# HG changeset patch
# User bzonnedda
# Date 1486396527 18000
# Node ID 54973c4a1125d3f8422c70da7ef9d6973ffc979a
# Parent  9e24f334dc80b6b16c27f0c6886941e62ac61370
Uploaded

diff -r 9e24f334dc80 -r 54973c4a1125 conifer.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/conifer.py	Mon Feb 06 10:55:27 2017 -0500
@@ -0,0 +1,692 @@
+#######################################################################
+#######################################################################
+# CoNIFER: Copy Number Inference From Exome Reads
+# Developed by Niklas Krumm (C) 2012
+# nkrumm@gmail.com
+# 
+# homepage: http://conifer.sf.net
+# This program is described in:
+# Krumm et al. 2012. Genome Research. doi:10.1101/gr.138115.112
+#
+# This file is part of CoNIFER.
+# CoNIFER is free software:  you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as published by
+# the Free Software Foundation, either version 3 of the License, or
+# (at your option) any later version.
+# 
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+# 
+# You should have received a copy of the GNU General Public License
+# along with this program.  If not, see <http://www.gnu.org/licenses/>.
+#######################################################################
+#######################################################################
+
+import argparse
+import os, sys, copy
+import glob
+import csv
+import conifer_functions as cf
+import operator
+from tables import *
+import numpy  as np
+
+def CF_analyze(args):
+	# do path/file checks:
+	try: 
+		# read probes table
+		probe_fn = str(args.probes[0])
+		probes = cf.loadProbeList(probe_fn)
+		num_probes = len(probes)
+		print '[INIT] Successfully read in %d probes from %s' % (num_probes, probe_fn)
+	except IOError as e: 
+		print '[ERROR] Cannot read probes file: ', probe_fn
+		sys.exit(0)
+	
+	try: 
+		svd_outfile_fn = str(args.output)
+		# h5file_out = openFile(svd_outfile_fn, mode='w')
+		h5file_out = open_file(svd_outfile_fn, mode='w')
+		# probe_group = h5file_out.createGroup("/","probes","probes")
+		probe_group = h5file_out.create_group("/","probes","probes")
+	except IOError as e: 
+		print '[ERROR] Cannot open SVD output file for writing: ', svd_outfile_fn
+		sys.exit(0)
+	
+	if args.write_svals != "":
+		sval_f = open(args.write_svals,'w')
+	
+	if args.plot_scree != "":
+		try:
+			import matplotlib
+			matplotlib.use('Agg')
+			import matplotlib.pyplot as plt
+			import pylab as P
+			from matplotlib.lines import Line2D
+			from matplotlib.patches import Rectangle
+		except:
+			print "[ERROR] One or more of the required modules for plotting cannot be loaded! Are matplotlib and pylab installed?"
+			sys.exit(0)
+		
+		plt.gcf().clear()
+		fig = plt.figure(figsize=(10,5))
+		ax = fig.add_subplot(111)
+	
+	rpkm_dir = str(args.rpkm_dir[0])
+	rpkm_files = glob.glob(rpkm_dir + "/*")
+	if len(rpkm_files) == 0:
+		print '[ERROR] Cannot find any files in RPKM directory (or directory path is incorrect): ', rpkm_dir
+		sys.exit(0)
+	elif len(rpkm_files) == 1:
+		print '[ERROR] Found only 1 RPKM file (sample). CoNIFER requires multiple samples (8 or more) to run. Exiting.'
+		sys.exit(0)
+	elif len(rpkm_files) < 8:
+		print '[WARNING] Only found %d samples... this is less than the recommended minimum, and CoNIFER may not analyze this dataset correctly!' % len(rpkm_files)
+	elif len(rpkm_files) <= int(args.svd):
+		print '[ERROR] The number of SVD values specified (%d) must be less than the number of samples (%d). Either add more samples to the analysis or reduce the --svd parameter! Exiting.' % (len(rpkm_files), int(args.svd))
+		sys.exit(0)
+	else:
+		print '[INIT] Found %d RPKM files in %s' % (len(rpkm_files), rpkm_dir)
+	
+	# read in samples names and generate file list
+	samples = {}
+	for f in rpkm_files:
+		s = '.'.join(f.split('/')[-1].split('.')[0:-1])
+		print "[INIT] Mapping file to sampleID: %s --> %s" % (f, s)
+		samples[s] = f
+	
+	#check uniqueness and total # of samples
+	if len(set(samples)) != len(set(rpkm_files)):
+		print '[ERROR] Could not successfully derive sample names from RPKM filenames. There are probably non-unique sample names! Please rename files using <sampleID>.txt format!'
