--- /dev/null
+-- Add fields to support multiplexing, and update our database
+
+alter table samples_library add column multiplex_id varchar(128);
+alter table samples_librarytype add column can_multiplex bool not null default false;
+alter table samples_librarytype add column is_paired_end bool not null default false;
+update samples_librarytype set can_multiplex=0, is_paired_end=0;
+update samples_librarytype set can_multiplex=1 where id in (5,7,8);
+update samples_librarytype set is_paired_end=1 where id in (2,5,7,8);
+update samples_library set multiplex_id=1 where library_name like "Index #1 %";
+update samples_library set multiplex_id=2 where library_name like "Index #2 %";
+update samples_library set multiplex_id=3 where library_name like "Index #3 %";
+update samples_library set multiplex_id=4 where library_name like "Index #4 %";
+update samples_library set multiplex_id=5 where library_name like "Index #5 %";
+update samples_library set multiplex_id=6 where library_name like "Index #6 %";
+update samples_library set multiplex_id=7 where library_name like "Index #7 %";
+update samples_library set multiplex_id=8 where library_name like "Index #8 %";
+update samples_library set multiplex_id=9 where library_name like "Index #9 %";
+update samples_library set multiplex_id=10 where library_name like "Index #10 %";
+update samples_library set multiplex_id=11 where library_name like "Index #11 %";
+update samples_library set multiplex_id=12 where library_name like "Index #12 %";
+
+update samples_library set multiplex_id=1 where library_name like "Nextera #1 %";
+update samples_library set multiplex_id=2 where library_name like "Nextera #2 %";
+update samples_library set multiplex_id=3 where library_name like "Nextera #3 %";
+update samples_library set multiplex_id=4 where library_name like "Nextera #4 %";
+update samples_library set multiplex_id=5 where library_name like "Nextera #5 %";
+update samples_library set multiplex_id=6 where library_name like "Nextera #6 %";
+update samples_library set multiplex_id=7 where library_name like "Nextera #7 %";
+update samples_library set multiplex_id=8 where library_name like "Nextera #8 %";
+update samples_library set multiplex_id=9 where library_name like "Nextera #9 %";
+update samples_library set multiplex_id=10 where library_name like "Nextera #10 %";
+update samples_library set multiplex_id=11 where library_name like "Nextera #11 %";
+update samples_library set multiplex_id=12 where library_name like "Nextera #12 %";
+
+update samples_library set multiplex_id=1 where library_name like "Nextera index1 %";
+update samples_library set multiplex_id=2 where library_name like "Nextera index2 %";
+update samples_library set multiplex_id=3 where library_name like "Nextera index3 %";
+update samples_library set multiplex_id=4 where library_name like "Nextera index4 %";
+update samples_library set multiplex_id=5 where library_name like "Nextera index5 %";
+update samples_library set multiplex_id=6 where library_name like "Nextera index6 %";
+update samples_library set multiplex_id=7 where library_name like "Nextera index7 %";
+update samples_library set multiplex_id=8 where library_name like "Nextera index8 %";
+update samples_library set multiplex_id=9 where library_name like "Nextera index9 %";
+update samples_library set multiplex_id=10 where library_name like "Nextera index10 %";
+update samples_library set multiplex_id=11 where library_name like "Nextera index11 %";
+update samples_library set multiplex_id=12 where library_name like "Nextera index12 %";
import json
except ImportError, e:
import simplejson as json
-
+
import os
import re
DataRun, \
Lane, \
LANE_STATUS_MAP
-from htsworkflow.frontend.samples.models import Library, HTSUser
+from htsworkflow.frontend.samples.models import Library, MultiplexIndex, HTSUser
def flowcell_information(flowcell_id):
"""
lane_set = {}
for lane in fc.lane_set.all():
- lane_set[lane.lane_number] = {
+ lane_item = {
'cluster_estimate': lane.cluster_estimate,
'comment': lane.comment,
'experiment_type': lane.library.experiment_type.name,
'experiment_type_id': lane.library.experiment_type_id,
'flowcell': lane.flowcell.flowcell_id,
- 'lane_number': int(lane.lane_number),
+ 'lane_number': lane.lane_number,
'library_name': lane.library.library_name,
'library_id': lane.library.id,
'library_species': lane.library.library_species.scientific_name,
'status_code': lane.status,
'status': LANE_STATUS_MAP[lane.status]
}
+ sequences = lane.library.index_sequences()
+ if sequences is not None:
+ lane_item['index_sequence'] = sequences
+
+ lane_set.setdefault(lane.lane_number,[]).append(lane_item)
if fc.control_lane is None:
control_lane = None
else:
control_lane = int(fc.control_lane)
-
+
info = {
'advanced_run': fc.advanced_run,
'cluster_station_id': fc.cluster_station_id,
'sequencer_id': fc.sequencer_id,
'sequencer': fc.sequencer.name,
}
-
+
return info
def flowcell_json(request, fc_id):
Return a JSON blob containing enough information to generate a config file.
"""
require_api_key(request)
-
+
fc_dict = flowcell_information(fc_id)
if fc_dict is None:
raise Http404
-
+
fc_json = json.dumps(fc_dict)
return HttpResponse(fc_json, mimetype = 'application/json')
"""
query = {}
if username is not None:
- user = HTSUser.objects.get(username=username)
+ user = HTSUser.objects.get(username=username)
query.update({'library__affiliations__users__id': user.id})
-
+
lanes = Lane.objects.filter(**query).order_by('-flowcell__run_date')
-
+
result = []
for l in lanes:
affiliations = l.library.affiliations.all()
result = lanes_for(username)
except ObjectDoesNotExist, e:
raise Http404
-
+
#convert query set to python structure
-
+
result_json = json.dumps(result)
return HttpResponse(result_json, mimetype='application/json')
-
+
+
def updStatus(request):
output=''
user = 'none'
user = request.user
#Check access permission
- if not (user.is_superuser and settings.ALLOWED_IPS.has_key(ClIP)):
+ if not (user.is_superuser and settings.ALLOWED_IPS.has_key(ClIP)):
return HttpResponse("%s access denied from %s." % (user, ClIP))
# ~~~~~~Parameters for the job ~~~~
fcid = request.REQUEST['fcid']
else:
return HttpResponse('missing fcid')
-
+
if request.REQUEST.has_key('runf'):
runfolder = request.REQUEST['runf']
else:
return HttpResponse('missing runf')
-
+
if request.REQUEST.has_key('updst'):
UpdatedStatus = request.REQUEST['updst']
else:
return HttpResponse('missing status')
-
- # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+ # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Update Data Run status in DB
- # Try get rec. If not found return 'entry not found + <fcid><runfolder>', if found try update and return updated
+ # Try get rec. If not found return 'entry not found + <fcid><runfolder>', if found try update and return updated
try:
rec = DataRun.objects.get(run_folder=runfolder)
rec.run_status = UpdatedStatus
config += ['ELAND_MULTIPLE_INSTANCES 8']
genome_dir = 'GENOME_DIR /Volumes/Genomes/'
eland_genome = 'ELAND_GENOME /Volumes/Genomes/'
-
- try:
+
+ try:
fc = FlowCell.objects.get(flowcell_id=fcid)
for lane in fc.lane_set.all():
config += [ str(lane.lane_number) +":" + \
genome_dir + lane.library.library_species.scientific_name ]
config += [ str(lane.lane_number) +":" + \
eland_genome + lane.library.library_species.scientific_name ]
-
+
except ObjectDoesNotExist:
config = 'Entry not found for fcid = '+fcid
rec.config_params = cnfgfile
rec.save()
else:
- cnfgfile = 'Failed generating config params for RunFolder = '+runfolder +', Flowcell id = '+ fcid+ ' Config Text:\n'+cnfgfile
-
+ cnfgfile = 'Failed generating config params for RunFolder = '+runfolder +', Flowcell id = '+ fcid+ ' Config Text:\n'+cnfgfile
+
except ObjectDoesNotExist:
cnfgfile = 'Entry not found for RunFolder = '+runfolder
outputfile = ''
if request.has_key('fcid'):
fcid = request['fcid']
- try:
+ try:
rec = FlowCell.objects.get(flowcell_id=fcid)
#Ex: 071211
year = datetime.today().year.__str__()
year = replace(year,'20','')
month = datetime.today().month
if month < 10: month = "0"+month.__str__()
- else: month = month.__str__()
+ else: month = month.__str__()
day = datetime.today().day
if day < 10: day = "0"+day.__str__()
else: day = day.__str__()
sequencing_seconds_per_cycle= 3600 * 1.5
# 800 is a rough guess
pipeline_seconds_per_cycle = 800
-
+
cycles = flowcell.read_length
if flowcell.paired_end:
cycles *= 2
def estimateFlowcellTimeRemaining(flowcell):
estimate_mid = estimateFlowcellDuration(flowcell)
-
+
# offset for how long we've been running
running_time = datetime.now() - flowcell.run_date
estimate_mid -= running_time
estimate_low = timedelta(estimate.days, 0)
# floor estimate_mid and add a day
estimate_high = timedelta(estimate.days+1, 0)
-
+
return (estimate_low, estimate_high)
-
+
def makeUserLaneMap(flowcell):
"""
def getUsersForFlowcell(flowcell):
users = set()
-
+
for lane in flowcell.lane_set.all():
for affiliation in lane.library.affiliations.all():
for user in affiliation.users.all():
users.add(user)
-
+
return users
-
+
def makeUserLibraryMap(libraries):
"""
Given an interable set of libraries return a mapping or
users interested in those libraries.
