def processBlock(tf_basecaller_bam_filename, BASECALLER_RESULTS, tfkey,
floworder, analysis_dir):
try:
# These files will be created
tfstatsjson_path = os.path.join(BASECALLER_RESULTS, "TFStats.json")
tfbam_filename = os.path.join(BASECALLER_RESULTS, "rawtf.bam")
tfref_filename = os.path.join(BASECALLER_RESULTS, "DefaultTFs.fasta")
ionstats_tf_filename = os.path.join(BASECALLER_RESULTS,
"ionstats_tf.json")
# TF analysis in 5 simple steps
buildTFReference(tfref_filename, analysis_dir, tfkey)
alignTFs(tf_basecaller_bam_filename, tfbam_filename, tfref_filename)
ionstats.generate_ionstats_tf(tfbam_filename, tfref_filename,
ionstats_tf_filename)
ionstats_plots.tf_length_histograms(ionstats_tf_filename, '.')
ionstats.generate_legacy_tf_files(ionstats_tf_filename,
tfstatsjson_path)
except NoTFDataException as e:
printtime("No data to analyze Test Fragments (%s)" % e.msg)
f = open(os.path.join(BASECALLER_RESULTS, 'TFStats.json'), 'w')
f.write(json.dumps({}))
f.close()
except:
traceback.print_exc()
def processBlock(tf_basecaller_bam_filename, BASECALLER_RESULTS, tfkey, floworder, analysis_dir):
try:
# These files will be created
tfstatsjson_path = os.path.join(BASECALLER_RESULTS, "TFStats.json")
tfbam_filename = os.path.join(BASECALLER_RESULTS, "rawtf.bam")
tfref_filename = os.path.join(BASECALLER_RESULTS, "DefaultTFs.fasta")
ionstats_tf_filename = os.path.join(BASECALLER_RESULTS, "ionstats_tf.json")
# TF analysis in 5 simple steps
buildTFReference(tfref_filename, analysis_dir, tfkey)
alignTFs(tf_basecaller_bam_filename, tfbam_filename, tfref_filename)
ionstats.generate_ionstats_tf(tfbam_filename, tfref_filename, ionstats_tf_filename)
ionstats_plots.tf_length_histograms(ionstats_tf_filename, ".")
ionstats.generate_legacy_tf_files(ionstats_tf_filename, tfstatsjson_path)
except NoTFDataException as e:
printtime("No data to analyze Test Fragments (%s)" % e.msg)
f = open(os.path.join(BASECALLER_RESULTS, "TFStats.json"), "w")
f.write(json.dumps({}))
f.close()
except:
traceback.print_exc()
def mergeBlocks(BASECALLER_RESULTS, dirs, floworder):
ionstats_tf_filename = os.path.join(BASECALLER_RESULTS, "ionstats_tf.json")
tfstatsjson_path = os.path.join(BASECALLER_RESULTS, "TFStats.json")
composite_filename_list = [os.path.join(BASECALLER_RESULTS, dir, "ionstats_tf.json") for dir in dirs]
composite_filename_list = [filename for filename in composite_filename_list if os.path.exists(filename)]
ionstats.reduce_stats(composite_filename_list, ionstats_tf_filename)
ionstats_plots.tf_length_histograms(ionstats_tf_filename, ".")
ionstats.generate_legacy_tf_files(ionstats_tf_filename, tfstatsjson_path)
def mergeBlocks(BASECALLER_RESULTS, dirs, floworder):
ionstats_tf_filename = os.path.join(BASECALLER_RESULTS, "ionstats_tf.json")
tfstatsjson_path = os.path.join(BASECALLER_RESULTS, "TFStats.json")
composite_filename_list = [
os.path.join(BASECALLER_RESULTS, dir, "ionstats_tf.json")
for dir in dirs
]
composite_filename_list = [
filename for filename in composite_filename_list
if os.path.exists(filename)
]
ionstats.reduce_stats(composite_filename_list, ionstats_tf_filename)
ionstats_plots.tf_length_histograms(ionstats_tf_filename, '.')