+		sys.exit(0)
+	
+	# LOAD RPKM DATA
+	RPKM_data = np.zeros([num_probes,len(samples)], dtype=np.float)
+	failed_samples = 0
+	
+	for i,s in enumerate(samples.keys()):
+		t = np.loadtxt(samples[s], dtype=np.float, delimiter="\t", skiprows=0, usecols=[2])
+		if len(t) != num_probes:
+			print "[WARNING] Number of RPKM values for %s in file %s does not match number of defined probes in %s. **This sample will be dropped from analysis**!" % (s, samples[s], probe_fn)
+			_ = samples.pop(s)
+			failed_samples += 1
+		else:
+			RPKM_data[:,i] = t
+			print "[INIT] Successfully read RPKM data for sampleID: %s" % s	
+	
+	RPKM_data = RPKM_data[:,0:len(samples)]
+	print "[INIT] Finished reading RPKM files. Total number of samples in experiment: %d (%d failed to read properly)" % (len(samples), failed_samples)
+	
+	if len(samples) <= int(args.svd):
+		print '[ERROR] The number of SVD values specified (%d) must be less than the number of samples (%d). Either add more samples to the analysis or reduce the --svd parameter! Exiting.' % (int(args.svd), len(samples))
+		sys.exit(0)
+	
+	# BEGIN 
+	chrs_to_process = set(map(operator.itemgetter("chr"),probes))
+	chrs_to_process_str = ', '.join([cf.chrInt2Str(c) for c in chrs_to_process])
+	print '[INIT] Attempting to process chromosomes: ', chrs_to_process_str
+	
+	
+	
+	for chr in chrs_to_process:
+		print "[RUNNING: chr%d] Now on: %s" %(chr, cf.chrInt2Str(chr))
+		chr_group_name = "chr%d" % chr
+		# chr_group = h5file_out.createGroup("/",chr_group_name,chr_group_name)
+		chr_group = h5file_out.create_group("/",chr_group_name,chr_group_name)
+		
+		chr_probes = filter(lambda i: i["chr"] == chr, probes)
+		num_chr_probes = len(chr_probes)
+		start_probeID = chr_probes[0]['probeID']
+		stop_probeID = chr_probes[-1]['probeID']
+		print "[RUNNING: chr%d] Found %d probes; probeID range is [%d-%d]" % (chr, len(chr_probes), start_probeID-1, stop_probeID) # probeID is 1-based and slicing is 0-based, hence the start_probeID-1 term
+		
+		rpkm = RPKM_data[start_probeID:stop_probeID,:]
+		
+		print "[RUNNING: chr%d] Calculating median RPKM" % chr
+		median = np.median(rpkm,1)
+		sd = np.std(rpkm,1)
+		probe_mask = median >= float(args.min_rpkm)
+		print "[RUNNING: chr%d] Masking %d probes with median RPKM < %f" % (chr, np.sum(probe_mask==False), float(args.min_rpkm))
+		
+		rpkm = rpkm[probe_mask, :]
+		num_chr_probes = np.sum(probe_mask)
+		
+		if num_chr_probes <= len(samples):
+			print "[ERROR] This chromosome has fewer informative probes than there are samples in the analysis! There are probably no mappings on this chromosome. Please remove these probes from the probes.txt file"
+			sys.exit(0)
+		
+		probeIDs = np.array(map(operator.itemgetter("probeID"),chr_probes))[probe_mask]
+		probe_starts = np.array(map(operator.itemgetter("start"),chr_probes))[probe_mask]
+		probe_stops = np.array(map(operator.itemgetter("stop"),chr_probes))[probe_mask]	
+		gene_names =  np.array(map(operator.itemgetter("name"),chr_probes))[probe_mask]	
+		
+		dt = np.dtype([('probeID',np.uint32),('start',np.uint32),('stop',np.uint32), ('name', np.str_, 20)])
+		
+		out_probes = np.empty(num_chr_probes,dtype=dt)
+		out_probes['probeID'] = probeIDs
+		out_probes['start'] = probe_starts
+		out_probes['stop'] = probe_stops
+		out_probes['name'] = gene_names
+		# probe_table = h5file_out.createTable(probe_group,"probes_chr%d" % chr,cf.probe,"chr%d" % chr)
