def __main__():
#Parse Command Line
parser = optparse.OptionParser()
parser.add_option(
'-1',
'--input',
dest='input',
help=
' file of RNA-Seq read alignments in the SAM format. SAM is a standard short read alignment, that allows aligners to attach custom tags to individual alignments, and Cufflinks requires that the alignments you supply have some of these tags. Please see Input formats for more details.'
)
parser.add_option(
'-s',
'--inner-dist-std-dev',
dest='inner_dist_std_dev',
help=
'The standard deviation for the distribution on inner distances between mate pairs. The default is 20bp.'
)
parser.add_option(
'-I',
'--max-intron-length',
dest='max_intron_len',
help=
'The minimum intron length. Cufflinks will not report transcripts with introns longer than this, and will ignore SAM alignments with REF_SKIP CIGAR operations longer than this. The default is 300,000.'
)
parser.add_option(
'-F',
'--min-isoform-fraction',
dest='min_isoform_fraction',
help=
'After calculating isoform abundance for a gene, Cufflinks filters out transcripts that it believes are very low abundance, because isoforms expressed at extremely low levels often cannot reliably be assembled, and may even be artifacts of incompletely spliced precursors of processed transcripts. This parameter is also used to filter out introns that have far fewer spliced alignments supporting them. The default is 0.05, or 5% of the most abundant isoform (the major isoform) of the gene.'
)
parser.add_option(
'-j',
'--pre-mrna-fraction',
dest='pre_mrna_fraction',
help=
'Some RNA-Seq protocols produce a significant amount of reads that originate from incompletely spliced transcripts, and these reads can confound the assembly of fully spliced mRNAs. Cufflinks uses this parameter to filter out alignments that lie within the intronic intervals implied by the spliced alignments. The minimum depth of coverage in the intronic region covered by the alignment is divided by the number of spliced reads, and if the result is lower than this parameter value, the intronic alignments are ignored. The default is 5%.'
)
parser.add_option(
'-p',
'--num-threads',
dest='num_threads',
help='Use this many threads to align reads. The default is 1.')
parser.add_option(
'-m',
'--inner-mean-dist',
dest='inner_mean_dist',
help='This is the expected (mean) inner distance between mate pairs. \
For, example, for paired end runs with fragments selected at 300bp, \
where each end is 50bp, you should set -r to be 200. The default is 45bp.'
)
parser.add_option(
'-G',
'--GTF',
dest='GTF',
help=
'Tells Cufflinks to use the supplied reference annotation to estimate isoform expression. It will not assemble novel transcripts, and the program will ignore alignments not structurally compatible with any reference transcript.'
)
parser.add_option(
'-g',
'--GTF-guide',
dest='GTFguide',
help='use reference transcript annotation to guide assembly')
parser.add_option(
'-u',
'--multi-read-correct',
dest='multi_read_correct',
action="store_true",
help=
'Tells Cufflinks to do an initial estimation procedure to more accurately weight reads mapping to multiple locations in the genome'
)
# Normalization options.
parser.add_option("-N",
"--quartile-normalization",
dest="do_normalization",
action="store_true")
parser.add_option("--no-effective-length-correction",
dest="no_effective_length_correction",
action="store_true")
# Wrapper / Galaxy options.
parser.add_option('-A',
'--assembled-isoforms-output',
dest='assembled_isoforms_output_file',
help='Assembled isoforms output file; formate is GTF.')
# Advanced Options:
parser.add_option(
'--num-importance-samples',
dest='num_importance_samples',
help=
'Sets the number of importance samples generated for each locus during abundance estimation. Default: 1000'
)
parser.add_option(
'--max-mle-iterations',
dest='max_mle_iterations',
help=
'Sets the number of iterations allowed during maximum likelihood estimation of abundances. Default: 5000'
)
# Bias correction options.
parser.add_option(
'-b',
dest='do_bias_correction',
action="store_true",
help=
'Providing Cufflinks with a multifasta file via this option instructs it to run our new bias detection and correction algorithm which can significantly improve accuracy of transcript abundance estimates.'
)
parser.add_option('',
'--dbkey',
dest='dbkey',
help='The build of the reference dataset')
parser.add_option('',
'--index_dir',
dest='index_dir',
help='GALAXY_DATA_INDEX_DIR')
parser.add_option('',
'--ref_file',
dest='ref_file',
help='The reference dataset from the history')
# Global model.
parser.add_option('',
'--global_model',
dest='global_model_file',
help='Global model used for computing on local data')
(options, args) = parser.parse_args()
# output version # of tool
try:
tmp = tempfile.NamedTemporaryFile().name
tmp_stdout = open(tmp, 'wb')
proc = subprocess.Popen(args='cufflinks --no-update-check 2>&1',
shell=True,
stdout=tmp_stdout)
tmp_stdout.close()
returncode = proc.wait()
stdout = None
for line in open(tmp_stdout.name, 'rb'):
if line.lower().find('cufflinks v') >= 0:
stdout = line.strip()
break
if stdout:
sys.stdout.write('%s\n' % stdout)
else:
raise Exception
except:
sys.stdout.write('Could not determine Cufflinks version\n')
# If doing bias correction, set/link to sequence file.
if options.do_bias_correction:
if options.ref_file != 'None':
# Sequence data from history.
# Create symbolic link to ref_file so that index will be created in working directory.
seq_path = "ref.fa"
os.symlink(options.ref_file, seq_path)
else:
# Sequence data from loc file.
cached_seqs_pointer_file = os.path.join(options.index_dir,
'sam_fa_indices.loc')
if not os.path.exists(cached_seqs_pointer_file):
stop_err('The required file (%s) does not exist.' %
cached_seqs_pointer_file)
# If found for the dbkey, seq_path will look something like /galaxy/data/equCab2/sam_index/equCab2.fa,
# and the equCab2.fa file will contain fasta sequences.
seq_path = check_seq_file(options.dbkey, cached_seqs_pointer_file)
if seq_path == '':
stop_err(
'No sequence data found for dbkey %s, so bias correction cannot be used.'
