def plot_density(pickle_filename, bam_filename):
print "Plotting density along alternative isoform"
print " - pickle: %s" %(pickle_filename)
print " - BAM: %s" %(bam_filename)
gff_genes = gff_utils.load_indexed_gff_file(pickle_filename)
#bamfile = pysam.Samfile(bam_filename, "rb")
plot_gene(gff_genes)
plt.show()
print "gff_genes: ", gff_genes
def main():
from optparse import OptionParser
parser = OptionParser()
##
## Two isoform Psi
##
parser.add_option("--compute-two-iso-psi", dest="two_iso_psi_files", nargs=2, default=None,
help="Compute Psi using MISO for a given set of two-isoform events. "
"Expects two arguments: the first is the set of events (in JSON/Pickle format), "
"the second is an output directory where estimated Psi values will "
"be outputted.")
##
## Multiple isoform Psi
##
# parser.add_option("--compute-multi-iso-psi", dest="multi_iso_psi_files", nargs=3, default=None,
# help="Compute Psi using for a given multi-isoform gene. Expects three arguments: "
# "the first is a file with the isoform lengths. The second is a file with the reads "
# "aligned to the isoform. The third is an output directory.")
parser.add_option("--compute-gene-psi", dest="compute_gene_psi", nargs=4, default=None,
help="Compute Psi using for a given multi-isoform gene. Expects four arguments: "
"the first is a gene ID or set of comma-separated (no spaces) gene IDs, "
"the second is a GFF indexed file with the gene information, the third is a sorted and "
"indexed BAM file with reads aligned to the gene, and the fourth is an output directory.")
parser.add_option("--paired-end", dest="paired_end", nargs=2, default=None,
help="Run in paired-end mode. Takes a mean and standard deviation "
"for the fragment length distribution (assumed to have discretized "
"normal form.)")
##
## Psi utilities
##
parser.add_option("--compare-samples", dest="samples_to_compare", nargs=3, default=None,
help="Compute comparison statistics between the two given samples. "
"Expects three directories: the first is sample1's MISO output, "
"the second is sample2's MISO output, and the third is the directory where "
"results of the sample comparison will be outputted.")
parser.add_option("--run-two-iso-event", dest="run_two_iso_event", nargs=3, default=None,
help="Run MISO on two isoform event, given an event name, an events file "
"(in JSON/Pickle format) and an output directory.")
parser.add_option("--summarize-samples", dest="summarize_samples", nargs=2, default=None,
help="Compute summary statistics of the given set of samples. "
"Expects a directory with MISO output and a directory to output "
"summary file to.")
parser.add_option("--summarize-multi-iso-samples", dest="summarize_samples", nargs=2, default=None,
help="Compute summary statistics of the given set of samples from multi-isoform runs. "
"Expects a directory with MISO output and a directory to output summary file to.")
parser.add_option("--pool-comparisons", dest="pool_comparisons", nargs=2, default=None,
help="Pool comparisons files into a single file. Expects a comparisons directory "
"generated by MISO and an output directory, and event type provided with --event-type.")
parser.add_option("--use-cluster", action="store_true", dest="use_cluster", default=False)
parser.add_option("--chunk-jobs", dest="chunk_jobs", default=False, type="int",
help="Size (in number of events) of each job to chunk events file into. "
"Only applies when running on cluster.")
parser.add_option("--settings-filename", dest="settings_filename",
default=os.path.join(miso_path, "settings", "miso_settings.txt"),
help="Filename specifying MISO settings.")
parser.add_option("--read-len", dest="read_len", type="int", default=None)
parser.add_option("--overhang-len", dest="overhang_len", type="int", default=None)
parser.add_option("--event-type", dest="event_type", default=None,
help="Event type of two-isoform events (e.g. 'SE', 'RI', 'A3SS', ...)")
##
## Gene utilities
##
parser.add_option("--view-gene", dest="view_gene", nargs=1, default=None,
help="View the contents of a gene/event that has been indexed. "\
"Takes as input an indexed (.pickle) filename.")