"""
users = {}
-
+
for library in libraries:
for affiliation in library.affiliations.all():
for user in affiliation.users.all():
users.setdefault(user,[]).append(library)
-
+
return users
def makeAffiliationLaneMap(flowcell):
[
- {"pk": 5, "model": "auth.user",
+ {"pk": 5, "model": "auth.user",
"fields": {
"username": "test",
"first_name": "",
{"pk": 5, "model": "samples.htsuser",
"fields" : {}
},
- {"pk": 6, "model": "auth.user",
+ {"pk": 6, "model": "auth.user",
"fields": {
"username": "admintest",
"first_name": "",
{"pk": 6, "model": "samples.htsuser",
"fields" : {}
},
- {"pk": 7, "model": "auth.user",
+ {"pk": 7, "model": "auth.user",
"fields": {
"username": "supertest",
"first_name": "",
"email": "pk5@example.com"
}
},
- {"pk": 1, "model": "experiments.clusterstation", "fields": {"name": "old"}},
- {"pk": 2, "model": "experiments.clusterstation", "fields": {"name": "loaner"}},
- {"pk": 3, "model": "experiments.clusterstation", "fields": {"name": "new"}},
- {"pk": 1, "model": "experiments.sequencer", "fields": {"name": "Rotifer (HWI-EAS229)"}},
- {"pk": 2, "model": "experiments.sequencer", "fields": {"name": "Tardigrade"}},
- {"pk": 3, "model": "experiments.sequencer", "fields": {"name": "Sequenced somewhere else."}},
- {"pk": 153, "model": "experiments.flowcell",
+ {"pk": 1, "model": "experiments.clusterstation", "fields": {"name": "old"}},
+ {"pk": 2, "model": "experiments.clusterstation", "fields": {"name": "loaner"}},
+ {"pk": 3, "model": "experiments.clusterstation", "fields": {"name": "new"}},
+ {"pk": 1, "model": "experiments.sequencer", "fields": {"name": "Rotifer (HWI-EAS229)"}},
+ {"pk": 2, "model": "experiments.sequencer", "fields": {"name": "Tardigrade"}},
+ {"pk": 3, "model": "experiments.sequencer", "fields": {"name": "Sequenced somewhere else."}},
+ {"pk": 153, "model": "experiments.flowcell",
"fields": {
- "paired_end": true,
- "run_date": "2007-09-27 22:12:13",
- "read_length": 36,
+ "paired_end": true,
+ "run_date": "2007-09-27 22:12:13",
+ "read_length": 36,
"notes": "",
"advanced_run": false,
"control_lane": 2,
"sequencer": 2,
"flowcell_id": "FC12150"
}
- },
+ },
{"pk": 1193, "model": "experiments.lane",
"fields": {
"comment": "No change in cluster numbers, despite slight increase in pM",
"lane_number": 1,
"pM": "8"
}
- },
+ },
{"pk": 1192, "model": "experiments.lane",
"fields": {
"comment": "Other library",
"lane_number": 1,
"pM": "7"
}
- },
+ },
- {"pk": "10981", "model": "samples.library",
+ {"pk": "10981", "model": "samples.library",
"fields": {
- "ten_nM_dilution": false,
- "gel_cut_size": 400,
- "library_name": "Paired End Multiplexed Sp-BAC",
- "creation_date": "2009-07-21",
- "cell_line": 1,
- "library_species": 10,
- "library_type": null,
- "made_by": "Igor",
+ "ten_nM_dilution": false,
+ "gel_cut_size": 400,
+ "library_name": "Paired End Multiplexed Sp-BAC",
+ "creation_date": "2009-07-21",
+ "cell_line": 1,
+ "library_species": 10,
+ "library_type": null,
+ "made_by": "Igor",
"affiliations": [
1,2
- ],
- "replicate": 1,
- "condition": 1,
- "hidden": false,
- "stopping_point": "Done",
- "tags": [],
- "made_for": "Andy Cameron",
- "amplified_from_sample": null,
- "notes": "Combined 10957-10968",
- "undiluted_concentration": "5.1",
- "successful_pM": null,
- "experiment_type": 10,
+ ],
+ "replicate": 1,
+ "condition": 1,
+ "hidden": false,
+ "stopping_point": "Done",
+ "tags": [],
+ "made_for": "Andy Cameron",
+ "amplified_from_sample": null,
+ "notes": "Combined 10957-10968",
+ "undiluted_concentration": "5.1",
+ "successful_pM": null,
+ "experiment_type": 10,
"antibody": null
}
- },
+ },
{"pk": 1194, "model": "experiments.lane",
"fields": {
"comment": "",
"lane_number": 2,
"pM": "7"
}
- },
+ },
{
- "pk": "11016",
- "model": "samples.library",
+ "pk": "11016",
+ "model": "samples.library",
"fields": {
- "ten_nM_dilution": false,
- "gel_cut_size": 325,
- "library_name": "Paired End Pfl #3 MP 7/24/9 a",
- "creation_date": "2009-08-06",
- "cell_line": 1,
- "library_species": 2,
- "library_type": 2,
- "made_by": "Lorian",
+ "ten_nM_dilution": false,
+ "gel_cut_size": 325,
+ "library_name": "Paired End Pfl #3 MP 7/24/9 a",
+ "creation_date": "2009-08-06",
+ "cell_line": 1,
+ "library_species": 2,
+ "library_type": 2,
+ "made_by": "Lorian",
"affiliations": [
2
- ],
- "replicate": 1,
- "condition": 1,
- "hidden": false,
- "stopping_point": "1Aa",
- "tags": [],
- "made_for": "",
- "amplified_from_sample": 11006,
- "notes": "7/31/2009 16:08:22\tColor: Blue",
- "undiluted_concentration": "35.5",
- "successful_pM": null,
- "experiment_type": 8,
+ ],
+ "replicate": 1,
+ "condition": 1,
+ "hidden": false,
+ "stopping_point": "1Aa",
+ "tags": [],
+ "made_for": "",
+ "amplified_from_sample": 11006,
+ "notes": "7/31/2009 16:08:22\tColor: Blue",
+ "undiluted_concentration": "35.5",
+ "successful_pM": null,
+ "experiment_type": 8,
"antibody": null
}
- },
+ },
{"pk": 1195, "model": "experiments.lane",
"fields": {
"comment": "",
"lane_number": 3,
"pM": "7"
}
- },
+ },
{
- "pk": "SL039",
- "model": "samples.library",
+ "pk": "SL039",
+ "model": "samples.library",
"fields": {
- "ten_nM_dilution": false,
- "gel_cut_size": 300,
- "library_name": "Paired ends 99 GM12892",
- "creation_date": "2009-08-25",
- "cell_line": 1,
- "library_species": 8,
- "library_type": 2,
- "made_by": "Brian Williams",
+ "ten_nM_dilution": false,
+ "gel_cut_size": 300,
+ "library_name": "Paired ends 99 GM12892",
+ "creation_date": "2009-08-25",
+ "cell_line": 1,
+ "library_species": 8,
+ "library_type": 2,
+ "made_by": "Brian Williams",
"affiliations": [
3,4
- ],
- "replicate": 1,
- "condition": 1,
- "hidden": false,
- "stopping_point": "1Aa",
- "tags": [],
- "made_for": "Brian Williams",
- "amplified_from_sample": null,
- "notes": "fragment size = 300 bp, Amicon filtered\r\nnanodrop: 56.3",
- "undiluted_concentration": "28.7",
- "successful_pM": null,
- "experiment_type": 4,
+ ],
+ "replicate": 1,
+ "condition": 1,
+ "hidden": false,
+ "stopping_point": "1Aa",
+ "tags": [],
+ "made_for": "Brian Williams",
+ "amplified_from_sample": null,
+ "notes": "fragment size = 300 bp, Amicon filtered\r\nnanodrop: 56.3",
+ "undiluted_concentration": "28.7",
+ "successful_pM": null,
+ "experiment_type": 4,
"antibody": null
}
- },
+ },
{"pk": 1196, "model": "experiments.lane",
"fields": {
"comment": "This lane's library had the second lowest concentration of all the libraries built at the same time (2.05ng/ul)",
"lane_number": 4,
"pM": "7"
}
- },
+ },
{
- "pk": "11060",
- "model": "samples.library",
+ "pk": "11060",
+ "model": "samples.library",
"fields": {
- "ten_nM_dilution": false,
- "gel_cut_size": 300,
- "library_name": "Paired ends 100 VC_CN_4_M_MBB1185_s1",
- "creation_date": "2009-09-01",
- "cell_line": 1,
- "library_species": 8,
- "library_type": 2,
- "made_by": "Brian Williams",
+ "ten_nM_dilution": false,
+ "gel_cut_size": 300,
+ "library_name": "Paired ends 100 VC_CN_4_M_MBB1185_s1",
+ "creation_date": "2009-09-01",
+ "cell_line": 1,
+ "library_species": 8,
+ "library_type": 2,
+ "made_by": "Brian Williams",
"affiliations": [
5
- ],
- "replicate": 1,
- "condition": 1,
- "hidden": false,
- "stopping_point": "1Aa",
- "tags": [],
- "made_for": "Brian Williams",
- "amplified_from_sample": null,
- "notes": "300 bp gel fragment, Amicon filtered\r\nnanodrop: 24.2",
- "undiluted_concentration": "2.05",
- "successful_pM": null,
- "experiment_type": 4,
+ ],
+ "replicate": 1,
+ "condition": 1,
+ "hidden": false,
+ "stopping_point": "1Aa",
+ "tags": [],
+ "made_for": "Brian Williams",
+ "amplified_from_sample": null,
+ "notes": "300 bp gel fragment, Amicon filtered\r\nnanodrop: 24.2",
+ "undiluted_concentration": "2.05",
+ "successful_pM": null,
+ "experiment_type": 4,