% options.dbkey)
# Build command.
# Base; always use quiet mode to avoid problems with storing log output.
cmd = "cufflinks -q --no-update-check"
# Add options.
if options.inner_dist_std_dev:
cmd += (" -s %i" % int(options.inner_dist_std_dev))
if options.max_intron_len:
cmd += (" -I %i" % int(options.max_intron_len))
if options.min_isoform_fraction:
cmd += (" -F %f" % float(options.min_isoform_fraction))
if options.pre_mrna_fraction:
cmd += (" -j %f" % float(options.pre_mrna_fraction))
if options.num_threads:
cmd += (" -p %i" % int(options.num_threads))
if options.inner_mean_dist:
cmd += (" -m %i" % int(options.inner_mean_dist))
if options.GTF:
cmd += (" -G %s" % options.GTF)
if options.GTFguide:
cmd += (" -g %s" % options.GTFguide)
if options.multi_read_correct:
cmd += (" -u")
if options.num_importance_samples:
cmd += (" --num-importance-samples %i" %
int(options.num_importance_samples))
if options.max_mle_iterations:
cmd += (" --max-mle-iterations %i" % int(options.max_mle_iterations))
if options.do_normalization:
cmd += (" -N")
if options.do_bias_correction:
cmd += (" -b %s" % seq_path)
if options.no_effective_length_correction:
cmd += (" --no-effective-length-correction")
# Debugging.
print cmd
# Add input files.
cmd += " " + options.input
#
# Run command and handle output.
#
try:
#
# Run command.
#
tmp_name = tempfile.NamedTemporaryFile(dir=".").name
tmp_stderr = open(tmp_name, 'wb')
proc = subprocess.Popen(args=cmd,
shell=True,
stderr=tmp_stderr.fileno())
returncode = proc.wait()
tmp_stderr.close()
# Error checking.
if returncode != 0:
raise Exception, "return code = %i" % returncode
#
# Handle output.
#
# Read standard error to get total map/upper quartile mass.
total_map_mass = -1
tmp_stderr = open(tmp_name, 'r')
for line in tmp_stderr:
if line.lower().find("map mass") >= 0 or line.lower().find(
"upper quartile") >= 0:
total_map_mass = float(line.split(":")[1].strip())
break
tmp_stderr.close()
#
# If there's a global model provided, use model's total map mass
# to adjust FPKM + confidence intervals.
#
if options.global_model_file:
# Global model is simply total map mass from original run.
global_model_file = open(options.global_model_file, 'r')
global_model_total_map_mass = float(global_model_file.readline())
global_model_file.close()
# Ratio of global model's total map mass to original run's map mass is
# factor used to adjust FPKM.
fpkm_map_mass_ratio = total_map_mass / global_model_total_map_mass
# Update FPKM values in transcripts.gtf file.
transcripts_file = open("transcripts.gtf", 'r')
tmp_transcripts = tempfile.NamedTemporaryFile(dir=".").name
new_transcripts_file = open(tmp_transcripts, 'w')
for line in transcripts_file:
fields = line.split('\t')
attrs = parse_gff_attributes(fields[8])
attrs["FPKM"] = str(float(attrs["FPKM"]) * fpkm_map_mass_ratio)
attrs["conf_lo"] = str(
float(attrs["conf_lo"]) * fpkm_map_mass_ratio)
attrs["conf_hi"] = str(
float(attrs["conf_hi"]) * fpkm_map_mass_ratio)
fields[8] = gff_attributes_to_str(attrs, "GTF")
new_transcripts_file.write("%s\n" % '\t'.join(fields))
transcripts_file.close()
new_transcripts_file.close()
shutil.copyfile(tmp_transcripts, "transcripts.gtf")
# TODO: update expression files as well.
# Set outputs. Transcript and gene expression handled by wrapper directives.
shutil.copyfile("transcripts.gtf",
options.assembled_isoforms_output_file)
if total_map_mass > -1:
f = open("global_model.txt", 'w')
f.write("%f\n" % total_map_mass)
f.close()
except Exception, e:
# Read stderr so that it can be reported:
tmp_stderr = open(tmp_name, 'rb')
stderr = ''
buffsize = 1048576
try:
while True:
stderr += tmp_stderr.read(buffsize)
if not stderr or len(stderr) % buffsize != 0:
break
except OverflowError:
pass
tmp_stderr.close()
stop_err('Error running cufflinks.\n%s\n%s' % (str(e), stderr))
def __main__():
input_name = sys.argv[1]
output_name = sys.argv[2]
skipped_lines = 0
first_skipped_line = 0
out = open(output_name, "w")
i = 0
cur_transcript_chrome = None
cur_transcript_id = None
cur_transcript_strand = None
cur_transcripts_blocks = [] # (start, end) for each block.
for i, line in enumerate(open(input_name)):
line = line.rstrip("\r\n")
if line and not line.startswith("#"):
try:
# GFF format: chrom source, name, chromStart, chromEnd, score, strand, attributes
elems = line.split("\t")
start = str(long(elems[3]) - 1)
coords = [long(start), long(elems[4])]
strand = elems[6]
if strand not in ["+", "-"]:
strand = "+"
attributes = parse_gff_attributes(elems[8])
t_id = attributes.get("transcript_id", None)
if not t_id:
#
# No transcript ID, so write last transcript and write current line as its own line.
#
# Write previous transcript.
if cur_transcript_id:
# Write BED entry.
out.write(
get_bed_line(
cur_transcript_chrome, cur_transcript_id, cur_transcript_strand, cur_transcripts_blocks
)
)
# Replace any spaces in the name with underscores so UCSC will not complain.
name = elems[2].replace(" ", "_")
out.write(get_bed_line(elems[0], name, strand, [coords]))
continue
# There is a transcript ID, so process line at transcript level.
if t_id == cur_transcript_id:
# Line is element of transcript and will be a block in the BED entry.
cur_transcripts_blocks.append(coords)
continue
#
# Line is part of new transcript; write previous transcript and start
# new transcript.
#
# Write previous transcript.
if cur_transcript_id:
# Write BED entry.
out.write(
get_bed_line(
cur_transcript_chrome, cur_transcript_id, cur_transcript_strand, cur_transcripts_blocks
)
)
# Start new transcript.
cur_transcript_chrome = elems[0]
cur_transcript_id = t_id
cur_transcript_strand = strand
cur_transcripts_blocks = []
cur_transcripts_blocks.append(coords)
except:
skipped_lines += 1
if not first_skipped_line:
first_skipped_line = i + 1
else:
skipped_lines += 1
if not first_skipped_line:
first_skipped_line = i + 1
# Write last transcript.
if cur_transcript_id:
# Write BED entry.
out.write(get_bed_line(cur_transcript_chrome, cur_transcript_id, cur_transcript_strand, cur_transcripts_blocks))
out.close()
info_msg = "%i lines converted to BED. " % (i + 1 - skipped_lines)
if skipped_lines > 0:
info_msg += "Skipped %d blank/comment/invalid lines starting with line #%d." % (
skipped_lines,
first_skipped_line,
)
print info_msg
def __main__():
#Parse Command Line
parser = optparse.OptionParser()
parser.add_option( '-1', '--input', dest='input', help=' file of RNA-Seq read alignments in the SAM format. SAM is a standard short read alignment, that allows aligners to attach custom tags to individual alignments, and Cufflinks requires that the alignments you supply have some of these tags. Please see Input formats for more details.' )
parser.add_option( '-I', '--max-intron-length', dest='max_intron_len', help='The minimum intron length. Cufflinks will not report transcripts with introns longer than this, and will ignore SAM alignments with REF_SKIP CIGAR operations longer than this. The default is 300,000.' )
parser.add_option( '-F', '--min-isoform-fraction', dest='min_isoform_fraction', help='After calculating isoform abundance for a gene, Cufflinks filters out transcripts that it believes are very low abundance, because isoforms expressed at extremely low levels often cannot reliably be assembled, and may even be artifacts of incompletely spliced precursors of processed transcripts. This parameter is also used to filter out introns that have far fewer spliced alignments supporting them. The default is 0.05, or 5% of the most abundant isoform (the major isoform) of the gene.' )
parser.add_option( '-j', '--pre-mrna-fraction', dest='pre_mrna_fraction', help='Some RNA-Seq protocols produce a significant amount of reads that originate from incompletely spliced transcripts, and these reads can confound the assembly of fully spliced mRNAs. Cufflinks uses this parameter to filter out alignments that lie within the intronic intervals implied by the spliced alignments. The minimum depth of coverage in the intronic region covered by the alignment is divided by the number of spliced reads, and if the result is lower than this parameter value, the intronic alignments are ignored. The default is 5%.' )
parser.add_option( '-p', '--num-threads', dest='num_threads', help='Use this many threads to align reads. The default is 1.' )
parser.add_option( '-G', '--GTF', dest='GTF', help='Tells Cufflinks to use the supplied reference annotation to estimate isoform expression. It will not assemble novel transcripts, and the program will ignore alignments not structurally compatible with any reference transcript.' )
parser.add_option("--compatible-hits-norm", dest='compatible_hits_norm', action="store_true", help='Count hits compatible with reference RNAs only')
parser.add_option( '-g', '--GTF-guide', dest='GTFguide', help='use reference transcript annotation to guide assembly' )
parser.add_option("--3-overhang-tolerance", dest='three_overhang_tolerance', help='The number of bp allowed to overhang the 3prime end of a reference transcript when determining if an assembled transcript should be merged with it (ie, the assembled transcript is not novel). The default is 600 bp.')
parser.add_option("--intron-overhang-tolerance", dest='intron_overhang_tolerance', help='The number of bp allowed to enter the intron of a reference transcript when determining if an assembled transcript should be merged with it (ie, the assembled transcript is not novel). The default is 50 bp.')
parser.add_option("--no-faux-reads", dest='no_faux_reads', help='This option disables tiling of the reference transcripts with faux reads. Use this if you only want to use sequencing reads in assembly but do not want to output assembled transcripts that lay within reference transcripts. All reference transcripts in the input annotation will also be included in the output.')
parser.add_option( '-u', '--multi-read-correct', dest='multi_read_correct', action="store_true", help='Tells Cufflinks to do an initial estimation procedure to more accurately weight reads mapping to multiple locations in the genome')
# Normalization options.
parser.add_option( "--no-effective-length-correction", dest="no_effective_length_correction", action="store_true" )
parser.add_option( "--no-length-correction", dest="no_length_correction", action="store_true" )
# Wrapper / Galaxy options.
parser.add_option( '-A', '--assembled-isoforms-output', dest='assembled_isoforms_output_file', help='Assembled isoforms output file; formate is GTF.' )
# Advanced Options:
parser.add_option( "--library-type", dest="library_type", help=' library prep used for input reads, default fr-unstranded')
parser.add_option( '-M', '--mask-file', dest='mask_file', help='Tells Cufflinks to ignore all reads that could have come from transcripts in this GTF file. \
We recommend including any annotated rRNA, mitochondrial transcripts other abundant transcripts \
you wish to ignore in your analysis in this file. Due to variable efficiency of mRNA enrichment \
methods and rRNA depletion kits, masking these transcripts often improves the overall robustness \
of transcript abundance estimates.')
parser.add_option( '-m', '--inner-mean-dist', dest='inner_mean_dist', help='This is the expected (mean) inner distance between mate pairs. \
For, example, for paired end runs with fragments selected at 300bp, \
where each end is 50bp, you should set -r to be 200. The default is 45bp.') # cufflinks: --frag-len-mean
parser.add_option( '-s', '--inner-dist-std-dev', dest='inner_dist_std_dev', help='The standard deviation for the distribution on inner distances between mate pairs. The default is 20bp.' ) # cufflinks: --frag-len-std-dev
parser.add_option( '--max-mle-iterations', dest='max_mle_iterations', help='Sets the number of iterations allowed during maximum likelihood estimation of abundances. Default: 5000' )
parser.add_option( '--junc-alpha', dest='junc_alpha', help='Alpha value for the binomial test used during false positive spliced alignment filtration. Default: 0.001' )
parser.add_option( '--small-anchor-fraction', dest='small_anchor_fraction', help='Spliced reads with less than this percent of their length on each side of\
the junction are considered suspicious and are candidates for filtering prior to assembly. Default: 0.09.' )
parser.add_option( '--overhang-tolerance', dest='overhang_tolerance', help='The number of bp allowed to enter the intron of a transcript when determining if a \
read or another transcript is mappable to/compatible with it. The default is 8 bp based on the default bowtie/TopHat parameters.' )
parser.add_option( '--max-bundle-length', dest='max_bundle_length', help='Maximum genomic length of a given bundle" help="Default: 3,500,000bp' )
parser.add_option( '--max-bundle-frags', dest='max_bundle_frags', help='Sets the maximum number of fragments a locus may have before being skipped. Skipped loci are listed in skipped.gtf. Default: 1,000,000' )
parser.add_option( '--min-intron-length', dest='min_intron_length', help='Minimal allowed intron size. Default: 50' )
parser.add_option( '--trim-3-avgcov-thresh', dest='trim_three_avgcov_thresh', help='Minimum average coverage required to attempt 3prime trimming. Default: 10' )
parser.add_option( '--trim-3-dropoff-frac', dest='trim_three_dropoff_frac', help='The fraction of average coverage below which to trim the 3prime end of an assembled transcript. Default: 0.1' )
# Bias correction options.
parser.add_option( '-b', dest='do_bias_correction', action="store_true", help='Providing Cufflinks with a multifasta file via this option instructs it to run our new bias detection and correction algorithm which can significantly improve accuracy of transcript abundance estimates.')