ionstats.generate_legacy_tf_files(ionstats_tf_filename, tfstatsjson_path)
tf_basecaller_bam_filename = os.path.join(env['BASECALLER_RESULTS'], 'rawtf.basecaller.bam')
tf_reference_filename = os.path.join("/results/referenceLibrary/TestFragment", env['tfKey'], "DefaultTFs.fasta")
# These files will be created
tfbam_filename = os.path.join(env['BASECALLER_RESULTS'],"rawtf.bam")
ionstats_tf_filename = os.path.join(env['BASECALLER_RESULTS'],"ionstats_tf.json")
tfstatsjson_path = os.path.join(env['BASECALLER_RESULTS'],"TFStats.json")
printtime("TF: Mapping '%s'" % tf_basecaller_bam_filename)
alignment.alignTFs(tf_basecaller_bam_filename, tfbam_filename, tf_reference_filename)
ionstats.generate_ionstats_tf(tfbam_filename,tf_reference_filename,ionstats_tf_filename)
ionstats_plots.tf_length_histograms(ionstats_tf_filename, '.')
ionstats.generate_legacy_tf_files(ionstats_tf_filename,tfstatsjson_path)
except:
traceback.print_exc()
printtime("No data to analyze Test Fragments")
f = open(os.path.join(env['BASECALLER_RESULTS'],'TFStats.json'),'w')
f.write(json.dumps({}))
f.close()
# Process unfiltered reads
if do_unfiltered_processing:
set_result_status('Process Unfiltered BAM')
do_ionstats = False
ionstats_tf_filename = os.path.join(env["BASECALLER_RESULTS"],
"ionstats_tf.json")
tfstatsjson_path = os.path.join(env["BASECALLER_RESULTS"],
"TFStats.json")
printtime("TF: Mapping '%s'" % tf_basecaller_bam_filename)
alignment.alignTFs(tf_basecaller_bam_filename, tfbam_filename,
tf_reference_filename)
ionstats.generate_ionstats_tf(tfbam_filename,
tf_reference_filename,
ionstats_tf_filename)
ionstats_plots.tf_length_histograms(ionstats_tf_filename, ".")
ionstats.generate_legacy_tf_files(ionstats_tf_filename,
tfstatsjson_path)
except Exception:
traceback.print_exc()
printtime("No data to analyze Test Fragments")
f = open(os.path.join(env["BASECALLER_RESULTS"], "TFStats.json"),
"w")
f.write(json.dumps({}))
f.close()
# Process unfiltered reads
if do_unfiltered_processing:
set_result_status("Process Unfiltered BAM")
do_ionstats = False
create_index = False
'-d',
'--dir',
dest='analysis_dir',
default='.',
help=
'Directory searched for DefaultTFs.conf (Default: current directory)')
args = parser.parse_args()
print "TFPipeline args :", args
# Step 2. If reference fasta file not specified, build one
try:
if args.ref == None:
args.ref = 'DefaultTFs.fasta'
buildTFReference(args.ref, args.analysis_dir, args.key)
# Step 3. Perform alignment and generate bam file
alignTFs(args.basecaller_bam, args.bam, args.ref)
# Step 4. Post-processing. Run alignStats and TFMapper
ionstats.generate_ionstats_tf(args.bam, args.ref, 'ionstats_tf.json')
ionstats_plots.tf_length_histograms('ionstats_tf.json', '.')
ionstats.generate_legacy_tf_files('ionstats_tf.json', 'TFStats.json')
except:
traceback.print_exc()
"-d",
"--dir",
dest="analysis_dir",
default=".",
help="Directory searched for DefaultTFs.conf (Default: current directory)",
)
args = parser.parse_args()
print "TFPipeline args :", args
# Step 2. If reference fasta file not specified, build one
try:
if args.ref == None:
args.ref = "DefaultTFs.fasta"
buildTFReference(args.ref, args.analysis_dir, args.key)
# Step 3. Perform alignment and generate bam file
alignTFs(args.basecaller_bam, args.bam, args.ref)
# Step 4. Post-processing. Run alignStats and TFMapper
ionstats.generate_ionstats_tf(args.bam, args.ref, "ionstats_tf.json")
ionstats_plots.tf_length_histograms("ionstats_tf.json", ".")
ionstats.generate_legacy_tf_files("ionstats_tf.json", "TFStats.json")
except:
traceback.print_exc()
args = parser.parse_args()
print "TFPipeline args :",args
# Step 2. If reference fasta file not specified, build one
try:
if args.ref == None:
args.ref = 'DefaultTFs.fasta'
buildTFReference(args.ref,args.analysis_dir,args.key)
# Step 3. Perform alignment and generate bam file
alignTFs(args.basecaller_bam, args.bam, args.ref)
# Step 4. Post-processing. Run alignStats and TFMapper
ionstats.generate_ionstats_tf(args.bam,args.ref,'ionstats_tf.json')
ionstats_plots.tf_length_histograms('ionstats_tf.json', '.')
ionstats.generate_legacy_tf_files('ionstats_tf.json','TFStats.json')
except:
traceback.print_exc()