"antibody": null
}
- },
+ },
{"pk": 1197, "model": "experiments.lane",
"fields": {
"comment": "stuff",
"pM": "7",
"status": 2
}
- },
+ },
{
- "pk": "11061",
- "model": "samples.library",
+ "pk": "11061",
+ "model": "samples.library",
"fields": {
- "ten_nM_dilution": false,
- "gel_cut_size": 300,
- "library_name": "Paired ends 101 VC_CN_4_M_MBB1185_s2",
- "creation_date": "2009-09-01",
- "cell_line": 1,
- "library_species": 8,
- "library_type": 2,
- "made_by": "Brian Williams",
+ "ten_nM_dilution": false,
+ "gel_cut_size": 300,
+ "library_name": "Paired ends 101 VC_CN_4_M_MBB1185_s2",
+ "creation_date": "2009-09-01",
+ "cell_line": 1,
+ "library_species": 8,
+ "library_type": 2,
+ "made_by": "Brian Williams",
"affiliations": [
2,4
- ],
- "replicate": 1,
- "condition": 1,
- "hidden": false,
- "stopping_point": "1Aa",
- "tags": [],
- "made_for": "Brian Williams",
- "amplified_from_sample": null,
- "notes": "300 bp gel fragment, Amicon filtered\r\nnanodrop: 33.1",
- "undiluted_concentration": "12.9",
- "successful_pM": null,
- "experiment_type": 4,
+ ],
+ "replicate": 1,
+ "condition": 1,
+ "hidden": false,
+ "stopping_point": "1Aa",
+ "tags": [],
+ "made_for": "Brian Williams",
+ "amplified_from_sample": null,
+ "notes": "300 bp gel fragment, Amicon filtered\r\nnanodrop: 33.1",
+ "undiluted_concentration": "12.9",
+ "successful_pM": null,
+ "experiment_type": 4,
"antibody": null
}
- },
+ },
{"pk": 1198, "model": "experiments.lane",
"fields": {
"comment": "This lane's library had the lowest concentration of all the libraries built at the same time (1.2ng/ul)",
"pM": "7",
"status": 0
}
- },
+ },
{
- "pk": "11062",
- "model": "samples.library",
+ "pk": "11062",
+ "model": "samples.library",
"fields": {
- "ten_nM_dilution": false,
- "gel_cut_size": 300,
- "library_name": "Paired ends 102 VC_AU_8_M_MBB4721_s1",
- "creation_date": "2009-09-01",
- "cell_line": 1,
- "library_species": 8,
- "library_type": 2,
- "made_by": "Brian Williams",
+ "ten_nM_dilution": false,
+ "gel_cut_size": 300,
+ "library_name": "Paired ends 102 VC_AU_8_M_MBB4721_s1",
+ "creation_date": "2009-09-01",
+ "cell_line": 1,
+ "library_species": 8,
+ "library_type": 2,
+ "made_by": "Brian Williams",
"affiliations": [
4,5
- ],
- "replicate": 1,
- "condition": 1,
- "hidden": false,
- "stopping_point": "1Aa",
- "tags": [],
- "made_for": "Brian Williams",
- "amplified_from_sample": null,
- "notes": "300 bp gel fragment, Amicon filtered\r\nnanodrop: 13.9",
- "undiluted_concentration": "1.2",
- "successful_pM": null,
- "experiment_type": 4,
+ ],
+ "replicate": 1,
+ "condition": 1,
+ "hidden": false,
+ "stopping_point": "1Aa",
+ "tags": [],
+ "made_for": "Brian Williams",
+ "amplified_from_sample": null,
+ "notes": "300 bp gel fragment, Amicon filtered\r\nnanodrop: 13.9",
+ "undiluted_concentration": "1.2",
+ "successful_pM": null,
+ "experiment_type": 4,
"antibody": null
}
- },
+ },
{"pk": 1199, "model": "experiments.lane",
"fields": {
"comment": "",
"lane_number": 7,
"pM": "7"
}
- },
+ },
{
- "pk": "11063",
- "model": "samples.library",
+ "pk": "11063",
+ "model": "samples.library",
"fields": {
- "ten_nM_dilution": false,
- "gel_cut_size": 300,
- "library_name": "Paired ends 103 VC_AU_8_M_MBB4721_s2",
- "creation_date": "2009-09-01",
- "cell_line": 1,
- "library_species": 8,
- "library_type": 2,
- "made_by": "Brian Williams",
+ "ten_nM_dilution": false,
+ "gel_cut_size": 300,
+ "library_name": "Paired ends 103 VC_AU_8_M_MBB4721_s2",
+ "creation_date": "2009-09-01",
+ "cell_line": 1,
+ "library_species": 8,
+ "library_type": 2,
+ "made_by": "Brian Williams",
"affiliations": [
1,3
- ],
- "replicate": 1,
- "condition": 1,
- "hidden": false,
- "stopping_point": "1Aa",
- "tags": [],
- "made_for": "Brian Williams",
- "amplified_from_sample": null,
- "notes": "300 bp gel fragment, Amicon filtered\r\nnanodrop: 46.9",
- "undiluted_concentration": "24.5",
- "successful_pM": null,
- "experiment_type": 4,
+ ],
+ "replicate": 1,
+ "condition": 1,
+ "hidden": false,
+ "stopping_point": "1Aa",
+ "tags": [],
+ "made_for": "Brian Williams",
+ "amplified_from_sample": null,
+ "notes": "300 bp gel fragment, Amicon filtered\r\nnanodrop: 46.9",
+ "undiluted_concentration": "24.5",
+ "successful_pM": null,
+ "experiment_type": 4,
"antibody": null
}
- },
+ },
{"pk": 1200, "model": "experiments.lane",
"fields": {
"comment": "This lane's library had the third lowest concentration of all the libraries built at the same time (5.21ng/ul), but gave perfectly normal cluster numbers",
}
},
{
- "pk": "11064",
- "model": "samples.library",
+ "pk": "11064",
+ "model": "samples.library",
"fields": {
- "ten_nM_dilution": false,
- "gel_cut_size": 300,
- "library_name": "Paired ends 104 VC_CN_7_M_MBB4898_s1",
- "creation_date": "2009-09-01",
- "cell_line": 1,
- "library_species": 8,
- "library_type": 2,
- "made_by": "Brian Williams",
+ "ten_nM_dilution": false,
+ "gel_cut_size": 300,
+ "library_name": "Paired ends 104 VC_CN_7_M_MBB4898_s1",
+ "creation_date": "2009-09-01",
+ "cell_line": 1,
+ "library_species": 8,
+ "library_type": 2,
+ "made_by": "Brian Williams",
"affiliations": [
3,5
- ],
- "replicate": 1,
- "condition": 1,
- "hidden": false,
- "stopping_point": "1Aa",
- "tags": [],
- "made_for": "Brian Williams",
- "amplified_from_sample": null,
- "notes": "300 bp gel fragment, Amicon filtered\r\nnanodrop: 20.4",
- "undiluted_concentration": "5.21",
- "successful_pM": null,
- "experiment_type": 4,
+ ],
+ "replicate": 1,
+ "condition": 1,
+ "hidden": false,
+ "stopping_point": "1Aa",
+ "tags": [],
+ "made_for": "Brian Williams",
+ "amplified_from_sample": null,
+ "notes": "300 bp gel fragment, Amicon filtered\r\nnanodrop: 20.4",
+ "undiluted_concentration": "5.21",
+ "successful_pM": null,
+ "experiment_type": 4,
"antibody": null
}
},
- {"pk": 152, "model": "experiments.flowcell",
+ {"pk": 152, "model": "experiments.flowcell",
"fields": {
"paired_end": false,
"run_date": "2009-09-10 18:30:15",
"sequencer": 1,
"flowcell_id": "42JTNAAXX"
}
- },
+ },
{"pk": 1185, "model": "experiments.lane",
"fields": {
"comment": "",
}
},
{
- "pk": "11035",
- "model": "samples.library",
+ "pk": "11035",
+ "model": "samples.library",
"fields": {
- "ten_nM_dilution": false,
- "gel_cut_size": 300,
- "library_name": "Paired ends 95 Gilberto_d3_control_LTA",
- "creation_date": "2009-08-25",
- "cell_line": 1,
- "library_species": 9,
- "library_type": 2,
- "made_by": "Brian Williams",
+ "ten_nM_dilution": false,
+ "gel_cut_size": 300,
+ "library_name": "Paired ends 95 Gilberto_d3_control_LTA",
+ "creation_date": "2009-08-25",
+ "cell_line": 1,
+ "library_species": 9,
+ "library_type": 2,
+ "made_by": "Brian Williams",
"affiliations": [
3
- ],
- "replicate": 1,
- "condition": 1,
- "hidden": false,
- "stopping_point": "1Aa",
- "tags": [],
- "made_for": "Brian Williams",
- "amplified_from_sample": null,
- "notes": "fragment size = 300 bp, Amicon filtered\r\nnanodrop: 67.1",
- "undiluted_concentration": "28.5",
- "successful_pM": null,
- "experiment_type": 4,
+ ],
+ "replicate": 1,
+ "condition": 1,
+ "hidden": false,
+ "stopping_point": "1Aa",
+ "tags": [],
+ "made_for": "Brian Williams",
+ "amplified_from_sample": null,
+ "notes": "fragment size = 300 bp, Amicon filtered\r\nnanodrop: 67.1",
+ "undiluted_concentration": "28.5",
+ "successful_pM": null,
+ "experiment_type": 4,
"antibody": null
}
- },
+ },
{"pk": 1186, "model": "experiments.lane",
"fields": {
"comment": "",
}
},
{
- "pk": "11037",
- "model": "samples.library",
+ "pk": "11037",
+ "model": "samples.library",
"fields": {
- "ten_nM_dilution": false,
- "gel_cut_size": 300,
- "library_name": "Paired ends 97 Kuntz_PDHT",
- "creation_date": "2009-08-25",
- "cell_line": 1,
- "library_species": 3,