+		probe_table = h5file_out.create_table(probe_group,"probes_chr%d" % chr,cf.probe,"chr%d" % chr)
+		probe_table.append(out_probes)
+		
+		print "[RUNNING: chr%d] Calculating ZRPKM scores..." % chr
+		rpkm = np.apply_along_axis(cf.zrpkm, 0, rpkm, median[probe_mask], sd[probe_mask])
+		
+		# svd transform
+		print "[RUNNING: chr%d] SVD decomposition..." % chr
+		components_removed = int(args.svd)
+		
+		U, S, Vt = np.linalg.svd(rpkm,full_matrices=False)
+		new_S = np.diag(np.hstack([np.zeros([components_removed]),S[components_removed:]]))
+		
+		if args.write_svals != "":
+			sval_f.write('chr' + str(chr) + '\t' + '\t'.join([str(_i) for _i in S]) + "\n")
+		
+		if args.plot_scree != "":
+			ax.plot(S, label='chr' + str(chr),lw=0.5)
+		
+		# reconstruct data matrix
+		rpkm = np.dot(U, np.dot(new_S, Vt))
+		
+		
+		# save to HDF5 file
+		print "[RUNNING: chr%d] Saving SVD-ZRPKM values" % chr
+		
+		for i,s in enumerate(samples):
+			out_data = np.empty(num_chr_probes,dtype='u4,f8')
+			out_data['f0'] = probeIDs
+			out_data['f1'] = rpkm[:,i]
+			# sample_tbl = h5file_out.createTable(chr_group,"sample_" + str(s),cf.rpkm_value,"%s" % str(s))
+			sample_tbl = h5file_out.create_table(chr_group,"sample_" + str(s),cf.rpkm_value,"%s" % str(s))
+			sample_tbl.append(out_data)
+	
+	
+	print "[RUNNING] Saving sampleIDs to file..."
+	# sample_group = h5file_out.createGroup("/","samples","samples")
+	# sample_table = h5file_out.createTable(sample_group,"samples",cf.sample,"samples")
+	sample_group = h5file_out.create_group("/","samples","samples")
+	sample_table = h5file_out.create_table(sample_group,"samples",cf.sample,"samples")
+	dt = np.dtype([('sampleID',np.str_,100)])
+	out_samples = np.empty(len(samples.keys()),dtype=dt)
+	out_samples['sampleID'] = np.array(samples.keys())
+	sample_table.append(out_samples)
+	
+	
+	if args.write_sd != "":
+		print "[RUNNING] Calculating standard deviations for all samples (this can take a while)..."
+		
+		sd_file = open(args.write_sd,'w')
+		
+		for i,s in enumerate(samples):
+			# collect all SVD-ZRPKM values
+			count = 1
+			for chr in chrs_to_process:
+				if count == 1:
+					sd_out = h5file_out.root._f_getChild("chr%d" % chr)._f_getChild("sample_%s" % s).read(field="rpkm").flatten()
+				else:
+					sd_out = np.hstack([sd_out,out.h5file_out.root._f_getChild("chr%d" % chr)._f_getChild("sample_%s" % s).read(field="rpkm").flatten()])
+				
+				sd = np.std(sd_out)
+			sd_file.write("%s\t%f\n" % (s,sd))
+		
+		sd_file.close()
+	
+	if args.plot_scree != "":
+		plt.title("Scree plot")
+		if len(samples) < 50:
+			plt.xlim([0,len(samples)])
+			plt.xlabel("S values")
+		else:
+			plt.xlim([0,50])
+			plt.xlabel("S values (only first 50 plotted)")
+		plt.ylabel("Relative contributed variance")		
+		plt.savefig(args.plot_scree)
+	
+	print "[FINISHED]"
+	h5file_out.close()
+	sys.exit(0)
+
+def CF_export(args):
+	try: 
+		h5file_in_fn = str(args.input)
+		# h5file_in = openFile(h5file_in_fn, mode='r')
+		h5file_in = open_file(h5file_in_fn, mode='r')
+	except IOError as e: 
+		print '[ERROR] Cannot open CoNIFER input file for reading: ', h5file_in_fn
+		sys.exit(0)	
+	
+	# read probes
+	probes = {}
+	for probes_chr in h5file_in.root.probes:
+		probes[probes_chr.title] = probes_chr.read()
+	
+	if args.sample =='all':
+		all_samples = list(h5file_in.root.samples.samples.read(field="sampleID"))