parser.add_option( '', '--index', dest='index', help='The path of the reference genome' )
parser.add_option( '', '--ref_file', dest='ref_file', help='The reference dataset from the history' )
# Global model (for trackster).
parser.add_option( '', '--global_model', dest='global_model_file', help='Global model used for computing on local data' )
(options, args) = parser.parse_args()
# output version # of tool
try:
tmp = tempfile.NamedTemporaryFile().name
tmp_stdout = open( tmp, 'wb' )
proc = subprocess.Popen( args='cufflinks --no-update-check 2>&1', shell=True, stdout=tmp_stdout )
tmp_stdout.close()
returncode = proc.wait()
stdout = None
for line in open( tmp_stdout.name, 'rb' ):
if line.lower().find( 'cufflinks v' ) >= 0:
stdout = line.strip()
break
if stdout:
sys.stdout.write( '%s\n' % stdout )
else:
raise Exception
except:
sys.stdout.write( 'Could not determine Cufflinks version\n' )
# If doing bias correction, set/link to sequence file.
if options.do_bias_correction:
if options.ref_file:
# Sequence data from history.
# Create symbolic link to ref_file so that index will be created in working directory.
seq_path = "ref.fa"
os.symlink( options.ref_file, seq_path )
else:
if not os.path.exists( options.index ):
stop_err( 'Reference genome %s not present, request it by reporting this error.' % options.index )
seq_path = options.index
# Build command.
# Base; always use quiet mode to avoid problems with storing log output.
cmd = "cufflinks -q --no-update-check"
# Add options.
if options.max_intron_len:
cmd += ( " -I %i" % int( options.max_intron_len ) )
if options.min_isoform_fraction:
cmd += ( " -F %f" % float( options.min_isoform_fraction ) )
if options.pre_mrna_fraction:
cmd += ( " -j %f" % float( options.pre_mrna_fraction ) )
if options.num_threads:
cmd += ( " -p %i" % int( options.num_threads ) )
if options.GTF:
cmd += ( " -G %s" % options.GTF )
if options.compatible_hits_norm:
cmd += ( " --compatible-hits-norm" )
if options.GTFguide:
cmd += ( " -g %s" % options.GTFguide )
cmd += ( " --3-overhang-tolerance %i" % int( options.three_overhang_tolerance ) )
cmd += ( " --intron-overhang-tolerance %i" % int( options.intron_overhang_tolerance ) )
if options.no_faux_reads:
cmd += ( " --no-faux-reads" )
if options.multi_read_correct:
cmd += ( " -u" )
if options.library_type and options.library_type != 'auto':
cmd += ( " --library-type %s" % options.library_type)
if options.mask_file:
cmd += ( " --mask-file %s" % options.mask_file )
if options.inner_mean_dist:
cmd += ( " -m %i" % int( options.inner_mean_dist ) )
if options.inner_dist_std_dev:
cmd += ( " -s %i" % int( options.inner_dist_std_dev ) )
if options.max_mle_iterations:
cmd += ( " --max-mle-iterations %i" % int( options.max_mle_iterations ) )
if options.junc_alpha:
cmd += ( " --junc-alpha %f" % float( options.junc_alpha) )
if options.small_anchor_fraction:
cmd += ( " --small-anchor-fraction %f" % float(options.small_anchor_fraction ) )
if options.overhang_tolerance:
cmd += ( " --overhang-tolerance %i" % int( options.overhang_tolerance ) )
if options.max_bundle_length:
cmd += ( " --max-bundle-length %i" % int( options.max_bundle_length ) )
if options.max_bundle_frags:
cmd += ( " --max-bundle-frags %i" % int( options.max_bundle_frags ) )
if options.min_intron_length:
cmd += ( " --min-intron-length %i" % int( options.min_intron_length ) )
if options.trim_three_avgcov_thresh:
cmd += ( " --trim-3-avgcov-thresh %i" % int( options.trim_three_avgcov_thresh ) )
if options.trim_three_dropoff_frac:
cmd += ( " --trim-3-dropoff-frac %f" % float( options.trim_three_dropoff_frac ) )
if options.do_bias_correction:
cmd += ( " -b %s" % seq_path )
if options.no_effective_length_correction:
cmd += ( " --no-effective-length-correction" )
if options.no_length_correction:
cmd += ( " --no-length-correction" )
# Add input files.
cmd += " " + options.input
# Debugging.
print cmd
#
# Run command and handle output.
#
try:
#
# Run command.
#
tmp_name = tempfile.NamedTemporaryFile( dir="." ).name
tmp_stderr = open( tmp_name, 'wb' )
proc = subprocess.Popen( args=cmd, shell=True, stderr=tmp_stderr.fileno() )
returncode = proc.wait()
tmp_stderr.close()
# Error checking.
if returncode != 0:
raise Exception("return code = %i" % returncode)
#
# Handle output.
#
# Read standard error to get total map/upper quartile mass.
total_map_mass = -1
tmp_stderr = open( tmp_name, 'r' )
for line in tmp_stderr:
if line.lower().find( "map mass" ) >= 0 or line.lower().find( "upper quartile" ) >= 0:
total_map_mass = float( line.split(":")[1].strip() )
break
tmp_stderr.close()
#
# If there's a global model provided, use model's total map mass
# to adjust FPKM + confidence intervals.
#
if options.global_model_file:
# Global model is simply total map mass from original run.
global_model_file = open( options.global_model_file, 'r' )
global_model_total_map_mass = float( global_model_file.readline() )
global_model_file.close()
# Ratio of global model's total map mass to original run's map mass is
# factor used to adjust FPKM.
fpkm_map_mass_ratio = total_map_mass / global_model_total_map_mass
# Update FPKM values in transcripts.gtf file.
transcripts_file = open( "transcripts.gtf", 'r' )
tmp_transcripts = tempfile.NamedTemporaryFile( dir="." ).name
new_transcripts_file = open( tmp_transcripts, 'w' )
for line in transcripts_file:
fields = line.split( '\t' )
attrs = parse_gff_attributes( fields[8] )
attrs[ "FPKM" ] = str( float( attrs[ "FPKM" ] ) * fpkm_map_mass_ratio )
attrs[ "conf_lo" ] = str( float( attrs[ "conf_lo" ] ) * fpkm_map_mass_ratio )
attrs[ "conf_hi" ] = str( float( attrs[ "conf_hi" ] ) * fpkm_map_mass_ratio )
fields[8] = gff_attributes_to_str( attrs, "GTF" )
new_transcripts_file.write( "%s\n" % '\t'.join( fields ) )
transcripts_file.close()
new_transcripts_file.close()
shutil.copyfile( tmp_transcripts, "transcripts.gtf" )