- "library_type": 2,
- "made_by": "Brian Williams",
+ "ten_nM_dilution": false,
+ "gel_cut_size": 300,
+ "library_name": "Paired ends 97 Kuntz_PDHT",
+ "creation_date": "2009-08-25",
+ "cell_line": 1,
+ "library_species": 3,
+ "library_type": 2,
+ "made_by": "Brian Williams",
"affiliations": [
4
- ],
- "replicate": 1,
- "condition": 1,
- "hidden": false,
- "stopping_point": "1Aa",
- "tags": [],
- "made_for": "Brian Williams",
- "amplified_from_sample": null,
- "notes": "fragment size = 300 bp, Amicon filtered\r\nnanodrop: 52.7",
- "undiluted_concentration": "25.5",
- "successful_pM": null,
- "experiment_type": 4,
+ ],
+ "replicate": 1,
+ "condition": 1,
+ "hidden": false,
+ "stopping_point": "1Aa",
+ "tags": [],
+ "made_for": "Brian Williams",
+ "amplified_from_sample": null,
+ "notes": "fragment size = 300 bp, Amicon filtered\r\nnanodrop: 52.7",
+ "undiluted_concentration": "25.5",
+ "successful_pM": null,
+ "experiment_type": 4,
"antibody": null
}
- },
+ },
{"pk": 1187, "model": "experiments.lane",
"fields": {
"comment": "",
}
},
{
- "pk": "11045",
- "model": "samples.library",
+ "pk": "11045",
+ "model": "samples.library",
"fields": {
- "ten_nM_dilution": false,
- "gel_cut_size": 250,
- "library_name": "FLDN1 8/3/9 anti-AcH3 chip B6 a",
- "creation_date": "2009-08-26",
- "cell_line": null,
- "library_species": 9,
- "library_type": 1,
- "made_by": "Lorian",
+ "ten_nM_dilution": false,
+ "gel_cut_size": 250,
+ "library_name": "FLDN1 8/3/9 anti-AcH3 chip B6 a",
+ "creation_date": "2009-08-26",
+ "cell_line": null,
+ "library_species": 9,
+ "library_type": 1,
+ "made_by": "Lorian",
"affiliations": [
5
- ],
- "replicate": 1,
- "condition": null,
- "hidden": false,
- "stopping_point": "2A",
- "tags": [],
- "made_for": "",
- "amplified_from_sample": 11044,
- "notes": "8/21/2009 11:57:54\tColor: Yellow",
- "undiluted_concentration": "20.5",
- "successful_pM": null,
- "experiment_type": 2,
+ ],
+ "replicate": 1,
+ "condition": null,
+ "hidden": false,
+ "stopping_point": "2A",
+ "tags": [],
+ "made_for": "",
+ "amplified_from_sample": 12044,
+ "notes": "8/21/2009 11:57:54\tColor: Yellow",
+ "undiluted_concentration": "20.5",
+ "successful_pM": null,
+ "experiment_type": 2,
"antibody": null
}
- },
+ },
{"pk": 1188, "model": "experiments.lane",
"fields": {
"comment": "",
"pM": "7"}
},
{
- "pk": "11046",
- "model": "samples.library",
+ "pk": "11046",
+ "model": "samples.library",
"fields": {
- "ten_nM_dilution": false,
- "gel_cut_size": 250,
- "library_name": "FLDN1 7/8/9 anti-DiMeH3K4 chip B6 a",
- "creation_date": "2009-08-26",
- "cell_line": null,
- "library_species": 9,
- "library_type": 1,
- "made_by": "Lorian",
+ "ten_nM_dilution": false,
+ "gel_cut_size": 250,
+ "library_name": "FLDN1 7/8/9 anti-DiMeH3K4 chip B6 a",
+ "creation_date": "2009-08-26",
+ "cell_line": null,
+ "library_species": 9,
+ "library_type": 1,
+ "made_by": "Lorian",
"affiliations": [
6
- ],
- "replicate": 1,
- "condition": null,
- "hidden": false,
- "stopping_point": "2A",
- "tags": [],
- "made_for": "",
- "amplified_from_sample": 11045,
- "notes": "8/21/2009 11:57:54\tColor: Blue",
- "undiluted_concentration": "23.9",
- "successful_pM": null,
- "experiment_type": 2,
+ ],
+ "replicate": 1,
+ "condition": null,
+ "hidden": false,
+ "stopping_point": "2A",
+ "tags": [],
+ "made_for": "",
+ "amplified_from_sample": 11045,
+ "notes": "8/21/2009 11:57:54\tColor: Blue",
+ "undiluted_concentration": "23.9",
+ "successful_pM": null,
+ "experiment_type": 2,
"antibody": null
}
- },
+ },
{"pk": 1189, "model": "experiments.lane",
"fields": {
"comment": "",
"lane_number": 5,
"pM": "7"
}
- },
+ },
{
- "pk": "11054",
- "model": "samples.library",
+ "pk": "11054",
+ "model": "samples.library",
"fields": {
- "ten_nM_dilution": false,
- "gel_cut_size": 225,
- "library_name": "HNDHT HLH hnd-1 strain HT115 fed anti-hlh-1 2% fix plate a",
- "creation_date": "2009-08-31",
- "cell_line": null,
- "library_species": 3,
- "library_type": 1,
- "made_by": "Lorian",
+ "ten_nM_dilution": false,
+ "gel_cut_size": 225,
+ "library_name": "HNDHT HLH hnd-1 strain HT115 fed anti-hlh-1 2% fix plate a",
+ "creation_date": "2009-08-31",
+ "cell_line": null,
+ "library_species": 3,
+ "library_type": 1,
+ "made_by": "Lorian",
"affiliations": [
1
- ],
- "replicate": 1,
- "condition": null,
- "hidden": false,
- "stopping_point": "1Aa",
- "tags": [],
- "made_for": "",
- "amplified_from_sample": 11051,
- "notes": "8/26/2009 14:46:56\tColor: Purple",
- "undiluted_concentration": "1.47",
- "successful_pM": null,
- "experiment_type": 2,
+ ],
+ "replicate": 1,
+ "condition": null,
+ "hidden": false,
+ "stopping_point": "1Aa",
+ "tags": [],
+ "made_for": "",
+ "amplified_from_sample": 11051,
+ "notes": "8/26/2009 14:46:56\tColor: Purple",
+ "undiluted_concentration": "1.47",
+ "successful_pM": null,
+ "experiment_type": 2,
"antibody": null
}
- },
+ },
{"pk": 1190, "model": "experiments.lane",
"fields": {
"comment": "",
}
},
{
- "pk": "11056",
- "model": "samples.library",
+ "pk": "11056",
+ "model": "samples.library",
"fields": {
- "ten_nM_dilution": false,
- "gel_cut_size": 225,
- "library_name": "HNDM3 HLH hnd-1 strain mex-3 fed anti-hlh-1 2% fix plate a",
- "creation_date": "2009-08-31",
- "cell_line": null,
- "library_species": 3,
- "library_type": 1,
- "made_by": "Lorian",
+ "ten_nM_dilution": false,
+ "gel_cut_size": 225,
+ "library_name": "HNDM3 HLH hnd-1 strain mex-3 fed anti-hlh-1 2% fix plate a",
+ "creation_date": "2009-08-31",
+ "cell_line": null,
+ "library_species": 3,
+ "library_type": 1,
+ "made_by": "Lorian",
"affiliations": [
2
- ],
- "replicate": 1,
- "condition": null,
- "hidden": false,
- "stopping_point": "1Aa",
- "tags": [],
- "made_for": "",
- "amplified_from_sample": 11053,
- "notes": "8/26/2009 14:46:56\tColor: Black",
- "undiluted_concentration": "1.42",
- "successful_pM": null,
- "experiment_type": 2,
+ ],
+ "replicate": 1,
+ "condition": null,
+ "hidden": false,
+ "stopping_point": "1Aa",
+ "tags": [],
+ "made_for": "",
+ "amplified_from_sample": 11053,
+ "notes": "8/26/2009 14:46:56\tColor: Black",
+ "undiluted_concentration": "1.42",
+ "successful_pM": null,
+ "experiment_type": 2,
"antibody": null
}
- },
+ },
{"pk": 1191, "model": "experiments.lane",
"fields": {
"comment": "",
"lane_number": 7,
"pM": "7"
}
- },
+ },
{
- "pk": "11057",
- "model": "samples.library",
+ "pk": "11057",
+ "model": "samples.library",
"fields": {
- "ten_nM_dilution": false,
- "gel_cut_size": 225,
- "library_name": "HNDM3 4H8 hnd-1 strain mex-3 fed 4H8 2% fix plate a",
- "creation_date": "2009-08-31",
- "cell_line": null,
- "library_species": 3,
- "library_type": 1,
- "made_by": "Lorian",
+ "ten_nM_dilution": false,
+ "gel_cut_size": 225,
+ "library_name": "HNDM3 4H8 hnd-1 strain mex-3 fed 4H8 2% fix plate a",
+ "creation_date": "2009-08-31",
+ "cell_line": null,
+ "library_species": 3,
+ "library_type": 1,
+ "made_by": "Lorian",
"affiliations": [
3
- ],
- "replicate": 1,
- "condition": null,
- "hidden": false,
- "stopping_point": "1Aa",
- "tags": [],
- "made_for": "",
- "amplified_from_sample": 11054,
- "notes": "8/26/2009 14:46:56\tColor: Orange.",
- "undiluted_concentration": "1.3",
- "successful_pM": null,
- "experiment_type": 2,
+ ],
+ "replicate": 1,
+ "condition": null,
+ "hidden": false,
+ "stopping_point": "1Aa",
+ "tags": [],
+ "made_for": "",
+ "amplified_from_sample": 11054,
+ "notes": "8/26/2009 14:46:56\tColor: Orange.",
+ "undiluted_concentration": "1.3",
+ "successful_pM": null,
+ "experiment_type": 2,
"antibody": null
}
- },
+ },
{"pk": 1192, "model": "experiments.lane",
"fields": {
"comment": "",
"lane_number": 8,
"pM": "7"
}
- },
+ },
{
- "pk": "11065",
- "model": "samples.library",