+		
+		out_path = os.path.abspath(args.output)
+		
+		print "[INIT] Preparing to export all samples (%d samples) to %s" % (len(all_samples), out_path)
+		for sample in all_samples:
+			try:
+				outfile_fn = out_path + "/" + sample + ".bed"
+				outfile_f = open(outfile_fn,'w')
+			except IOError as e:
+				print '[ERROR] Cannot open output file for writing: ', outfile_fn
+				sys.exit(0)
+			print "[RUNNING] Exporting %s" % sample
+			
+			cf.export_sample(h5file_in,sample,probes,outfile_f)
+			outfile_f.close()
+	
+	elif len(args.sample) == 1:
+		out_path = os.path.abspath(args.output)
+		sample = args.sample[0]
+		print "[INIT] Preparing to export sampleID %s to %s" % (args.sample[0], out_path)
+		try:
+			if os.path.isdir(out_path):
+				outfile_fn = out_path + "/" + sample + ".bed"
+			else:
+				outfile_fn = out_path
+			outfile_f = open(outfile_fn,'w')
+		except IOError as e:
+			print '[ERROR] Cannot open output file for writing: ', outfile_fn
+			sys.exit(0)
+		print "[RUNNING] Exporting %s to %s" % (sample, outfile_fn)
+		
+		cf.export_sample(h5file_in,sample,probes,outfile_f)
+		outfile_f.close()
+	
+	else:
+		out_path = os.path.abspath(args.output)
+		print "[INIT] Preparing to export %d samples to %s" % (len(args.sample), out_path)
+		for sample in args.sample:
+			try:
+				if os.path.isdir(out_path):
+					outfile_fn = out_path + "/" + sample + ".bed"
+				else:
+					outfile_fn = out_path
+				outfile_f = open(outfile_fn,'w')
+			except IOError as e:
+				print '[ERROR] Cannot open output file for writing: ', outfile_fn
+				sys.exit(0)
+			print "[RUNNING] Exporting %s to %s" % (sample, outfile_fn)
+			
+			cf.export_sample(h5file_in,sample,probes,outfile_f)
+			outfile_f.close()		
+	sys.exit(0)
+
+def CF_call(args):
+	try: 
+		h5file_in_fn = str(args.input)
+		# h5file_in = openFile(h5file_in_fn, mode='r')
+		h5file_in = open_file(h5file_in_fn, mode='r')
+	except IOError as e: 
+		print '[ERROR] Cannot open CoNIFER input file for reading: ', h5file_in_fn
+		sys.exit(0)		
+	
+	try: 
+		callfile_fn = str(args.output)
+		callfile_f = open(callfile_fn, mode='w')
+	except IOError as e: 
+		print '[ERROR] Cannot open output file for writing: ', callfile_fn
+		sys.exit(0)
+	
+	chrs_to_process = []
+	for chr in h5file_in.root:
+		if chr._v_title not in ('probes','samples'):
+			chrs_to_process.append(chr._v_title.replace("chr",""))
+	
+	h5file_in.close()
+	
+	print '[INIT] Initializing caller at threshold = %f' % (args.threshold)
+	
+	r = cf.rpkm_reader(h5file_in_fn)
+	
+	all_calls = []
+	
+	for chr in chrs_to_process:
+		print '[RUNNING] Now processing chr%s' % chr
+		data = r.getExonValuesByRegion(chr)
+		
+		#raw_data = copy.copy(data)
+		_ = data.smooth()
+		
+		mean= np.mean(data.rpkm,axis=1)
+		sd =  np.std(data.rpkm,axis=1)
+		
+		for sample in r.getSampleList():
+			sample_data = data.getSample([sample]).flatten()
+			#sample_raw_data = raw_data.getSample([sample]).flatten()
+			
+			dup_mask = sample_data >= args.threshold
+			del_mask = sample_data <= -1*args.threshold
+			
+			dup_bkpoints = cf.getbkpoints(dup_mask) #returns exon coordinates for this chromosome (numpy array coords)
+			del_bkpoints = cf.getbkpoints(del_mask)
+			
+			
+			dups = []
+			for start,stop in dup_bkpoints:
+				try: new_start =  np.max(np.where(sample_data[:start] < (mean[:start] + 3*sd[:start])))
+				except ValueError: new_start = 0