(options, args) = parser.parse_args()
##
## Load the settings file
##
Settings.load(os.path.expanduser(options.settings_filename))
if options.pool_comparisons != None:
if options.event_type == None:
print "Error: Must provide --event-type to pool comparisons"
sys.exit(1)
comparison_dir = os.path.abspath(os.path.expanduser(options.pool_comparisons[0]))
output_dir = os.path.abspath(os.path.expanduser(options.pool_comparisons[1]))
pool_comparisons(comparison_dir, options.event_type, output_dir)
if options.samples_to_compare:
sample1_dirname = os.path.abspath(options.samples_to_compare[0])
sample2_dirname = os.path.abspath(options.samples_to_compare[1])
output_dirname = os.path.abspath(options.samples_to_compare[2])
if not os.path.isdir(output_dirname):
print "Making comparisons directory: %s" %(output_dirname)
os.makedirs(output_dirname)
ht.output_samples_comparison(sample1_dirname, sample2_dirname,
output_dirname)
if options.run_two_iso_event:
if options.read_len == None or options.overhang_len == None:
print "Error: must provide --read-len and --overhang-len to run."
sys.exit(1)
if options.use_cluster:
print "Use cluster option not supported for running on a single event."
sys.exit(1)
# convert paths to absolute path names
event_name = options.run_two_iso_event[0]
events_filename = os.path.abspath(options.run_two_iso_event[1])
psi_outdir = os.path.abspath(os.path.expanduser(options.run_two_iso_event[2])) + '/'
miso_events = as_events.MISOEvents(2, options.event_type,
from_file=events_filename)
run_two_iso_event(event_name, options.event_type, miso_events, psi_outdir,
options.read_len, options.overhang_len)
# if options.inspect_events:
# print "Loading events from: %s" %(options.inspect_events)
# miso_events = as_events.MISOEvents(2, options.event_type, from_file=options.inspect_events)
# print " - Total of %d events." %(len(miso_events.events))
if options.two_iso_psi_files:
if options.read_len == None or options.overhang_len == None:
print "Error: must provide --read-len and --overhang-len to run."
sys.exit(1)
# convert paths to absolute path names
events_filename = os.path.abspath(options.two_iso_psi_files[0])
psi_outdir = os.path.abspath(options.two_iso_psi_files[1]) + '/'
if options.use_cluster:
run_two_iso_on_cluster(miso_path, events_filename, options.event_type, psi_outdir,
options.read_len, options.overhang_len,
chunk_jobs=options.chunk_jobs)
else:
if options.chunk_jobs:
print "Error: Chunking jobs only applies when using the --use-cluster option " \
"to run MISO on cluster."
sys.exit(1)
compute_two_iso_psi(events_filename, options.event_type, psi_outdir,
options.read_len, options.overhang_len)
##
## Multiple isoforms interface based on SAM files
##
if options.compute_gene_psi != None:
if options.read_len == None:
print "Error: must provide --read-len."
sys.exit(1)
paired_end = None
if options.paired_end != None:
paired_end = float(options.paired_end[0]), \
float(options.paired_end[1])
overhang_len = 1
if options.overhang_len != None:
overhang_len = options.overhang_len
# Genes to run on from GFF
gene_ids = options.compute_gene_psi[0].split(",")
# GFF filename describing genes
gff_filename = os.path.abspath(os.path.expanduser(options.compute_gene_psi[1]))
# BAM filename with reads
bam_filename = os.path.abspath(os.path.expanduser(options.compute_gene_psi[2]))
# Output directory
output_dir = os.path.abspath(os.path.expanduser(options.compute_gene_psi[3]))
compute_gene_psi(gene_ids, gff_filename, bam_filename, output_dir,
options.read_len, overhang_len, paired_end=paired_end,
event_type=options.event_type)
##
## Summarizing samples
##
if options.summarize_samples:
samples_dir = os.path.abspath(os.path.expanduser(options.summarize_samples[0]))
samples_label = os.path.basename(os.path.expanduser(samples_dir))
assert(len(samples_label) >= 1)
summary_output_dir = os.path.abspath(os.path.join(os.path.expanduser(options.summarize_samples[1]),
'summary'))
if not os.path.isdir(summary_output_dir):
os.makedirs(summary_output_dir)
summary_filename = os.path.join(summary_output_dir,
'%s.miso_summary' %(samples_label))
summarize_sampler_results(samples_dir, summary_filename)
if options.view_gene != None:
indexed_gene_filename = os.path.abspath(os.path.expanduser(options.view_gene))
print "Viewing genes in %s" %(indexed_gene_filename)
gff_genes = gff_utils.load_indexed_gff_file(indexed_gene_filename)
if gff_genes == None:
print "No genes."
return
for gene_id, gene_info in gff_genes.iteritems():
print "Gene %s" %(gene_id)
gene_obj = gene_info['gene_object']
print " - Gene object: ", gene_obj
print "=="
print "Isoforms: "
for isoform in gene_obj.isoforms:
print " - ", isoform
print "=="
print "Exons: "
for exon in gene_obj.parts:
print " - ", exon
def compute_gene_psi(gene_ids, gff_index_filename, bam_filename, output_dir,
read_len, overhang_len, paired_end=None, event_type=None):
"""
Run Psi at the Gene-level (for multi-isoform inference.)