# TODO: update expression files as well.
# Set outputs. Transcript and gene expression handled by wrapper directives.
shutil.copyfile( "transcripts.gtf", options.assembled_isoforms_output_file )
if total_map_mass > -1:
f = open( "global_model.txt", 'w' )
f.write( "%f\n" % total_map_mass )
f.close()
except Exception, e:
# Read stderr so that it can be reported:
tmp_stderr = open( tmp_name, 'rb' )
stderr = ''
buffsize = 1048576
try:
while True:
stderr += tmp_stderr.read( buffsize )
if not stderr or len( stderr ) % buffsize != 0:
break
except OverflowError:
pass
tmp_stderr.close()
stop_err( 'Error running cufflinks.\n%s\n%s' % ( str( e ), stderr ) )
def __main__():
#Parse Command Line
parser = optparse.OptionParser()
parser.add_option( '-1', '--input', dest='input', help=' file of RNA-Seq read alignments in the SAM format. SAM is a standard short read alignment, that allows aligners to attach custom tags to individual alignments, and Cufflinks requires that the alignments you supply have some of these tags. Please see Input formats for more details.' )
parser.add_option( '-s', '--inner-dist-std-dev', dest='inner_dist_std_dev', help='The standard deviation for the distribution on inner distances between mate pairs. The default is 20bp.' )
parser.add_option( '-I', '--max-intron-length', dest='max_intron_len', help='The minimum intron length. Cufflinks will not report transcripts with introns longer than this, and will ignore SAM alignments with REF_SKIP CIGAR operations longer than this. The default is 300,000.' )
parser.add_option( '-F', '--min-isoform-fraction', dest='min_isoform_fraction', help='After calculating isoform abundance for a gene, Cufflinks filters out transcripts that it believes are very low abundance, because isoforms expressed at extremely low levels often cannot reliably be assembled, and may even be artifacts of incompletely spliced precursors of processed transcripts. This parameter is also used to filter out introns that have far fewer spliced alignments supporting them. The default is 0.05, or 5% of the most abundant isoform (the major isoform) of the gene.' )
parser.add_option( '-j', '--pre-mrna-fraction', dest='pre_mrna_fraction', help='Some RNA-Seq protocols produce a significant amount of reads that originate from incompletely spliced transcripts, and these reads can confound the assembly of fully spliced mRNAs. Cufflinks uses this parameter to filter out alignments that lie within the intronic intervals implied by the spliced alignments. The minimum depth of coverage in the intronic region covered by the alignment is divided by the number of spliced reads, and if the result is lower than this parameter value, the intronic alignments are ignored. The default is 5%.' )
parser.add_option( '-p', '--num-threads', dest='num_threads', help='Use this many threads to align reads. The default is 1.' )
parser.add_option( '-m', '--inner-mean-dist', dest='inner_mean_dist', help='This is the expected (mean) inner distance between mate pairs. \
For, example, for paired end runs with fragments selected at 300bp, \
where each end is 50bp, you should set -r to be 200. The default is 45bp.')
parser.add_option( '-G', '--GTF', dest='GTF', help='Tells Cufflinks to use the supplied reference annotation to estimate isoform expression. It will not assemble novel transcripts, and the program will ignore alignments not structurally compatible with any reference transcript.' )
parser.add_option( '-g', '--GTF-guide', dest='GTFguide', help='use reference transcript annotation to guide assembly' )
parser.add_option( '-u', '--multi-read-correct', dest='multi_read_correct', action="store_true", help='Tells Cufflinks to do an initial estimation procedure to more accurately weight reads mapping to multiple locations in the genome')
# Normalization options.
parser.add_option( "-N", "--quartile-normalization", dest="do_normalization", action="store_true" )
# Wrapper / Galaxy options.
parser.add_option( '-A', '--assembled-isoforms-output', dest='assembled_isoforms_output_file', help='Assembled isoforms output file; formate is GTF.' )
# Advanced Options:
parser.add_option( '--num-importance-samples', dest='num_importance_samples', help='Sets the number of importance samples generated for each locus during abundance estimation. Default: 1000' )
parser.add_option( '--max-mle-iterations', dest='max_mle_iterations', help='Sets the number of iterations allowed during maximum likelihood estimation of abundances. Default: 5000' )
# Bias correction options.
parser.add_option( '-b', dest='do_bias_correction', action="store_true", help='Providing Cufflinks with a multifasta file via this option instructs it to run our new bias detection and correction algorithm which can significantly improve accuracy of transcript abundance estimates.')
parser.add_option( '', '--dbkey', dest='dbkey', help='The build of the reference dataset' )
parser.add_option( '', '--index_dir', dest='index_dir', help='GALAXY_DATA_INDEX_DIR' )
parser.add_option( '', '--ref_file', dest='ref_file', help='The reference dataset from the history' )
# Global model.
parser.add_option( '', '--global_model', dest='global_model_file', help='Global model used for computing on local data' )
(options, args) = parser.parse_args()
# output version # of tool
try:
tmp = tempfile.NamedTemporaryFile().name
tmp_stdout = open( tmp, 'wb' )
proc = subprocess.Popen( args='cufflinks --no-update-check 2>&1', shell=True, stdout=tmp_stdout )
tmp_stdout.close()
returncode = proc.wait()
stdout = None
for line in open( tmp_stdout.name, 'rb' ):
if line.lower().find( 'cufflinks v' ) >= 0:
stdout = line.strip()
break
if stdout:
sys.stdout.write( '%s\n' % stdout )
else:
raise Exception
except:
sys.stdout.write( 'Could not determine Cufflinks version\n' )
# If doing bias correction, set/link to sequence file.
if options.do_bias_correction:
if options.ref_file != 'None':
# Sequence data from history.
# Create symbolic link to ref_file so that index will be created in working directory.
seq_path = "ref.fa"
os.symlink( options.ref_file, seq_path )
else:
# Sequence data from loc file.
cached_seqs_pointer_file = os.path.join( options.index_dir, 'sam_fa_indices.loc' )
if not os.path.exists( cached_seqs_pointer_file ):
stop_err( 'The required file (%s) does not exist.' % cached_seqs_pointer_file )
# If found for the dbkey, seq_path will look something like /galaxy/data/equCab2/sam_index/equCab2.fa,
# and the equCab2.fa file will contain fasta sequences.
seq_path = check_seq_file( options.dbkey, cached_seqs_pointer_file )
if seq_path == '':
stop_err( 'No sequence data found for dbkey %s, so bias correction cannot be used.' % options.dbkey )
# Build command.
# Base; always use quiet mode to avoid problems with storing log output.
cmd = "cufflinks -q --no-update-check"
# Add options.
if options.inner_dist_std_dev:
cmd += ( " -s %i" % int ( options.inner_dist_std_dev ) )
if options.max_intron_len:
cmd += ( " -I %i" % int ( options.max_intron_len ) )
if options.min_isoform_fraction:
cmd += ( " -F %f" % float ( options.min_isoform_fraction ) )
if options.pre_mrna_fraction:
cmd += ( " -j %f" % float ( options.pre_mrna_fraction ) )
if options.num_threads:
cmd += ( " -p %i" % int ( options.num_threads ) )
if options.inner_mean_dist:
cmd += ( " -m %i" % int ( options.inner_mean_dist ) )
if options.GTF:
cmd += ( " -G %s" % options.GTF )
if options.GTFguide:
cmd += ( " -g %s" % options.GTFguide )
if options.multi_read_correct:
cmd += ( " -u" )
if options.num_importance_samples:
cmd += ( " --num-importance-samples %i" % int ( options.num_importance_samples ) )
if options.max_mle_iterations:
cmd += ( " --max-mle-iterations %i" % int ( options.max_mle_iterations ) )
if options.do_normalization:
cmd += ( " -N" )
if options.do_bias_correction:
cmd += ( " -b %s" % seq_path )