+				try: new_stop = stop + np.min(np.where(sample_data[stop:] < (mean[stop:] + 3*sd[stop:])))
+				except ValueError: new_stop = data.shape[1]-1
+				dups.append({"sampleID":sample,"chromosome":  cf.chrInt2Str(chr), "start":data.exons[new_start]["start"], "stop": data.exons[new_stop]["stop"], "state": "dup"})
+			
+			dels = []
+			for start,stop in del_bkpoints:	
+				try: new_start =  np.max(np.where(sample_data[:start] > (-1*mean[:start] - 3*sd[:start])))
+				except ValueError: new_start = 0
+				try: new_stop = stop + np.min(np.where(sample_data[stop:] > (-1*mean[stop:] - 3*sd[stop:])))
+				except ValueError: new_stop = data.shape[1]-1
+				dels.append({"sampleID":sample,"chromosome": cf.chrInt2Str(chr), "start":data.exons[new_start]["start"], "stop": data.exons[new_stop]["stop"], "state": "del"})
+			
+			dels = cf.mergeCalls(dels) #merges overlapping calls
+			dups = cf.mergeCalls(dups)
+			
+			#print sampleID, len(dels), len(dups)
+			
+			all_calls.extend(list(dels))
+			all_calls.extend(list(dups))
+	
+	# print calls to file
+	header = ['sampleID','chromosome','start','stop','state']
+	
+	callfile_f.write('\t'.join(header) + "\n")
+	for call in all_calls:
+		print "%s\t%s\t%d\t%d\t%s" % (call["sampleID"], call["chromosome"], call["start"], call["stop"], call["state"])
+		callfile_f.write("%s\t%s\t%d\t%d\t%s\n" % (call["sampleID"], call["chromosome"], call["start"], call["stop"], call["state"]))
+	
+	sys.exit(0)
+
+def CF_plot(args):
+	try:
+		import locale
+		import matplotlib
+		matplotlib.use('Agg')
+		import matplotlib.pyplot as plt
+		import pylab as P
+		from matplotlib.lines import Line2D
+		from matplotlib.patches import Rectangle
+		_ = locale.setlocale(locale.LC_ALL, '')
+	except:
+		print "[ERROR] One or more of the required modules for plotting cannot be loaded! Are matplotlib and pylab installed?"
+		sys.exit(0)
+		
+		
+	chr, start, stop = cf.parseLocString(args.region)
+	
+	r = cf.rpkm_reader(args.input)
+	
+	data = r.getExonValuesByRegion(chr,start,stop)
+	_ = data.smooth()
+	
+	plt.gcf().clear()
+	fig = plt.figure(figsize=(10,5))
+	ax = fig.add_subplot(111)
+	
+	
+	ax.plot(data.rpkm, linewidth = 0.3, c='k')
+	
+	
+	if args.sample != 'none':
+		cnt = 1
+		coloriter = iter(['r','b','g','y'])
+		for sample in args.sample:
+			try:
+				color, sampleID = sample.split(":")
+			except:
+				color =coloriter.next()
+				sampleID = sample
+			
+			ax.plot(data.getSample([sampleID]), linewidth = 1, c=color, label = sampleID)
+			
+			if cnt == 1:
+				cf.plotRawData(ax, r.getExonValuesByRegion(chr,start,stop,sampleList=[sampleID]).getSample([sampleID]),color=color)
+			cnt +=1
+		plt.legend(prop={'size':10},frameon=False)
+		
+	cf.plotGenes(ax, data)
+	cf.plotGenomicCoords(plt,data)
+	plt.xlim(0,data.shape[1])
+	plt.ylim(-3,3)
+	
+	plt.title("%s: %s - %s" % (cf.chrInt2Str(chr),locale.format("%d",start, grouping=True),locale.format("%d",stop, grouping=True)))
+	plt.xlabel("Position")
+	plt.ylabel("SVD-ZRPKM Values")
+	
+	plt.savefig(args.output)
+	
+	sys.exit(0)
+
+def CF_plotcalls(args):
+	try:
+		import matplotlib
+		matplotlib.use('Agg')
+		import matplotlib.pyplot as plt
+		import pylab as P
+		from matplotlib.lines import Line2D
+		from matplotlib.patches import Rectangle
+	except:
+		print "[ERROR] One or more of the required modules for plotting cannot be loaded! Are matplotlib and pylab installed?"