+ "pk": "11065",
+ "model": "samples.library",
"fields": {
- "ten_nM_dilution": false,
- "gel_cut_size": 300,
- "library_name": "Paired ends 105 Kuntz PDM3",
- "creation_date": "2009-09-01",
- "cell_line": 1,
- "library_species": 3,
- "library_type": 2,
- "made_by": "Brian Williams",
+ "ten_nM_dilution": false,
+ "gel_cut_size": 300,
+ "library_name": "Paired ends 105 Kuntz PDM3",
+ "creation_date": "2009-09-01",
+ "cell_line": 1,
+ "library_species": 3,
+ "library_type": 2,
+ "made_by": "Brian Williams",
"affiliations": [
4
- ],
- "replicate": 1,
- "condition": 1,
- "hidden": false,
- "stopping_point": "1Aa",
- "tags": [],
- "made_for": "Brian Williams",
- "amplified_from_sample": null,
- "notes": "300 bp gel fragment, Amicon filtered\r\nnanodrop: 30.5",
- "undiluted_concentration": "2.47",
- "successful_pM": null,
- "experiment_type": 4,
+ ],
+ "replicate": 1,
+ "condition": 1,
+ "hidden": false,
+ "stopping_point": "1Aa",
+ "tags": [],
+ "made_for": "Brian Williams",
+ "amplified_from_sample": null,
+ "notes": "300 bp gel fragment, Amicon filtered\r\nnanodrop: 30.5",
+ "undiluted_concentration": "2.47",
+ "successful_pM": null,
+ "experiment_type": 4,
"antibody": null
}
- },
+ },
{"pk": 151, "model": "experiments.flowcell",
"fields": {
"paired_end": false,
"lane_number": 1,
"pM": "7"
}
- },
+ },
{"pk": 1178, "model": "experiments.lane",
"fields": {
"comment": "",
"lane_number": 2,
"pM": "7"
}
- },
+ },
{
- "pk": "11036",
- "model": "samples.library",
+ "pk": "11036",
+ "model": "samples.library",
"fields": {
- "ten_nM_dilution": false,
- "gel_cut_size": 300,
- "library_name": "Paired ends 96 Kuntz_PDE1",
- "creation_date": "2009-08-25",
- "cell_line": 1,
- "library_species": 3,
- "library_type": 2,
- "made_by": "Brian Williams",
+ "ten_nM_dilution": false,
+ "gel_cut_size": 300,
+ "library_name": "Paired ends 96 Kuntz_PDE1",
+ "creation_date": "2009-08-25",
+ "cell_line": 1,
+ "library_species": 3,
+ "library_type": 2,
+ "made_by": "Brian Williams",
"affiliations": [
5
- ],
- "replicate": 1,
- "condition": 1,
- "hidden": false,
- "stopping_point": "1Aa",
- "tags": [],
- "made_for": "Brian Williams",
- "amplified_from_sample": null,
- "notes": "fragment size = 300 bp",
- "undiluted_concentration": "30.6",
- "successful_pM": null,
- "experiment_type": 4,
+ ],
+ "replicate": 1,
+ "condition": 1,
+ "hidden": false,
+ "stopping_point": "1Aa",
+ "tags": [],
+ "made_for": "Brian Williams",
+ "amplified_from_sample": null,
+ "notes": "fragment size = 300 bp",
+ "undiluted_concentration": "30.6",
+ "successful_pM": null,
+ "experiment_type": 4,
"antibody": null
}
- },
+ },
{
- "pk": "11034",
- "model": "samples.library",
+ "pk": "11034",
+ "model": "samples.library",
"fields": {
- "ten_nM_dilution": false,
- "gel_cut_size": 300,
- "library_name": "Paired ends 94 Gilberto_d3_denerv_LTA",
- "creation_date": "2009-08-25",
- "cell_line": 1,
- "library_species": 9,
- "library_type": 2,
- "made_by": "Brian Williams",
+ "ten_nM_dilution": false,
+ "gel_cut_size": 300,
+ "library_name": "Paired ends 94 Gilberto_d3_denerv_LTA",
+ "creation_date": "2009-08-25",
+ "cell_line": 1,
+ "library_species": 9,
+ "library_type": 2,
+ "made_by": "Brian Williams",
"affiliations": [
1
- ],
- "replicate": 1,
- "condition": 1,
- "hidden": false,
- "stopping_point": "1Aa",
- "tags": [],
- "made_for": "Brian Williams",
- "amplified_from_sample": null,
- "notes": "fragment size = 300 bp",
- "undiluted_concentration": "27",
- "successful_pM": null,
- "experiment_type": 4,
+ ],
+ "replicate": 1,
+ "condition": 1,
+ "hidden": false,
+ "stopping_point": "1Aa",
+ "tags": [],
+ "made_for": "Brian Williams",
+ "amplified_from_sample": null,
+ "notes": "fragment size = 300 bp",
+ "undiluted_concentration": "27",
+ "successful_pM": null,
+ "experiment_type": 4,
"antibody": null
}
- },
+ },
{
- "pk": "11044",
- "model": "samples.library",
+ "pk": "12044",
+ "model": "samples.library",
"fields": {
- "ten_nM_dilution": false,
- "gel_cut_size": 225,
- "library_name": "p300 60h C2 FA KF 12/22/8 a",
- "creation_date": "2009-08-26",
- "cell_line": null,
- "library_species": 9,
- "library_type": 1,
- "made_by": "Lorian",
+ "ten_nM_dilution": false,
+ "gel_cut_size": 225,
+ "library_name": "Pooled Indexed Test",
+ "creation_date": "2009-08-26",
+ "cell_line": null,
+ "library_species": 9,
+ "library_type": 5,
+ "multiplex_id": "1,2,3",
+ "made_by": "Lorian",
"affiliations": [
2
- ],
- "replicate": 1,
- "condition": null,
- "hidden": false,
- "stopping_point": "2A",
- "tags": [],
- "made_for": "",
- "amplified_from_sample": 11043,
- "notes": "8/21/2009 11:57:54\tColor: Orange",
- "undiluted_concentration": "22.4",
- "successful_pM": null,
- "experiment_type": 2,
+ ],
+ "replicate": 1,
+ "condition": null,
+ "hidden": false,
+ "stopping_point": "2A",
+ "tags": [],
+ "made_for": "",
+ "amplified_from_sample": 11043,
+ "notes": "8/21/2009 11:57:54\tColor: Orange",
+ "undiluted_concentration": "22.4",
+ "successful_pM": null,
+ "experiment_type": 2,
"antibody": null
}
- },
+ },
+ {
+ "pk": "11045",
+ "model": "samples.library",
+ "fields": {
+ "ten_nM_dilution": false,
+ "gel_cut_size": 225,
+ "library_name": "Simple Indexed Test",
+ "creation_date": "2009-08-26",
+ "cell_line": null,
+ "library_species": 9,
+ "library_type": 5,
+ "multiplex_id": "1",
+ "made_by": "Lorian",
+ "affiliations": [
+ 2
+ ],
+ "replicate": 2,
+ "condition": null,
+ "hidden": false,
+ "stopping_point": "2A",
+ "tags": [],
+ "made_for": "",
+ "amplified_from_sample": 11043,
+ "notes": "8/21/2009 11:57:54\tColor: Orange",
+ "undiluted_concentration": "22.4",
+ "successful_pM": null,
+ "experiment_type": 2,
+ "antibody": null
+ }
+ },
{"pk": 1179,
"model": "experiments.lane",
"fields": {
"comment": "",
- "library": "11044",
+ "library": "12044",
+ "cluster_estimate": 196000,
+ "flowcell": 151,
+ "lane_number": 3,
+ "pM": "7"
+ }
+ },
+ {"pk": 1279,
+ "model": "experiments.lane",
+ "fields": {
+ "comment": "",
+ "library": "11045",
"cluster_estimate": 196000,
"flowcell": 151,
"lane_number": 3,
"pM": "7"
}
- },
+ },
{
- "pk": "11044",
- "model": "samples.library",
+ "pk": "11044",
+ "model": "samples.library",
"fields": {
- "ten_nM_dilution": false,
- "gel_cut_size": 225,
- "library_name": "p300 60h C2 FA KF 12/22/8 a",
- "creation_date": "2009-08-26",
- "cell_line": null,
- "library_species": 9,
- "library_type": 1,
- "made_by": "Lorian",
+ "ten_nM_dilution": false,
+ "gel_cut_size": 225,
+ "library_name": "p300 60h C2 FA KF 12/22/8 a",
+ "creation_date": "2009-08-26",
+ "cell_line": null,
+ "library_species": 9,
+ "library_type": 1,
+ "made_by": "Lorian",
"affiliations": [
3
- ],
- "replicate": 1,
- "condition": null,
- "hidden": false,
- "stopping_point": "2A",
- "tags": [],
- "made_for": "",
- "amplified_from_sample": 11043,
- "notes": "8/21/2009 11:57:54\tColor: Orange.",
- "undiluted_concentration": "22.4",
- "successful_pM": null,
- "experiment_type": 2,
+ ],
+ "replicate": 1,
+ "condition": null,
+ "hidden": false,
+ "stopping_point": "2A",
+ "tags": [],
+ "made_for": "",
+ "amplified_from_sample": 11043,
+ "notes": "8/21/2009 11:57:54\tColor: Orange.",
+ "undiluted_concentration": "22.4",
+ "successful_pM": null,
+ "experiment_type": 2,
"antibody": null
}
- },
+ },
{"pk": 1180, "model": "experiments.lane",
"fields": {
"comment": "",
"lane_number": 4,
"pM": "7"
}
- },
+ },
{
- "pk": "11047",
- "model": "samples.library",
+ "pk": "11047",
+ "model": "samples.library",
"fields": {
- "ten_nM_dilution": false,
- "gel_cut_size": 250,
- "library_name": "FLDN1 7/8/9 anti-TriMeH3K27 chip B6 a",
- "creation_date": "2009-08-26",
- "cell_line": null,
- "library_species": 9,
- "library_type": 1,
- "made_by": "Lorian",
+ "ten_nM_dilution": false,