# Debugging.
print cmd
# Add input files.
cmd += " " + options.input
#
# Run command and handle output.
#
try:
#
# Run command.
#
tmp_name = tempfile.NamedTemporaryFile( dir="." ).name
tmp_stderr = open( tmp_name, 'wb' )
proc = subprocess.Popen( args=cmd, shell=True, stderr=tmp_stderr.fileno() )
returncode = proc.wait()
tmp_stderr.close()
# Error checking.
if returncode != 0:
raise Exception, "return code = %i" % returncode
#
# Handle output.
#
# Read standard error to get total map/upper quartile mass.
total_map_mass = -1
tmp_stderr = open( tmp_name, 'r' )
for line in tmp_stderr:
if line.lower().find( "map mass" ) >= 0 or line.lower().find( "upper quartile" ) >= 0:
total_map_mass = float( line.split(":")[1].strip() )
break
tmp_stderr.close()
#
# If there's a global model provided, use model's total map mass
# to adjust FPKM + confidence intervals.
#
if options.global_model_file:
# Global model is simply total map mass from original run.
global_model_file = open( options.global_model_file, 'r' )
global_model_total_map_mass = float( global_model_file.readline() )
global_model_file.close()
# Ratio of global model's total map mass to original run's map mass is
# factor used to adjust FPKM.
fpkm_map_mass_ratio = total_map_mass / global_model_total_map_mass
# Update FPKM values in transcripts.gtf file.
transcripts_file = open( "transcripts.gtf", 'r' )
tmp_transcripts = tempfile.NamedTemporaryFile( dir="." ).name
new_transcripts_file = open( tmp_transcripts, 'w' )
for line in transcripts_file:
fields = line.split( '\t' )
attrs = parse_gff_attributes( fields[8] )
attrs[ "FPKM" ] = str( float( attrs[ "FPKM" ] ) * fpkm_map_mass_ratio )
attrs[ "conf_lo" ] = str( float( attrs[ "conf_lo" ] ) * fpkm_map_mass_ratio )
attrs[ "conf_hi" ] = str( float( attrs[ "conf_hi" ] ) * fpkm_map_mass_ratio )
fields[8] = gff_attributes_to_str( attrs, "GTF" )
new_transcripts_file.write( "%s\n" % '\t'.join( fields ) )
transcripts_file.close()
new_transcripts_file.close()
shutil.copyfile( tmp_transcripts, "transcripts.gtf" )
# TODO: update expression files as well.
# Set outputs. Transcript and gene expression handled by wrapper directives.
shutil.copyfile( "transcripts.gtf" , options.assembled_isoforms_output_file )
if total_map_mass > -1:
f = open( "global_model.txt", 'w' )
f.write( "%f\n" % total_map_mass )
f.close()
except Exception, e:
# Read stderr so that it can be reported:
tmp_stderr = open( tmp_name, 'rb' )
stderr = ''
buffsize = 1048576
try:
while True:
stderr += tmp_stderr.read( buffsize )
if not stderr or len( stderr ) % buffsize != 0:
break
except OverflowError:
pass
tmp_stderr.close()
stop_err( 'Error running cufflinks.\n%s\n%s' % ( str( e ), stderr ) )
def __main__():
input_name = sys.argv[1]
output_name = sys.argv[2]
skipped_lines = 0
first_skipped_line = 0
out = open(output_name, 'w')
i = 0
cur_transcript_chrome = None
cur_transcript_id = None
cur_transcript_strand = None
cur_transcripts_blocks = [] # (start, end) for each block.
for i, line in enumerate(open(input_name)):
line = line.rstrip('\r\n')
if line and not line.startswith('#'):
try:
# GFF format: chrom source, name, chromStart, chromEnd, score, strand, attributes
elems = line.split('\t')
start = str(int(elems[3]) - 1)
coords = [int(start), int(elems[4])]
strand = elems[6]
if strand not in ['+', '-']:
strand = '+'
attributes = parse_gff_attributes(elems[8])
t_id = attributes.get("transcript_id", None)
if not t_id:
#
# No transcript ID, so write last transcript and write current line as its own line.
#
# Write previous transcript.
if cur_transcript_id:
# Write BED entry.
out.write(
get_bed_line(cur_transcript_chrome,
cur_transcript_id,
cur_transcript_strand,
cur_transcripts_blocks))
# Replace any spaces in the name with underscores so UCSC will not complain.
name = elems[2].replace(" ", "_")
out.write(get_bed_line(elems[0], name, strand, [coords]))
continue
# There is a transcript ID, so process line at transcript level.
if t_id == cur_transcript_id:
# Line is element of transcript and will be a block in the BED entry.
cur_transcripts_blocks.append(coords)
continue
#
# Line is part of new transcript; write previous transcript and start
# new transcript.
#
# Write previous transcript.
if cur_transcript_id:
# Write BED entry.
out.write(
get_bed_line(cur_transcript_chrome, cur_transcript_id,
cur_transcript_strand,
cur_transcripts_blocks))
# Start new transcript.
cur_transcript_chrome = elems[0]
cur_transcript_id = t_id
cur_transcript_strand = strand
cur_transcripts_blocks = []
cur_transcripts_blocks.append(coords)
except:
skipped_lines += 1
if not first_skipped_line:
first_skipped_line = i + 1
else:
skipped_lines += 1
if not first_skipped_line:
first_skipped_line = i + 1
# Write last transcript.
if cur_transcript_id:
# Write BED entry.
out.write(
get_bed_line(cur_transcript_chrome, cur_transcript_id,
cur_transcript_strand, cur_transcripts_blocks))
out.close()
info_msg = "%i lines converted to BED. " % (i + 1 - skipped_lines)
if skipped_lines > 0:
info_msg += "Skipped %d blank/comment/invalid lines starting with line #%d." % (
skipped_lines, first_skipped_line)
print(info_msg)
def __main__():
#Parse Command Line
parser = optparse.OptionParser()
parser.add_option(
'-1',
'--input',
dest='input',
help=
' file of RNA-Seq read alignments in the SAM format. SAM is a standard short read alignment, that allows aligners to attach custom tags to individual alignments, and Cufflinks requires that the alignments you supply have some of these tags. Please see Input formats for more details.'
)
parser.add_option(
'-I',
'--max-intron-length',
dest='max_intron_len',
help=
'The minimum intron length. Cufflinks will not report transcripts with introns longer than this, and will ignore SAM alignments with REF_SKIP CIGAR operations longer than this. The default is 300,000.'