+		sys.exit(0)
+	
+	import locale	
+	try:
+		_ = locale.setlocale(locale.LC_ALL, 'en_US')
+	except:
+		_ = locale.setlocale(locale.LC_ALL, '')
+	
+	try: 
+		callfile_fn = str(args.calls)
+		callfile_f = open(callfile_fn, mode='r')
+	except IOError as e: 
+		print '[ERROR] Cannot open call file for reading: ', callfile_fn
+		sys.exit(0)
+	
+	all_calls = []
+	header = callfile_f.readline()
+	
+	for line in callfile_f:
+		sampleID, chr, start, stop, state = line.strip().split()
+		chr = cf.chrStr2Int(chr)
+		all_calls.append({"chromosome":int(chr), "start":int(start), "stop":int(stop), "sampleID":sampleID})
+	
+	r = cf.rpkm_reader(args.input)
+	
+	for call in all_calls:
+		chr = call["chromosome"]
+		start = call["start"]
+		stop = call["stop"]
+		sampleID = call["sampleID"]
+		
+		exons = r.getExonIDs(chr,int(start),int(stop))
+		
+		
+		window_start = max(exons[0]-args.window,0)
+		window_stop = exons[-1]+args.window
+		
+		data = r.getExonValuesByExons(chr,window_start, window_stop)
+		_ = data.smooth()
+		
+		plt.gcf().clear()
+		fig = plt.figure(figsize=(10,5))
+		ax = fig.add_subplot(111)
+		
+		
+		ax.plot(data.rpkm, linewidth = 0.3, c='k')
+		
+		
+		ax.plot(data.getSample([sampleID]), linewidth = 1, c='r', label = sampleID)
+		cf.plotRawData(ax, r.getExonValuesByExons(chr,window_start, window_stop,sampleList=[sampleID]).getSample([sampleID]),color='r')
+		
+		plt.legend(prop={'size':10},frameon=False)
+		
+		cf.plotGenes(ax, data)
+		cf.plotGenomicCoords(plt,data)
+		
+		exon_start = np.where(data.exons["start"] == start)[0][0]
+		exon_stop = np.where(data.exons["stop"] == stop)[0][0]
+		_ = ax.add_line(matplotlib.lines.Line2D([exon_start,exon_stop],[2,2],color='k',lw=6,linestyle='-',alpha=1,solid_capstyle='butt'))
+		
+		_ = plt.xlim(0,data.shape[1])
+		_ = plt.ylim(-3,3)
+		
+		plt.title("%s: %s - %s" % (cf.chrInt2Str(chr),locale.format("%d",start, grouping=True),locale.format("%d",stop, grouping=True)))
+		plt.xlabel("Position")
+		plt.ylabel("SVD-ZRPKM Values")
+		outfile = "%s_%d_%d_%s.png" % (cf.chrInt2Str(chr), start, stop, sampleID)
+		plt.savefig(args.outputdir + "/" + outfile)
+
+def CF_bam2RPKM(args):
+	try:
+		import pysam
+	except:
+		print '[ERROR] Cannot load pysam module! Make sure it is insalled'
+		sys.exit(0)
+	try: 
+		# read probes table
+		probe_fn = str(args.probes[0])
+		probes = cf.loadProbeList(probe_fn)
+		num_probes = len(probes)
+		print '[INIT] Successfully read in %d probes from %s' % (num_probes, probe_fn)
+	except IOError as e: 
+		print '[ERROR] Cannot read probes file: ', probe_fn
+		sys.exit(0)
+	
+	try:
+		rpkm_f = open(args.output[0],'w')
+	except IOError as e:
+		print '[ERROR] Cannot open rpkm file for writing: ', args.output
+		sys.exit(0)
+	
+	print "[RUNNING] Counting total number of reads in bam file..."