+ "gel_cut_size": 250,
+ "library_name": "FLDN1 7/8/9 anti-TriMeH3K27 chip B6 a",
+ "creation_date": "2009-08-26",
+ "cell_line": null,
+ "library_species": 9,
+ "library_type": 1,
+ "made_by": "Lorian",
"affiliations": [
4
- ],
- "replicate": 1,
- "condition": null,
- "hidden": false,
- "stopping_point": "2A",
- "tags": [],
- "made_for": "",
- "amplified_from_sample": 11046,
- "notes": "8/21/2009 11:57:54\tColor: Green",
- "undiluted_concentration": "24.9",
- "successful_pM": null,
- "experiment_type": 2,
+ ],
+ "replicate": 1,
+ "condition": null,
+ "hidden": false,
+ "stopping_point": "2A",
+ "tags": [],
+ "made_for": "",
+ "amplified_from_sample": 11046,
+ "notes": "8/21/2009 11:57:54\tColor: Green",
+ "undiluted_concentration": "24.9",
+ "successful_pM": null,
+ "experiment_type": 2,
"antibody": null
}
- },
+ },
{"pk": 1181, "model": "experiments.lane",
"fields": {
"comment": "",
"lane_number": 5,
"pM": "7"
}
- },
+ },
{
- "pk": "11055",
- "model": "samples.library",
+ "pk": "11055",
+ "model": "samples.library",
"fields": {
- "ten_nM_dilution": false,
- "gel_cut_size": 225,
- "library_name": "HNDHT 4H8 hnd-1 strain HT115 fed 4H8 2% fix plate a",
- "creation_date": "2009-08-31",
- "cell_line": null,
- "library_species": 3,
- "library_type": 1,
- "made_by": "Lorian",
+ "ten_nM_dilution": false,
+ "gel_cut_size": 225,
+ "library_name": "HNDHT 4H8 hnd-1 strain HT115 fed 4H8 2% fix plate a",
+ "creation_date": "2009-08-31",
+ "cell_line": null,
+ "library_species": 3,
+ "library_type": 1,
+ "made_by": "Lorian",
"affiliations": [
5
- ],
- "replicate": 1,
- "condition": null,
- "hidden": false,
- "stopping_point": "1Aa",
- "tags": [],
- "made_for": "",
- "amplified_from_sample": 11052,
- "notes": "8/26/2009 14:46:56\tColor: White.",
- "undiluted_concentration": "2.17",
- "successful_pM": null,
- "experiment_type": 2,
+ ],
+ "replicate": 1,
+ "condition": null,
+ "hidden": false,
+ "stopping_point": "1Aa",
+ "tags": [],
+ "made_for": "",
+ "amplified_from_sample": 11052,
+ "notes": "8/26/2009 14:46:56\tColor: White.",
+ "undiluted_concentration": "2.17",
+ "successful_pM": null,
+ "experiment_type": 2,
"antibody": null
}
- },
+ },
{"pk": 1182, "model": "experiments.lane",
"fields": {
"comment": "",
"lane_number": 6,
"pM": "7"
}
- },
+ },
{
- "pk": "11067",
- "model": "samples.library",
+ "pk": "11067",
+ "model": "samples.library",
"fields": {
- "ten_nM_dilution": false,
- "gel_cut_size": 325,
- "library_name": "Paired End SP-BAC Barcoding test 250-300 bp",
- "creation_date": "2009-09-03",
- "cell_line": 1,
- "library_species": 10,
- "library_type": 2,
- "made_by": "Igor",
+ "ten_nM_dilution": false,
+ "gel_cut_size": 325,
+ "library_name": "Paired End SP-BAC Barcoding test 250-300 bp",
+ "creation_date": "2009-09-03",
+ "cell_line": 1,
+ "library_species": 10,
+ "library_type": 2,
+ "made_by": "Igor",
"affiliations": [
1
- ],
- "replicate": 1,
- "condition": 1,
- "hidden": false,
- "stopping_point": "Done",
- "tags": [],
- "made_for": "Andy Cameron",
- "amplified_from_sample": null,
- "notes": "12 SP BACs",
- "undiluted_concentration": "1.45",
- "successful_pM": null,
- "experiment_type": 8,
+ ],
+ "replicate": 1,
+ "condition": 1,
+ "hidden": false,
+ "stopping_point": "Done",
+ "tags": [],
+ "made_for": "Andy Cameron",
+ "amplified_from_sample": null,
+ "notes": "12 SP BACs",
+ "undiluted_concentration": "1.45",
+ "successful_pM": null,
+ "experiment_type": 8,
"antibody": null
}
- },
+ },
{"pk": 1183, "model": "experiments.lane",
"fields": {
"comment": "",
"lane_number": 7,
"pM": "7"
}
- },
+ },
{
- "pk": "11069",
- "model": "samples.library",
+ "pk": "11069",
+ "model": "samples.library",
"fields": {
- "ten_nM_dilution": false,
- "gel_cut_size": 300,
- "library_name": "Paired End AG-3d-1 AG domain of floral meristem day 3, rep 1",
- "creation_date": "2009-09-02",
- "cell_line": null,
- "library_species": 6,
- "library_type": 2,
- "made_by": "Yuling Jiao",
+ "ten_nM_dilution": false,
+ "gel_cut_size": 300,
+ "library_name": "Paired End AG-3d-1 AG domain of floral meristem day 3, rep 1",
+ "creation_date": "2009-09-02",
+ "cell_line": null,
+ "library_species": 6,
+ "library_type": 2,
+ "made_by": "Yuling Jiao",
"affiliations": [
2
- ],
- "replicate": 1,
- "condition": null,
- "hidden": false,
- "stopping_point": "Done",
- "tags": [],
- "made_for": "",
- "amplified_from_sample": null,
- "notes": "nanodrop: Xng/ul.",
- "undiluted_concentration": "18.3",
- "successful_pM": null,
- "experiment_type": 4,
+ ],
+ "replicate": 1,
+ "condition": null,
+ "hidden": false,
+ "stopping_point": "Done",
+ "tags": [],
+ "made_for": "",
+ "amplified_from_sample": null,
+ "notes": "nanodrop: Xng/ul.",
+ "undiluted_concentration": "18.3",
+ "successful_pM": null,
+ "experiment_type": 4,
"antibody": null
}
- },
+ },
{"pk": 1184, "model": "experiments.lane",
"fields": {
"comment": "",
}
},
{
- "pk": "11070",
- "model": "samples.library",
+ "pk": "11070",
+ "model": "samples.library",
"fields": {
- "ten_nM_dilution": false,
- "gel_cut_size": 300,
- "library_name": "Paired End AG-5d-1 AG domain of floral meristem day 5, rep 1",
- "creation_date": "2009-09-02",
- "cell_line": null,
- "library_species": 6,
- "library_type": 2,
- "made_by": "Yuling Jiao",
+ "ten_nM_dilution": false,
+ "gel_cut_size": 300,
+ "library_name": "Paired End AG-5d-1 AG domain of floral meristem day 5, rep 1",
+ "creation_date": "2009-09-02",
+ "cell_line": null,
+ "library_species": 6,
+ "library_type": 2,
+ "made_by": "Yuling Jiao",
"affiliations": [
3
- ],
- "replicate": 1,
- "condition": null,
- "hidden": false,
- "stopping_point": "Done",
- "tags": [],
- "made_for": "",
- "amplified_from_sample": null,
- "notes": "nanodrop: 40ng/ul\r\nCalibrated qbit with standards.\r\nMeasured 2ul library with qbit using HS kit.\r\n",
- "undiluted_concentration": "20.3",
- "successful_pM": null,
- "experiment_type": 4,
+ ],
+ "replicate": 1,
+ "condition": null,
+ "hidden": false,
+ "stopping_point": "Done",
+ "tags": [],
+ "made_for": "",
+ "amplified_from_sample": null,
+ "notes": "nanodrop: 40ng/ul\r\nCalibrated qbit with standards.\r\nMeasured 2ul library with qbit using HS kit.\r\n",
+ "undiluted_concentration": "20.3",
+ "successful_pM": null,
+ "experiment_type": 4,
"antibody": null
}
},
- {"pk": 200, "model": "experiments.flowcell",
+ {"pk": 200, "model": "experiments.flowcell",
"fields": {
- "paired_end": true,
- "run_date": "2007-09-27 22:12:13",
- "read_length": 36,
+ "paired_end": true,
+ "run_date": "2007-09-27 22:12:13",
+ "read_length": 36,
"notes": "",
"advanced_run": false,
"control_lane": 2,
from htsworkflow.pipelines.test.simulate_runfolder import TESTDATA_DIR
-LANE_SET = range(1,9)
+LANE_SET = range(1, 9)
+
class ExperimentsTestCases(TestCase):
fixtures = ['test_flowcells.json']
runxml = 'run_FC12150_2007-09-27.xml'
shutil.copy(os.path.join(TESTDATA_DIR, runxml),
os.path.join(self.fc1_dir, runxml))
- for i in range(1,9):
+ for i in range(1, 9):
shutil.copy(
os.path.join(TESTDATA_DIR,
'woldlab_070829_USI-EAS44_0017_FC11055_1.srf'),
os.path.join(self.fc1_dir,
- 'woldlab_070829_SERIAL_FC12150_%d.srf' %(i,))
+ 'woldlab_070829_SERIAL_FC12150_%d.srf' % (i, ))
)
-
+
self.fc2_dir = os.path.join(self.tempdir, '42JTNAAXX')
os.mkdir(self.fc2_dir)
os.mkdir(os.path.join(self.fc2_dir, 'C1-25'))
fc_django = models.FlowCell.objects.get(flowcell_id=fc_id)
self.failUnlessEqual(fc_dict['flowcell_id'], fc_id)
self.failUnlessEqual(fc_django.flowcell_id, fc_id)
- self.failUnlessEqual(fc_dict['sequencer'], fc_django.sequencer.name)
- self.failUnlessEqual(fc_dict['read_length'], fc_django.read_length)
+ self.failUnlessEqual(fc_dict['sequencer'],
+ fc_django.sequencer.name)