)
parser.add_option(
'-F',
'--min-isoform-fraction',
dest='min_isoform_fraction',
help=
'After calculating isoform abundance for a gene, Cufflinks filters out transcripts that it believes are very low abundance, because isoforms expressed at extremely low levels often cannot reliably be assembled, and may even be artifacts of incompletely spliced precursors of processed transcripts. This parameter is also used to filter out introns that have far fewer spliced alignments supporting them. The default is 0.05, or 5% of the most abundant isoform (the major isoform) of the gene.'
)
parser.add_option(
'-j',
'--pre-mrna-fraction',
dest='pre_mrna_fraction',
help=
'Some RNA-Seq protocols produce a significant amount of reads that originate from incompletely spliced transcripts, and these reads can confound the assembly of fully spliced mRNAs. Cufflinks uses this parameter to filter out alignments that lie within the intronic intervals implied by the spliced alignments. The minimum depth of coverage in the intronic region covered by the alignment is divided by the number of spliced reads, and if the result is lower than this parameter value, the intronic alignments are ignored. The default is 5%.'
)
parser.add_option(
'-p',
'--num-threads',
dest='num_threads',
help='Use this many threads to align reads. The default is 1.')
parser.add_option(
'-G',
'--GTF',
dest='GTF',
help=
'Tells Cufflinks to use the supplied reference annotation to estimate isoform expression. It will not assemble novel transcripts, and the program will ignore alignments not structurally compatible with any reference transcript.'
)
parser.add_option("--compatible-hits-norm",
dest='compatible_hits_norm',
help='Count hits compatible with reference RNAs only')
parser.add_option(
'-g',
'--GTF-guide',
dest='GTFguide',
help='use reference transcript annotation to guide assembly')
parser.add_option(
"--3-overhang-tolerance",
dest='three_overhang_tolerance',
help=
'The number of bp allowed to overhang the 3prime end of a reference transcript when determining if an assembled transcript should be merged with it (ie, the assembled transcript is not novel). The default is 600 bp.'
)
parser.add_option(
"--intron-overhang-tolerance",
dest='intron_overhang_tolerance',
help=
'The number of bp allowed to enter the intron of a reference transcript when determining if an assembled transcript should be merged with it (ie, the assembled transcript is not novel). The default is 50 bp.'
)
parser.add_option(
"--no-faux-reads",
dest='no_faux_reads',
help=
'This option disables tiling of the reference transcripts with faux reads. Use this if you only want to use sequencing reads in assembly but do not want to output assembled transcripts that lay within reference transcripts. All reference transcripts in the input annotation will also be included in the output.'
)
parser.add_option(
'-u',
'--multi-read-correct',
dest='multi_read_correct',
action="store_true",
help=
'Tells Cufflinks to do an initial estimation procedure to more accurately weight reads mapping to multiple locations in the genome'
)
# Normalization options.
parser.add_option("--no-effective-length-correction",
dest="no_effective_length_correction",
action="store_true")
parser.add_option("--no-length-correction",
dest="no_length_correction",
action="store_true")
# Wrapper / Galaxy options.
parser.add_option('-A',
'--assembled-isoforms-output',
dest='assembled_isoforms_output_file',
help='Assembled isoforms output file; formate is GTF.')
# Advanced Options:
parser.add_option(
"--library-type",
dest="library_type",
help=' library prep used for input reads, default fr-unstranded')
parser.add_option(
'-M',
'--mask-file',
dest='mask_file',
help=
'Tells Cufflinks to ignore all reads that could have come from transcripts in this GTF file. \
We recommend including any annotated rRNA, mitochondrial transcripts other abundant transcripts \
you wish to ignore in your analysis in this file. Due to variable efficiency of mRNA enrichment \
methods and rRNA depletion kits, masking these transcripts often improves the overall robustness \
of transcript abundance estimates.'
)
parser.add_option(
'-m',
'--inner-mean-dist',
dest='inner_mean_dist',
help='This is the expected (mean) inner distance between mate pairs. \
For, example, for paired end runs with fragments selected at 300bp, \
where each end is 50bp, you should set -r to be 200. The default is 45bp.'
) # cufflinks: --frag-len-mean
parser.add_option(
'-s',
'--inner-dist-std-dev',
dest='inner_dist_std_dev',
help=
'The standard deviation for the distribution on inner distances between mate pairs. The default is 20bp.'
) # cufflinks: --frag-len-std-dev
parser.add_option(
'--max-mle-iterations',
dest='max_mle_iterations',
help=
'Sets the number of iterations allowed during maximum likelihood estimation of abundances. Default: 5000'
)
parser.add_option(
'--junc-alpha',
dest='junc_alpha',
help=
'Alpha value for the binomial test used during false positive spliced alignment filtration. Default: 0.001'
)
parser.add_option(
'--small-anchor-fraction',
dest='small_anchor_fraction',
help=
'Spliced reads with less than this percent of their length on each side of\
the junction are considered suspicious and are candidates for filtering prior to assembly. Default: 0.09.'
)
parser.add_option(
'--overhang-tolerance',
dest='overhang_tolerance',
help=
'The number of bp allowed to enter the intron of a transcript when determining if a \
read or another transcript is mappable to/compatible with it. The default is 8 bp based on the default bowtie/TopHat parameters.'
)
parser.add_option(
'--max-bundle-length',
dest='max_bundle_length',
help=
'Maximum genomic length of a given bundle" help="Default: 3,500,000bp')
parser.add_option(
'--max-bundle-frags',
dest='max_bundle_frags',
help=
'Sets the maximum number of fragments a locus may have before being skipped. Skipped loci are listed in skipped.gtf. Default: 1,000,000'
)
parser.add_option('--min-intron-length',
dest='min_intron_length',
help='Minimal allowed intron size. Default: 50')
parser.add_option(
'--trim-3-avgcov-thresh',
dest='trim_three_avgcov_thresh',
help=
'Minimum average coverage required to attempt 3prime trimming. Default: 10'
)
parser.add_option(
'--trim-3-dropoff-frac',
dest='trim_three_dropoff_frac',
help=
'The fraction of average coverage below which to trim the 3prime end of an assembled transcript. Default: 0.1'
)
# Bias correction options.
parser.add_option(
'-b',
dest='do_bias_correction',
action="store_true",
help=
'Providing Cufflinks with a multifasta file via this option instructs it to run our new bias detection and correction algorithm which can significantly improve accuracy of transcript abundance estimates.'