+	total_reads = float(pysam.view("-c", args.input[0])[0].strip("\n"))
+	print "[RUNNING] Found %d reads" % total_reads
+	
+	f = pysam.Samfile(args.input[0], "rb" )	
+	
+	# if not f._hasIndex():
+	if not f.has_index():
+		print "[ERROR] No index found for bam file (%s)!\n[ERROR] You must first index the bam file and include the .bai file in the same directory as the bam file!" % args.input[0]
+		sys.exit(0)
+    
+	# will be storing values in these arrays
+	readcount = np.zeros(num_probes)
+	exon_bp = np.zeros(num_probes)
+	probeIDs = np.zeros(num_probes)
+	counter = 0
+	
+	# detect contig naming scheme here # TODO, add an optional "contigs.txt" file or automatically handle contig naming
+	bam_contigs = f.references
+	probes_contigs = [str(p) for p in set(map(operator.itemgetter("chr"),probes))]
+	
+	probes2contigmap = {}
+	
+	for probes_contig in probes_contigs:
+		if probes_contig in bam_contigs:
+			probes2contigmap[probes_contig] = probes_contig
+		elif cf.chrInt2Str(probes_contig) in bam_contigs:
+			probes2contigmap[probes_contig] = cf.chrInt2Str(probes_contig)
+		elif cf.chrInt2Str(probes_contig).replace("chr","") in bam_contigs:
+			probes2contigmap[probes_contig] = cf.chrInt2Str(probes_contig).replace("chr","")
+		else:
+			print "[ERROR] Could not find contig '%s' from %s in bam file! \n[ERROR] Perhaps the contig names for the probes are incompatible with the bam file ('chr1' vs. '1'), or unsupported contig naming is used?" % (probes_contig, probe_fn)
+			sys.exit(0)
+	
+	print "[RUNNING] Calculating RPKM values..."
+	
+	# loop through each probe	
+	for p in probes:
+		
+		# f.fetch is a pysam method and returns an iterator for reads overlapping interval
+		
+		p_chr = probes2contigmap[str(p["chr"])]
+		
+		p_start = p["start"]
+		p_stop = p["stop"]
+		try:
+			iter = f.fetch(p_chr,p_start,p_stop)
+		except:
+			print "[ERROR] Could not retrieve mappings for region %s:%d-%d. Check that contigs are named correctly and the bam file is properly indexed" % (p_chr,p_start,p_stop)
+			sys.exit(0)
+		
+		for i in iter:
+			if i.pos+1 >= p_start: #this checks to make sure a read actually starts in an interval
+				readcount[counter] += 1
+		
+		exon_bp[counter] = p_stop-p_start
+		probeIDs[counter] = counter +1 #probeIDs are 1-based
+		counter +=1
+	
+	#calcualte RPKM values for all probes
+	rpkm = (10**9*(readcount)/(exon_bp))/(total_reads)
+	
+	out = np.vstack([probeIDs,readcount,rpkm])
+	
+	np.savetxt(rpkm_f,out.transpose(),delimiter='\t',fmt=['%d','%d','%f'])
+	
+	rpkm_f.close()
+
+	
+
+VERSION = "0.2.2"
+parser = argparse.ArgumentParser(prog="CoNIFER", description="This is CoNIFER %s (Copy Number Inference From Exome Reads), designed to detect and genotype CNVs and CNPs from exome sequence read-depth data. See Krumm et al., Genome Research (2012) doi:10.1101/gr.138115.112 \nNiklas Krumm, 2012\n nkrumm@uw.edu" % VERSION)
+parser.add_argument('--version', action='version', version='%(prog)s ' + VERSION)
+subparsers = parser.add_subparsers(help='Command to be run.')
+
+# rpkm command
+rpkm_parser= subparsers.add_parser('rpkm', help='Create an RPKM file from a BAM file')
+rpkm_parser.add_argument('--probes',action='store', required=True, metavar='/path/to/probes_file.txt',  nargs=1,help="Probe definition file")
+rpkm_parser.add_argument('--input',action='store', required=True, metavar='sample.bam',nargs=1,  help="Aligned BAM file")
+rpkm_parser.add_argument('--output',action='store', required=True, metavar='sample.rpkm.txt',nargs=1,  help="RPKM file to write")
+rpkm_parser.set_defaults(func=CF_bam2RPKM)
+
+# analyze command
+analyze_parser= subparsers.add_parser('analyze', help='Basic CoNIFER analysis. Reads a directory of RPKM files and a probe list and outputs a HDF5 file containing SVD-ZRPKM values.')
+analyze_parser.add_argument('--probes',action='store', required=True, metavar='/path/to/probes_file.txt',  nargs=1,help="Probe definition file")
+analyze_parser.add_argument('--rpkm_dir',action='store', required=True, metavar='/path/to/folder/containing/rpkm_files/',nargs=1,  help="Location of folder containing RPKM files. Folder should contain ONLY contain RPKM files, and all readable RPKM files will used in analysis.")
