Merge branch 'hugo' into 'main'

Add command-line arguments

See merge request !17

frag_package/fragmentation.py

-import pandas as pd
 import random
-import numpy as np
+
 
 dna_seq = {
     "ATAACATGTGGATGGCCAGTGGTCGGTTGTTACACGCCTACCGCGATGCTGAATGACCCGGACTAGAGTGGCGAAATTTATGGCGTGTGACCCGTTATGC": 100,

frag_package/fragmentation_2.py

-import pandas as pdimport randomimport numpy as npimport re
dna_seq = {
    "ATAACATGTGGATGGCCAGTGGTCGGTTGTTACACGCCTACCGCGATGCTGAATGACCCGGACTAGAGTGGCGAAATTTATGGCGTGTGACCCGTTATGC": 100,
    "TCCATTTCGGTCAGTGGGTCATTGCTAGTAGTCGATTGCATTGCCATTCTCCGAGTGATTTAGCGTGACAGCCGCAGGGAACCCATAAAATGCAATCGTA": 100}nucs = ['A','T','G','C']mononuc_freqs = [0.22, 0.25, 0.23, 0.30]
# A_dinuc_freqs = {'AA':0.27,'AT':0.25, 'AG':0.22, 'AC':0.26}
# T_dinuc_freqs = {'TA':0.27, 'TT':0.24, 'TG':0.24, 'TC':0.25}
# C_dinuc_freqs = {'CA':0.23, 'CT':0.21, 'CG':0.35, 'CC':0.21}
# G_dinuc_freqs = {'GA':0.25, 'GT':0.25, 'GG':0.23, 'GC':0.27}

mean_length = 12
std = 1

term_frags = [] 
for seq, counts in dna_seq.items():
    for _ in range(counts): 
        n_cuts = int(len(seq)/mean_length)
        
        # non-random DNA fragmentation implementation based on https://www.nature.com/articles/srep04532#Sec1
        # assume fragmentation by sonication for NGS workflow
        cuts = []
        cut_nucs = np.random.choice(nucs, n_cuts, p=mononuc_freqs) 
        for nuc in cut_nucs:
            nuc_pos = [x.start() for x in re.finditer(nuc, seq)]
            pos = np.random.choice(nuc_pos)
            while pos in cuts:
                pos = np.random.choice(nuc_pos)
            cuts.append(pos)

        cuts.sort() 
        cuts.insert(0,0)
        term_frag = ""
        for i, val in enumerate(cuts):
            if i == len(cuts)-1:
                fragment = seq[val+1:cuts[-1]]
            else:
                fragment = seq[val:cuts[i+1]]
            if mean_length-std <= len(fragment) <= mean_length+std:
                term_frag = fragment
        if term_frag == "":
            continue
        else:
            term_frags.append(term_frag)
    
with open('terminal_frags.txt', 'w') as f:
    for line in term_frags:
        f.write(line)
        f.write('\n')
\ No newline at end of file

frag_package/fragmentation_v2.py

+import argparse
+import os.path
+import re
+
+import numpy as np
+
+
+def fragmentation(fasta, seq_counts, mean_length, std):
+    nucs = ['A','T','G','C']
+    mononuc_freqs = [0.22, 0.25, 0.23, 0.30]
+    term_frags = [] 
+    for seq, counts in dna_seq.items():
+        for _ in range(counts): 
+            n_cuts = int(len(seq)/mean_length)
+            
+            # non-uniformly random DNA fragmentation implementation based on https://www.nature.com/articles/srep04532#Sec1
+            # assume fragmentation by sonication for NGS workflow
+            cuts = []
+            cut_nucs = np.random.choice(nucs, n_cuts, p=mononuc_freqs) 
+            for nuc in cut_nucs:
+                nuc_pos = [x.start() for x in re.finditer(nuc, seq)]
+                pos = np.random.choice(nuc_pos)
+                while pos in cuts:
+                    pos = np.random.choice(nuc_pos)
+                cuts.append(pos)
+
+            cuts.sort() 
+            cuts.insert(0,0)
+            term_frag = ""
+            for i, val in enumerate(cuts):
+                if i == len(cuts)-1:
+                    fragment = seq[val+1:cuts[-1]]
+                else:
+                    fragment = seq[val:cuts[i+1]]
+                if mean_length-std <= len(fragment) <= mean_length+std:
+                    term_frag = fragment
+            if term_frag == "":
+                continue
+            else:
+                term_frags.append(term_frag)
+    return term_frags
+
+def main(args):   
+    fasta, seq_counts, mean_length, std = args
+    dna_seq = {
+    "ATAACATGTGGATGGCCAGTGGTCGGTTGTTACACGCCTACCGCGATGCTGAATGACCCGGACTAGAGTGGCGAAATTTATGGCGTGTGACCCGTTATGC": 100,
+    "TCCATTTCGGTCAGTGGGTCATTGCTAGTAGTCGATTGCATTGCCATTCTCCGAGTGATTTAGCGTGACAGCCGCAGGGAACCCATAAAATGCAATCGTA": 100}
+
+    term_frags = fragmentation(fasta, seq_counts, mean_length, std)
+    with open('terminal_frags.txt', 'w') as f:
+        for line in term_frags:
+            f.write(line)
+            f.write('\n')
+
+# found on https://stackoverflow.com/questions/11540854/file-as-command-line-argument-for-argparse-error-message-if-argument-is-not-va
+def extant_file(x):
+    """
+    'Type' for argparse - checks that file exists but does not open.
+    """
+    if not os.path.exists(x):
+        # Argparse uses the ArgumentTypeError to give a rejection message like:
+        # error: argument input: x does not exist
+        raise argparse.ArgumentTypeError("{0} does not exist".format(x))
+    return x
+
+# Parse command-line arguments
+def parse_arguments():
+    parser = argparse.ArgumentParser(description="Takes as input FASTA file of cDNA sequences, a CSV with sequence counts, and mean and std. dev. of fragment lengths. Outputs most terminal fragment (within desired length range) for each sequence.")
+    
+    parser.add_argument('--fasta', required=True, type=extant_file, help="FASTA file with cDNA sequences")
+    parser.add_argument('--counts', required=True, type=extant_file, help="CSV file with sequence counts")
+    parser.add_argument('--mean', required = False, default = 10, type = int, help="Mean fragment length (default: 10)")
+    parser.add_argument('--std', required = False, default = 1, type = int, help="Standard deviation fragment length (defafult: 1)")
+    args = parser.parse_args()
+    
+    return args.fasta, args.counts, args.mean, args.std
+
+
+if __name__ == '__main__':
+    arguments = parse_arguments()
+    main(arguments)