--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/deseq/sam2counts_galaxy.py	Thu Jul 05 21:02:43 2012 -0400
@@ -0,0 +1,209 @@
+#!/usr/bin/env python
+
+"""
+count.py -- Take SAM files and output a table of counts with column
+names that are the filenames, and rowname that are the reference
+names.
+
+Author: Vince Buffalo
+Email: vsbuffaloAAAAA@gmail.com (with poly-A tail removed)
+"""
+
+VERSION = 0.91
+
+import sys
+import csv
+from os import path
+try:
+    import pysam
+except ImportError:
+    sys.exit("pysam not installed; please install it\n")
+
+from optparse import OptionParser
+
+def SAM_file_to_counts(filename, bam=False, extra=False, use_all_references=True):
+    """
+    Take SAM filename, and create a hash of mapped and unmapped reads;
+    keys are reference sequences, values are the counts of occurences.
+
+    Also, a hash of qualities (either 0 or >0) of mapped reads
+    is output, which is handy for diagnostics.
+    """
+    counts = dict()
+    unique = dict()
+    nonunique = dict()
+    mode = 'r'
+    if bam:
+        mode = 'rb'
+    sf = pysam.Samfile(filename, mode)
+
+    if use_all_references:
+        # Make dictionary of all entries in header
+        for sn in sf.header['SQ']:
+            if extra:
+                unique[sn['SN']] = 0
+                nonunique[sn['SN']] = 0
+            counts[sn['SN']] = 0
+
+    for read in sf:
+        if not read.is_unmapped:
+            id_name = sf.getrname(read.rname) if read.rname != -1 else 0
+
+            if not use_all_references and not counts.get(id_name, False):
+                ## Only make keys based on aligning reads, make empty hash
+                if extra:
+                    unique[id_name] = 0
+                    nonunique[id_name] = 0
+                ## initiate entry; even if not mapped, record 0 count
+                counts[id_name] = counts.get(id_name, 0)
+        
+            
+            counts[id_name] = counts.get(id_name, 0) + 1
+
+            if extra:
+                if read.mapq == 0:
+                    nonunique[id_name] = nonunique[id_name] + 1
+                else:
+                    unique[id_name] = unique[id_name] + 1
+
+    if extra:
+        return {'counts':counts, 'unique':unique, 'nonunique':nonunique}
+
+    return {'counts':counts}
+
+def collapsed_nested_count_dict(counts_dict, all_ids, order=None):
+    """
+    Takes a nested dictionary `counts_dict` and `all_ids`, which is
+    built with the `table_dict`. All files (first keys) in
+    `counts_dict` are made into columns with order specified by
+    `order`.
+
+    Output is a dictionary with keys that are the id's (genes or
+    transcripts), with values that are ordered counts. A header will
+    be created on the first row from the ordered columns (extracted
+    from filenames).
+    """
+    if order is None:
+        col_order = counts_dict.keys()
+    else:
+        col_order = order
+
+    collapsed_dict = dict()
+    for i, filename in enumerate(col_order):
+        for id_name in all_ids:
+            if not collapsed_dict.get(id_name, False):
+                collapsed_dict[id_name] = list()
+
+            # get counts and append
+            c = counts_dict[filename].get(id_name, 0)
+            collapsed_dict[id_name].append(c)
+    return {'table':collapsed_dict, 'header':col_order}
+
+
+def counts_to_file(table_dict, outfilename, delimiter=',', labels=''):
+    """
+    A function for its side-effect of writing `table_dict` (which
+    contains a table and header), to `outfilename` with the specified
+    `delimiter`.