+ self.failUnlessEqual(fc_dict['read_length'],
+ fc_django.read_length)
self.failUnlessEqual(fc_dict['notes'], fc_django.notes)
- self.failUnlessEqual(fc_dict['cluster_station'], fc_django.cluster_station.name)
+ self.failUnlessEqual(fc_dict['cluster_station'],
+ fc_django.cluster_station.name)
for lane in fc_django.lane_set.all():
- lane_dict = fc_dict['lane_set'][lane.lane_number]
- self.failUnlessEqual(lane_dict['cluster_estimate'], lane.cluster_estimate)
+ lane_contents = fc_dict['lane_set'][lane.lane_number]
+ lane_dict = multi_lane_to_dict(lane_contents)[lane.library_id]
+ self.failUnlessEqual(lane_dict['cluster_estimate'],
+ lane.cluster_estimate)
self.failUnlessEqual(lane_dict['comment'], lane.comment)
- self.failUnlessEqual(lane_dict['flowcell'], lane.flowcell.flowcell_id)
- self.failUnlessEqual(lane_dict['lane_number'], lane.lane_number)
- self.failUnlessEqual(lane_dict['library_name'], lane.library.library_name)
+ self.failUnlessEqual(lane_dict['flowcell'],
+ lane.flowcell.flowcell_id)
+ self.failUnlessEqual(lane_dict['lane_number'],
+ lane.lane_number)
+ self.failUnlessEqual(lane_dict['library_name'],
+ lane.library.library_name)
self.failUnlessEqual(lane_dict['library_id'], lane.library.id)
- self.failUnlessAlmostEqual(float(lane_dict['pM']), float(lane.pM))
+ self.failUnlessAlmostEqual(float(lane_dict['pM']),
+ float(lane.pM))
self.failUnlessEqual(lane_dict['library_species'],
- lane.library.library_species.scientific_name)
-
- response = self.client.get('/experiments/config/%s/json' % (fc_id,), apidata)
+ lane.library.library_species.scientific_name)
+
+ flowcell_url = '/experiments/config/%s/json'
+ response = self.client.get(flowcell_url % (fc_id,), apidata)
# strptime isoformat string = '%Y-%m-%dT%H:%M:%S'
fc_json = json.loads(response.content)
self.failUnlessEqual(fc_json['flowcell_id'], fc_id)
- self.failUnlessEqual(fc_json['sequencer'], fc_django.sequencer.name)
+ self.failUnlessEqual(fc_json['sequencer'],
+ fc_django.sequencer.name)
self.failUnlessEqual(fc_json['read_length'], fc_django.read_length)
self.failUnlessEqual(fc_json['notes'], fc_django.notes)
- self.failUnlessEqual(fc_json['cluster_station'], fc_django.cluster_station.name)
-
+ self.failUnlessEqual(fc_json['cluster_station'],
+ fc_django.cluster_station.name)
for lane in fc_django.lane_set.all():
- lane_dict = fc_json['lane_set'][unicode(lane.lane_number)]
- self.failUnlessEqual(lane_dict['cluster_estimate'], lane.cluster_estimate)
+ lane_contents = fc_json['lane_set'][unicode(lane.lane_number)]
+ lane_dict = multi_lane_to_dict(lane_contents)[lane.library_id]
+
+ self.failUnlessEqual(lane_dict['cluster_estimate'],
+ lane.cluster_estimate)
self.failUnlessEqual(lane_dict['comment'], lane.comment)
- self.failUnlessEqual(lane_dict['flowcell'], lane.flowcell.flowcell_id)
- self.failUnlessEqual(lane_dict['lane_number'], lane.lane_number)
- self.failUnlessEqual(lane_dict['library_name'], lane.library.library_name)
+ self.failUnlessEqual(lane_dict['flowcell'],
+ lane.flowcell.flowcell_id)
+ self.failUnlessEqual(lane_dict['lane_number'],
+ lane.lane_number)
+ self.failUnlessEqual(lane_dict['library_name'],
+ lane.library.library_name)
self.failUnlessEqual(lane_dict['library_id'], lane.library.id)
- self.failUnlessAlmostEqual(float(lane_dict['pM']), float(lane.pM))
+ self.failUnlessAlmostEqual(float(lane_dict['pM']),
+ float(lane.pM))
self.failUnlessEqual(lane_dict['library_species'],
- lane.library.library_species.scientific_name)
+ lane.library.library_species.scientific_name)
def test_invalid_flowcell(self):
"""
Make sure we get a 404 if we request an invalid flowcell ID
"""
- response = self.client.get('/experiments/config/nottheone/json', apidata)
+ flowcell_url = '/experiments/config/nottheone/json'
+ response = self.client.get(flowcell_url, apidata)
self.failUnlessEqual(response.status_code, 404)
def test_no_key(self):
def test_library_id(self):
"""
- Library IDs should be flexible, so make sure we can retrive a non-numeric ID
+ Library IDs should be flexible, retrive a non-numeric ID
"""
- response = self.client.get('/experiments/config/FC12150/json', apidata)
+ flowcell_url = '/experiments/config/FC12150/json'
+ response = self.client.get(flowcell_url, apidata)
self.failUnlessEqual(response.status_code, 200)
flowcell = json.loads(response.content)
- self.failUnlessEqual(flowcell['lane_set']['3']['library_id'], 'SL039')
+ lane_contents = flowcell['lane_set']['3']
+ lane_library = lane_contents[0]
+ self.failUnlessEqual(lane_library['library_id'], 'SL039')
response = self.client.get('/samples/library/SL039/json', apidata)
self.failUnlessEqual(response.status_code, 200)
Library's have IDs, libraries also have primary keys,
we eventually had enough libraries that the drop down combo box was too
- hard to filter through, unfortnately we want a field that uses our library
- id and not the internal primary key, and raw_id_field uses primary keys.
+ hard to filter through, unfortnately we want a field that uses our
+ library id and not the internal primary key, and raw_id_field uses
+ primary keys.
- This tests to make sure that the value entered in the raw library id field matches
- the library id looked up.
+ This tests to make sure that the value entered in the raw library id
+ field matches the library id looked up.
"""
- expected_ids = [u'10981',u'11016',u'SL039',u'11060',
- u'11061',u'11062',u'11063',u'11064']
+ expected_ids = [u'10981', u'11016', u'SL039', u'11060',
+ u'11061', u'11062', u'11063', u'11064']
self.client.login(username='supertest', password='BJOKL5kAj6aFZ6A5')
response = self.client.get('/admin/experiments/flowcell/153/')
soup = BeautifulSoup(response.content)
- for i in range(0,8):
+ for i in range(0, 8):
input_field = soup.find(id='id_lane_set-%d-library' % (i,))
library_field = input_field.findNext('strong')
- library_id, library_name = library_field.string.split(':')
+ library_id, library_name = library_field.text.split(':')
# strip leading '#' sign from name
library_id = library_id[1:]
self.failUnlessEqual(library_id, expected_ids[i])
self.failUnlessEqual(fc_response.status_code, 200)
fc_lane_response = self.client.get('/flowcell/30012AAXX/8/')
self.failUnlessEqual(fc_lane_response.status_code, 200)
-
-
+
+ def test_pooled_multiplex_id(self):
+ fc_dict = experiments.flowcell_information('42JU1AAXX')
+ lane_contents = fc_dict['lane_set'][3]
+ self.assertEqual(len(lane_contents), 2)
+ lane_dict = multi_lane_to_dict(lane_contents)
+
+ self.assertEqual(lane_dict['12044']['index_sequence'],
+ {u'1': u'ATCACG',
+ u'2': u'CGATGT',
+ u'3': u'TTAGGC'})
+ self.assertEqual(lane_dict['11045']['index_sequence'],
+ {u'1': u'ATCACG'})
def test_lanes_for(self):
"""
lanes = experiments.lanes_for(user)
self.failUnlessEqual(len(lanes), 5)
- response = self.client.get('/experiments/lanes_for/%s/json' % (user,), apidata)
+ flowcell_url = '/experiments/lanes_for/%s/json'
+ response = self.client.get(flowcell_url % (user,), apidata)
lanes_json = json.loads(response.content)
self.failUnlessEqual(len(lanes), len(lanes_json))
for i in range(len(lanes)):
self.failUnlessEqual(lanes[i]['comment'], lanes_json[i]['comment'])
- self.failUnlessEqual(lanes[i]['lane_number'], lanes_json[i]['lane_number'])
- self.failUnlessEqual(lanes[i]['flowcell'], lanes_json[i]['flowcell'])
- self.failUnlessEqual(lanes[i]['run_date'], lanes_json[i]['run_date'])
-
+ self.failUnlessEqual(lanes[i]['lane_number'],
+ lanes_json[i]['lane_number'])
+ self.failUnlessEqual(lanes[i]['flowcell'],
+ lanes_json[i]['flowcell'])
+ self.failUnlessEqual(lanes[i]['run_date'],
+ lanes_json[i]['run_date'])
+
def test_lanes_for_no_lanes(self):
"""
- Do we get something meaningful back when the user isn't attached to anything?