Arguments:
- Set of gene IDs corresponding to gene IDs from the GFF
- Indexed GFF filename describing the genes
- BAM filename with the reads (must be sorted and indexed)
- Output directory
- Optional: Run in paired-end mode. Gives mean and standard deviation
of fragment length distribution.
"""
if not os.path.isdir(output_dir):
os.makedirs(output_dir)
if not os.path.exists(gff_index_filename):
print "Error: no such GFF file as %s" %(gff_index_filename)
return
num_genes = len(gene_ids)
print "Computing Psi for %d genes..." %(num_genes)
print " - " + ", ".join(gene_ids)
print " - GFF filename: %s" %(gff_index_filename)
print " - BAM: %s" %(bam_filename)
print " - Outputting to: %s" %(output_dir)
if paired_end:
print " - Paired-end mode: ", paired_end
settings = Settings.get()
settings_params = Settings.get_sampler_params()
burn_in = settings_params["burn_in"]
lag = settings_params["lag"]
num_iters = settings_params["num_iters"]
min_event_reads = Settings.get_min_event_reads()
if paired_end:
mean_frag_len = int(paired_end[0])
frag_variance = power(int(paired_end[1]), 2)
# Load the genes from the GFF
# print "Loading genes from indexed GFF..."
# t1 = time.time()
gff_genes = gff_utils.load_indexed_gff_file(gff_index_filename)
# t2 = time.time()
# print " - Loading took: %.2f seconds" %(t2 - t1)
for gene_id, gene_info in gff_genes.iteritems():
if gene_id not in gene_ids:
# Skip genes that we were not asked to run on
continue
gene_obj = gene_info['gene_object']
gene_hierarchy = gene_info['hierarchy']
# Find the most inclusive transcription start and end sites for each gene
tx_start, tx_end = gff_utils.get_inclusive_txn_bounds(gene_info['hierarchy'][gene_id])
# If given a template for the SAM file, use it
template = None
if settings and "sam_template" in settings:
template = settings["sam_template"]
# Load the BAM file
bamfile = sam_utils.load_bam_reads(bam_filename, template=template)
# Fetch reads aligning to the gene boundaries
gene_reads = sam_utils.fetch_bam_reads_in_gene(bamfile, gene_obj.chrom,
tx_start, tx_end,
gene_obj)
# Align the reads to the isoforms
reads = sam_utils.sam_reads_to_isoforms(gene_reads, gene_obj, read_len,
overhang_len,
paired_end=paired_end)
num_raw_reads = len(reads)
# Skip gene if none of the reads align to gene boundaries
if num_raw_reads < min_event_reads:
print "Only %d reads in gene, skipping (needed >= %d reads)" \
%(num_raw_reads, min_event_reads)
continue
reads = array(reads)
num_isoforms = len(gene_obj.isoforms)
hyperparameters = ones(num_isoforms)
##
## Run the sampler
##
# Create the sampler with the right parameters depending on whether
# this is a paired-end or single-end data set.
if paired_end:
# Sampler parameters for paired-end mode
sampler_params = miso.get_paired_end_sampler_params(num_isoforms,
mean_frag_len,
frag_variance,
read_len,
overhang_len=overhang_len)
sampler = miso.MISOSampler(sampler_params, paired_end=True,
log_dir=output_dir)
else:
# Sampler parameters for single-end mode
sampler_params = miso.get_single_end_sampler_params(num_isoforms,
read_len,
overhang_len)
sampler = miso.MISOSampler(sampler_params, paired_end=False,
log_dir=output_dir)
# Make directory for chromosome -- if given an event type, put
# the gene in the event type directory
if event_type != None:
chrom_dir = os.path.join(output_dir, event_type, gene_obj.chrom)
else:
chrom_dir = os.path.join(output_dir, gene_obj.chrom)
if not os.path.isdir(chrom_dir):
os.makedirs(chrom_dir)
output_filename = os.path.join(chrom_dir, gene_obj.label)
sampler.run_sampler(num_iters, reads, gene_obj,
hyperparameters, sampler_params,
output_filename, burn_in=burn_in,
lag=lag)
def compute_gene_psi(gene_ids,
gff_index_filename,
bam_filename,
output_dir,
read_len,
overhang_len,
paired_end=None,
event_type=None):
"""
Run Psi at the Gene-level (for multi-isoform inference.)
