible(False)
 
-    heatmap.savefig('SNP_matrix.pdf')
+    SNP_matrix = args.out
+    outfile = (args.out + "." + args.type)
+    print("\tOutput file is ", outfile)
+    heatmap.savefig(outfile)
 
     plt.show()
-    print("Done")
 
 if __name__ == "__main__":
     main()