+analyze_parser.add_argument('--output','-o', required=True, metavar='/path/to/output_file.hdf5', type=str, help="Output location of HDF5 file to contain SVD-ZRPKM values")
+analyze_parser.add_argument('--svd', metavar='12', type=int, nargs='?', default = 12,help="Number of components to remove")
+analyze_parser.add_argument('--min_rpkm', metavar='1.00', type=float, nargs="?", default = 1.00,help="Minimum population median RPKM per probe.")
+analyze_parser.add_argument('--write_svals', metavar='SingularValues.txt', type=str, default= "", help="Optional file to write singular values (S-values). Used for Scree Plot.")
+analyze_parser.add_argument('--plot_scree', metavar='ScreePlot.png', type=str, default= "", help="Optional graphical scree plot. Requires matplotlib.")
+analyze_parser.add_argument('--write_sd', metavar='StandardDeviations.txt', type=str, default= "", help="Optional file with sample SVD-ZRPKM standard deviations. Used to filter noisy samples.")
+analyze_parser.set_defaults(func=CF_analyze)
+
+# export command
+export_parser= subparsers.add_parser('export', help='Export SVD-ZRPKM values from a HDF5 file to bed or vcf format.')
+export_parser.add_argument('--input','-i',action='store', required=True, metavar='CoNIFER_SVD.hdf5',help="HDF5 file from CoNIFER 'analyze' step")
+export_parser.add_argument('--output','-o',action='store', required=False, default='.', metavar='output.bed',help="Location of output file[s]. When exporting multiple samples, top-level directory of this path will be used.")
+export_parser.add_argument('--sample','-s',action='store', required=False, metavar='sampleID', default='all', nargs="+",help="SampleID or comma-separated list of sampleIDs to export. Default: export all samples")
+export_parser.set_defaults(func=CF_export)
+
+# plot command
+plot_parser= subparsers.add_parser('plot', help='Plot SVD-ZRPKM values using matplotlib')
+plot_parser.add_argument('--input','-i',action='store', required=True, metavar='CoNIFER_SVD.hdf5',help="HDF5 file from CoNIFER 'analyze' step")
+plot_parser.add_argument('--region',action='store', required=True, metavar='chr#:start-stop',help="Region to plot")
+plot_parser.add_argument('--output',action='store', required=True, metavar='image.png',help="Output path and filetype. PDF, PNG, PS, EPS, and SVG are supported.")
+plot_parser.add_argument('--sample',action='store', required=False, metavar='sampleID',nargs="+",default='none',help="Sample[s] to highlight. The following optional color spec can be used: <color>:<sampleID>. Available colors are r,b,g,y,c,m,y,k. The unsmoothed SVD-ZRPKM values for the first sample in this list will be drawn. Default: No samples highlighted.")
+plot_parser.set_defaults(func=CF_plot)
+
+# make calls command
+call_parser= subparsers.add_parser('call', help='Very rudimentary caller for CNVs using SVD-ZRPKM thresholding.')
+call_parser.add_argument('--input','-i',action='store', required=True, metavar='CoNIFER_SVD.hdf5',help="HDF5 file from CoNIFER 'analyze' step")
+call_parser.add_argument('--output',action='store', required=True, metavar='calls.txt',help="Output file for calls")
+call_parser.add_argument('--threshold', metavar='1.50', type=float, nargs='?', required=False, default = 1.50,help="+/- Threshold for calling (minimum SVD-ZRPKM)")
+call_parser.set_defaults(func=CF_call)
+
+# plotcalls command
+plotcalls_parser= subparsers.add_parser('plotcalls', help='Make basic plots from call file from "call" command.')
+plotcalls_parser.add_argument('--input','-i',action='store', required=True, metavar='CoNIFER_SVD.hdf5',help="HDF5 file from CoNIFER 'analyze' step")
+plotcalls_parser.add_argument('--calls',action='store', required=True, metavar='calls.txt',help="File with calls from 'call' command.")
+plotcalls_parser.add_argument('--outputdir',action='store', required=True, metavar='/path/to/directory',help="Output directory for plots")
+plotcalls_parser.add_argument('--window',action='store', required=False, metavar='50',default=50,help="In exons, the amount of padding to plot around each call")
+plotcalls_parser.set_defaults(func=CF_plotcalls)
+
+args = parser.parse_args()
+args.func(args)