Arguments:
- Set of gene IDs corresponding to gene IDs from the GFF
- Indexed GFF filename describing the genes
- BAM filename with the reads (must be sorted and indexed)
- Output directory
- Optional: Run in paired-end mode. Gives mean and standard deviation
of fragment length distribution.
"""
if not os.path.isdir(output_dir):
os.makedirs(output_dir)
num_genes = len(gene_ids)
print "Computing Psi for %d genes..." % (num_genes)
print " - " + ", ".join(gene_ids)
print " - GFF filename: %s" % (gff_index_filename)
print " - BAM: %s" % (bam_filename)
print " - Outputting to: %s" % (output_dir)
if paired_end:
print " - Paired-end mode: ", paired_end
settings = Settings.get()
settings_params = Settings.get_sampler_params()
burn_in = settings_params["burn_in"]
lag = settings_params["lag"]
num_iters = settings_params["num_iters"]
min_event_reads = Settings.get_min_event_reads()
if paired_end:
mean_frag_len = int(paired_end[0])
frag_variance = power(int(paired_end[1]), 2)
# Load the genes from the GFF
# print "Loading genes from indexed GFF..."
# t1 = time.time()
gff_genes = gff_utils.load_indexed_gff_file(gff_index_filename)
# t2 = time.time()
# print " - Loading took: %.2f seconds" %(t2 - t1)
for gene_id, gene_info in gff_genes.iteritems():
if gene_id not in gene_ids:
# Skip genes that we were not asked to run on
continue
gene_obj = gene_info['gene_object']
gene_hierarchy = gene_info['hierarchy']
# Find the most inclusive transcription start and end sites for each gene
tx_start, tx_end = gff_utils.get_inclusive_txn_bounds(
gene_info['hierarchy'][gene_id])
# If given a template for the SAM file, use it
template = None
if settings and "sam_template" in settings:
template = settings["sam_template"]
# Load the BAM file
bamfile = sam_utils.load_bam_reads(bam_filename, template=template)
# Fetch reads aligning to the gene boundaries
gene_reads = sam_utils.fetch_bam_reads_in_gene(bamfile, gene_obj.chrom,
tx_start, tx_end,
gene_obj)
# Align the reads to the isoforms
reads = sam_utils.sam_reads_to_isoforms(gene_reads,
gene_obj,
paired_end=paired_end)
num_raw_reads = len(reads)
# Skip gene if none of the reads align to gene boundaries
if num_raw_reads < min_event_reads:
print "Only %d reads in gene, skipping (needed >= %d reads)" \
%(num_raw_reads, min_event_reads)
continue
reads = array(reads)
num_isoforms = len(gene_obj.isoforms)
hyperparameters = ones(num_isoforms)
##
## Run the sampler
##
# Create the sampler with the right parameters depending on whether
# this is a paired-end or single-end data set.
if paired_end:
# Sampler parameters for paired-end mode
sampler_params = miso.get_paired_end_sampler_params(
num_isoforms, mean_frag_len, frag_variance, read_len)
sampler = miso.MISOSampler(sampler_params,
paired_end=True,
log_dir=output_dir)
else:
# Sampler parameters for single-end mode
sampler_params = miso.get_single_end_sampler_params(
num_isoforms, read_len, overhang_len)
sampler = miso.MISOSampler(sampler_params,
paired_end=False,
log_dir=output_dir)
# Make directory for chromosome -- if given an event type, put
# the gene in the event type directory
if event_type != None:
chrom_dir = os.path.join(output_dir, event_type, gene_obj.chrom)
else:
chrom_dir = os.path.join(output_dir, gene_obj.chrom)
if not os.path.isdir(chrom_dir):
os.makedirs(chrom_dir)
output_filename = os.path.join(chrom_dir, gene_obj.label)
sampler.run_sampler(num_iters,
reads,
gene_obj,
hyperparameters,
sampler_params,
output_filename,
burn_in=burn_in,
lag=lag)