+    """
+    writer = csv.writer(open(outfilename, 'w'), delimiter=delimiter)
+    table = table_dict['table']
+    if labels:
+        header = labels.split(',')
+    else:
+        header = table_dict['header']
+    
+    header_row = True
+    for id_name, fields in table.items():
+        if header_row:
+            row = ['id'] + header
+            writer.writerow(row)
+            header_row = False
+
+        if id_name == 0:
+            continue
+        row = [id_name]
+        row.extend(fields)
+        writer.writerow(row)
+
+if __name__ == '__main__':
+    parser = OptionParser()
+    parser.add_option("-d", "--delimiter", dest="delimiter",
+                      help="the delimiter (default: tab)", default='\t')
+    parser.add_option("-o", "--out-file", dest="out_file",
+                      help="output filename (default: counts.txt)",
+                      default='counts.txt', action="store", type="string")
+    parser.add_option("-u", "--extra-output", dest="extra_out",
+                      help="output extra information on non-unique and unique mappers (default: False)",
+                      default=False, action="store_true")
+    parser.add_option("-b", "--bam", dest="bam",
+                      help="all input files are BAM (default: False)", 
+                      default=False, action="store_true")
+    parser.add_option("-r", "--use-all-references", dest="use_all_references",
+                      help="Use all the references from the SAM header (default: True)",
+                      default=True, action="store_false")
+    parser.add_option("-f", "--extra-out-files", dest="extra_out_files",
+                      help="comma-delimited filenames of unique and non-unique output "
+                      "(default: unique.txt,nonunique.txt)",
+                      default='unique.txt,nonunique.txt', action="store", type="string")
+    parser.add_option("-v", "--verbose", dest="verbose",
+                      help="enable verbose output")
+    parser.add_option("-l", "--columns-labels", dest="col_labels", help="comma-delimited label names for samples", action="store", type="string")
+
+    (options, args) = parser.parse_args()
+
+    if len(args) < 1:
+        parser.error("one or more SAM files as arguments required")
+
+    file_counts = dict()
+    file_unique_counts = dict()
+    file_nonunique_counts = dict()
+    all_ids = list()
+    files = [path.basename(f) for f in args]
+
+    if options.col_labels and len(files) != len(options.col_labels.split(',')):
+        parser.error("Number of sample names does not equal number of files")
+
+    if len(set(files)) != len(set(args)):
+        parser.error("file args must have unique base names (i.e. no foo/bar joo/bar)")
+
+    ## do a pre-run check that all files exist
+    for full_filename in args:
+        if not path.exists(full_filename):
+            parser.error("file '%s' does not exist" % full_filename)
+        
+    for full_filename in args:
+        filename = path.basename(full_filename)
+        ## read in SAM file, extract counts, and unpack counts
+        tmp = SAM_file_to_counts(full_filename, bam=options.bam, extra=options.extra_out,
+                                 use_all_references=options.use_all_references)
+
+        if options.extra_out:
+            counts, unique, nonunique = tmp['counts'], tmp['unique'], tmp['nonunique']
+        else:
+            counts = tmp['counts']
+
+        ## save counts, and unique/non-unique counts
+        file_counts[filename] = counts
+
+        if options.extra_out:
+            file_unique_counts[filename] = unique
+            file_nonunique_counts[filename] = nonunique
+
+        ## add all ids encountered in this in this file
+        all_ids.extend(file_counts[filename].keys())
+
+    ## Uniquify all_ids, and then take the nested file_counts
+    ## dictionary, collapse, and write to file.
+    all_ids = set(all_ids)
+    table_dict = collapsed_nested_count_dict(file_counts, all_ids, order=files)
+    counts_to_file(table_dict, options.out_file, delimiter=options.delimiter, labels=options.col_labels)
+
+    if options.extra_out:
+        unique_fn, nonunique_fn = options.extra_out_files.split(',')
+        unique_table_dict = collapsed_nested_count_dict(file_unique_counts, all_ids, order=files)
+        nonunique_table_dict = collapsed_nested_count_dict(file_nonunique_counts, all_ids, order=files)
+        
+        counts_to_file(unique_table_dict, unique_fn, delimiter=options.delimiter)
+        counts_to_file(nonunique_table_dict, nonunique_fn, delimiter=options.delimiter)
+