)
parser.add_option('',
'--index',
dest='index',
help='The path of the reference genome')
parser.add_option('',
'--ref_file',
dest='ref_file',
help='The reference dataset from the history')
# Global model (for trackster).
parser.add_option('',
'--global_model',
dest='global_model_file',
help='Global model used for computing on local data')
(options, args) = parser.parse_args()
# output version # of tool
try:
tmp = tempfile.NamedTemporaryFile().name
tmp_stdout = open(tmp, 'wb')
proc = subprocess.Popen(args='cufflinks --no-update-check 2>&1',
shell=True,
stdout=tmp_stdout)
tmp_stdout.close()
returncode = proc.wait()
stdout = None
for line in open(tmp_stdout.name, 'rb'):
if line.lower().find('cufflinks v') >= 0:
stdout = line.strip()
break
if stdout:
sys.stdout.write('%s\n' % stdout)
else:
raise Exception
except:
sys.stdout.write('Could not determine Cufflinks version\n')
# If doing bias correction, set/link to sequence file.
if options.do_bias_correction:
if options.ref_file:
# Sequence data from history.
# Create symbolic link to ref_file so that index will be created in working directory.
seq_path = "ref.fa"
os.symlink(options.ref_file, seq_path)
else:
if not os.path.exists(options.index):
stop_err(
'Reference genome %s not present, request it by reporting this error.'
% options.index)
seq_path = options.index
# Build command.
# Base; always use quiet mode to avoid problems with storing log output.
cmd = "cufflinks -q --no-update-check"
# Add options.
if options.max_intron_len:
cmd += (" -I %i" % int(options.max_intron_len))
if options.min_isoform_fraction:
cmd += (" -F %f" % float(options.min_isoform_fraction))
if options.pre_mrna_fraction:
cmd += (" -j %f" % float(options.pre_mrna_fraction))
if options.num_threads:
cmd += (" -p %i" % int(options.num_threads))
if options.GTF:
cmd += (" -G %s" % options.GTF)
if options.compatible_hits_norm:
cmd += (" --compatible-hits-norm")
if options.GTFguide:
cmd += (" -g %s" % options.GTFguide)
cmd += (" --3-overhang-tolerance %i" %
int(options.three_overhang_tolerance))
cmd += (" --intron-overhang-tolerance %i" %
int(options.intron_overhang_tolerance))
if options.no_faux_reads:
cmd += (" --no-faux-reads")
if options.multi_read_correct:
cmd += (" -u")
if options.library_type and options.library_type != 'auto':
cmd += (" --library-type %s" % options.library_type)
if options.mask_file:
cmd += (" --mask-file %s" % options.mask_file)
if options.inner_mean_dist:
cmd += (" -m %i" % int(options.inner_mean_dist))
if options.inner_dist_std_dev:
cmd += (" -s %i" % int(options.inner_dist_std_dev))
if options.max_mle_iterations:
cmd += (" --max-mle-iterations %i" % int(options.max_mle_iterations))
if options.junc_alpha:
cmd += (" --junc-alpha %f" % float(options.junc_alpha))
if options.small_anchor_fraction:
cmd += (" --small-anchor-fraction %f" %
float(options.small_anchor_fraction))
if options.overhang_tolerance:
cmd += (" --overhang-tolerance %i" % int(options.overhang_tolerance))
if options.max_bundle_length:
cmd += (" --max-bundle-length %i" % int(options.max_bundle_length))
if options.max_bundle_frags:
cmd += (" --max-bundle-frags %i" % int(options.max_bundle_frags))
if options.min_intron_length:
cmd += (" --min-intron-length %i" % int(options.min_intron_length))
if options.trim_three_avgcov_thresh:
cmd += (" --trim-3-avgcov-thresh %i" %
int(options.trim_three_avgcov_thresh))
if options.trim_three_dropoff_frac:
cmd += (" --trim-3-dropoff-frac %f" %
float(options.trim_three_dropoff_frac))
if options.do_bias_correction:
cmd += (" -b %s" % seq_path)
if options.no_effective_length_correction:
cmd += (" --no-effective-length-correction")
if options.no_length_correction:
cmd += (" --no-length-correction")
# Add input files.
cmd += " " + options.input
# Debugging.
print cmd
#
# Run command and handle output.
#
try:
#
# Run command.
#
tmp_name = tempfile.NamedTemporaryFile(dir=".").name
tmp_stderr = open(tmp_name, 'wb')
proc = subprocess.Popen(args=cmd,
shell=True,
stderr=tmp_stderr.fileno())
returncode = proc.wait()
tmp_stderr.close()
# Error checking.
if returncode != 0:
raise Exception, "return code = %i" % returncode
#
# Handle output.
#
# Read standard error to get total map/upper quartile mass.
total_map_mass = -1
tmp_stderr = open(tmp_name, 'r')
for line in tmp_stderr:
if line.lower().find("map mass") >= 0 or line.lower().find(
"upper quartile") >= 0:
total_map_mass = float(line.split(":")[1].strip())
break
tmp_stderr.close()
#
# If there's a global model provided, use model's total map mass
# to adjust FPKM + confidence intervals.
#
if options.global_model_file:
# Global model is simply total map mass from original run.
global_model_file = open(options.global_model_file, 'r')
global_model_total_map_mass = float(global_model_file.readline())
global_model_file.close()
# Ratio of global model's total map mass to original run's map mass is
# factor used to adjust FPKM.
fpkm_map_mass_ratio = total_map_mass / global_model_total_map_mass
# Update FPKM values in transcripts.gtf file.
transcripts_file = open("transcripts.gtf", 'r')
tmp_transcripts = tempfile.NamedTemporaryFile(dir=".").name
new_transcripts_file = open(tmp_transcripts, 'w')
for line in transcripts_file:
fields = line.split('\t')
attrs = parse_gff_attributes(fields[8])
attrs["FPKM"] = str(float(attrs["FPKM"]) * fpkm_map_mass_ratio)
attrs["conf_lo"] = str(
float(attrs["conf_lo"]) * fpkm_map_mass_ratio)
attrs["conf_hi"] = str(
float(attrs["conf_hi"]) * fpkm_map_mass_ratio)
fields[8] = gff_attributes_to_str(attrs, "GTF")
new_transcripts_file.write("%s\n" % '\t'.join(fields))
transcripts_file.close()
new_transcripts_file.close()
shutil.copyfile(tmp_transcripts, "transcripts.gtf")
# TODO: update expression files as well.
# Set outputs. Transcript and gene expression handled by wrapper directives.
shutil.copyfile("transcripts.gtf",
options.assembled_isoforms_output_file)
if total_map_mass > -1:
f = open("global_model.txt", 'w')
f.write("%f\n" % total_map_mass)
f.close()
except Exception, e:
# Read stderr so that it can be reported:
tmp_stderr = open(tmp_name, 'rb')
stderr = ''
buffsize = 1048576
try:
while True:
stderr += tmp_stderr.read(buffsize)
if not stderr or len(stderr) % buffsize != 0:
break
except OverflowError:
pass
tmp_stderr.close()
stop_err('Error running cufflinks.\n%s\n%s' % (str(e), stderr))