+ What happens to user who haven't submitted anything
"""
user = 'supertest'
lanes = experiments.lanes_for(user)
self.failUnlessEqual(len(lanes), 0)
- response = self.client.get('/experiments/lanes_for/%s/json' % (user,), apidata)
+ url = '/experiments/lanes_for/%s/json'
+ response = self.client.get(url % (user,), apidata)
lanes_json = json.loads(response.content)
def test_lanes_for_no_user(self):
user = 'not a real user'
self.failUnlessRaises(ObjectDoesNotExist, experiments.lanes_for, user)
- response = self.client.get('/experiments/lanes_for/%s/json' % (user,), apidata)
+ url = '/experiments/lanes_for/%s/json'
+ response = self.client.get(url % (user,), apidata)
self.failUnlessEqual(response.status_code, 404)
-
def test_raw_data_dir(self):
"""Raw data path generator check"""
flowcell_id = self.fc1_id
raw_dir = os.path.join(settings.RESULT_HOME_DIR, flowcell_id)
-
+
fc = models.FlowCell.objects.get(flowcell_id=flowcell_id)
self.failUnlessEqual(fc.get_raw_data_directory(), raw_dir)
fc.flowcell_id = flowcell_id + " (failed)"
self.failUnlessEqual(fc.get_raw_data_directory(), raw_dir)
-
def test_data_run_import(self):
srf_file_type = models.FileType.objects.get(name='SRF')
runxml_file_type = models.FileType.objects.get(name='run_xml')
lane_files = run.lane_files()
self.failUnlessEqual(lane_files[4]['srf'], srf4)
- runxml= result_dict['FC12150/C1-37/run_FC12150_2007-09-27.xml']
+ runxml = result_dict['FC12150/C1-37/run_FC12150_2007-09-27.xml']
self.failUnlessEqual(runxml.file_type, runxml_file_type)
self.failUnlessEqual(runxml.library_id, None)
-
def test_read_result_file(self):
"""make sure we can return a result file
flowcell_id = self.fc1_id
flowcell = models.FlowCell.objects.get(flowcell_id=flowcell_id)
flowcell.update_data_runs()
-
- #self.client.login(username='supertest', password='BJOKL5kAj6aFZ6A5')
+
+ #self.client.login(username='supertest', password='BJOKL5kAj6aFZ6A5')
result_files = flowcell.datarun_set.all()[0].datafile_set.all()
for f in result_files:
- url = '/experiments/file/%s' % ( f.random_key,)
+ url = '/experiments/file/%s' % (f.random_key, )
response = self.client.get(url)
self.failUnlessEqual(response.status_code, 200)
mimetype = f.file_type.mimetype
if mimetype is None:
mimetype = 'application/octet-stream'
-
+
self.failUnlessEqual(mimetype, response['content-type'])
-
+
+
class TestFileType(TestCase):
def test_file_type_unicode(self):
file_type_objects = models.FileType.objects
file_type_object = file_type_objects.get(name=name)
self.failUnlessEqual(u"<FileType: QSEQ tarfile>",
unicode(file_type_object))
-
+
+
class TestFileType(TestCase):
def test_find_file_type(self):
file_type_objects = models.FileType.objects
'QSEQ tarfile', 7, 1),
('woldlab_091005_HWUSI-EAS627_0010_42JT2AAXX_1.srf',
'SRF', 1, None),
- ('s_1_eland_extended.txt.bz2','ELAND Extended', 1, None),
+ ('s_1_eland_extended.txt.bz2', 'ELAND Extended', 1, None),
('s_7_eland_multi.txt.bz2', 'ELAND Multi', 7, None),
- ('s_3_eland_result.txt.bz2','ELAND Result', 3, None),
+ ('s_3_eland_result.txt.bz2', 'ELAND Result', 3, None),
('s_1_export.txt.bz2','ELAND Export', 1, None),
('s_1_percent_call.png', 'IVC Percent Call', 1, None),
('s_2_percent_base.png', 'IVC Percent Base', 2, None),
'QSEQ tarfile', 7, 1),
('foo/woldlab_091005_HWUSI-EAS627_0010_42JT2AAXX_1.srf',
'SRF', 1, None),
- ('../s_1_eland_extended.txt.bz2','ELAND Extended', 1, None),
+ ('../s_1_eland_extended.txt.bz2', 'ELAND Extended', 1, None),
('/bleem/s_7_eland_multi.txt.bz2', 'ELAND Multi', 7, None),
- ('/qwer/s_3_eland_result.txt.bz2','ELAND Result', 3, None),
- ('/ty///1/s_1_export.txt.bz2','ELAND Export', 1, None),
+ ('/qwer/s_3_eland_result.txt.bz2', 'ELAND Result', 3, None),
+ ('/ty///1/s_1_export.txt.bz2', 'ELAND Export', 1, None),
('/help/s_1_percent_call.png', 'IVC Percent Call', 1, None),
('/bored/s_2_percent_base.png', 'IVC Percent Base', 2, None),
('/example1/s_3_percent_all.png', 'IVC Percent All', 3, None),
result = models.find_file_type_metadata_from_filename(filename)
self.failUnlessEqual(result['file_type'],
file_type_objects.get(name=typename))
- self.failUnlessEqual(result.get('lane',None), lane)
+ self.failUnlessEqual(result.get('lane', None), lane)
self.failUnlessEqual(result.get('end', None), end)
-
+
+
class TestEmailNotify(TestCase):
fixtures = ['test_flowcells.json']
self.client.login(username='test', password='BJOKL5kAj6aFZ6A5')
response = self.client.get('/experiments/started/153/')
self.failUnlessEqual(response.status_code, 302)
-
+
def test_started_email_logged_in_staff(self):
- self.client.login(username='admintest', password='BJOKL5kAj6aFZ6A5')
+ self.client.login(username='admintest', password='BJOKL5kAj6aFZ6A5')
response = self.client.get('/experiments/started/153/')
self.failUnlessEqual(response.status_code, 200)
def test_started_email_send(self):
- self.client.login(username='admintest', password='BJOKL5kAj6aFZ6A5')
+ self.client.login(username='admintest', password='BJOKL5kAj6aFZ6A5')
response = self.client.get('/experiments/started/153/')
self.failUnlessEqual(response.status_code, 200)
-
+
self.failUnless('pk1@example.com' in response.content)
self.failUnless('Lane #8 : (11064) Paired ends 104' in response.content)
- response = self.client.get('/experiments/started/153/', {'send':'1','bcc':'on'})
+ response = self.client.get('/experiments/started/153/',
+ {'send': '1','bcc': 'on'})
self.failUnlessEqual(response.status_code, 200)
self.failUnlessEqual(len(mail.outbox), 4)
for m in mail.outbox:
"""
Can we navigate between the flowcell and email forms properly?
"""
- self.client.login(username='supertest', password='BJOKL5kAj6aFZ6A5')
+ self.client.login(username='supertest', password='BJOKL5kAj6aFZ6A5')
response = self.client.get('/experiments/started/153/')
self.failUnlessEqual(response.status_code, 200)
self.failUnless(re.search('Flowcell FC12150', response.content))
# require that navigation back to the admin page exists
- self.failUnless(re.search('<a href="/admin/experiments/flowcell/153/">[^<]+</a>', response.content))
-
+ flowcell_a_re = '<a href="/admin/experiments/flowcell/153/">[^<]+</a>'
+ self.failUnless(re.search(flowcell_a_re, response.content))
+
+def multi_lane_to_dict(lane):
+ """Convert a list of lane entries into a dictionary indexed by library ID
+ """
+ return dict(((x['library_id'], x) for x in lane))
from django.utils.translation import ugettext_lazy as _
from django.forms import TextInput, Textarea
-from htsworkflow.frontend.samples.models import Antibody, Cellline, Condition, ExperimentType, HTSUser, LibraryType, Species, Affiliation, Library, Tag
+from htsworkflow.frontend.samples.models import \
+ Antibody, Cellline, Condition, ExperimentType, HTSUser, \
+ LibraryType, MultiplexIndex, Species, Affiliation, Library, Tag
from htsworkflow.frontend.experiments.models import Lane
from htsworkflow.frontend.inventory.models import PrinterTemplate
from htsworkflow.frontend.bcmagic.utils import print_zpl_socket
}),
)
- # some post 1.0.2 version of django has formfield_overrides
+ # some post 1.0.2 version of django has formfield_overrides
# which would replace this code with:
# formfield_overrids = {
# models.ManyToMany: { 'widget': widgets.FilteredSelectMultiple }
class HTSUserChangeForm(UserChangeForm):
class Meta:
model = HTSUser
-
+
class HTSUserOptions(UserAdmin):
form = HTSUserChangeForm
add_form = HTSUserCreationForm
model = Library
class LibraryTypeOptions(admin.ModelAdmin):
+ list_display = ['name', 'is_paired_end', 'can_multiplex']
model = LibraryType
+class MultiplexIndexOptions(admin.ModelAdmin):
+ model = MultiplexIndex
+ list_display = ['adapter_type', 'multiplex_id', 'sequence']
+
class LibraryOptions(admin.ModelAdmin):
class Media:
css = {
"all": ("css/wide_account_number.css",)
}
-
+
date_hierarchy = "creation_date"
save_as = True
save_on_top = True
list_display = (
'id',
'library_name',
- 'public',
+ 'index_sequence_text',
'affiliation',
'undiluted_concentration',
'gel_cut_size',
list_filter = (
'hidden',
'affiliations',
- 'library_species',
- 'experiment_type',
- 'made_by',
+ 'library_species',
+ 'experiment_type',
+ 'made_by',
'cell_line',
'stopping_point',)
list_display_links = ('id', 'library_name',)
(None, {
'fields': (
('id','library_name','hidden'),
- ('library_species', 'library_type', 'experiment_type'),
+ ('library_species', 'experiment_type'),
+ ('library_type', 'multiplex_id'),
)
}),
('Experiment Detail:', {
'classes': ('collapse',),
}),
('Creation Information:', {
- 'fields' : (('made_by', 'creation_date', 'stopping_point'),
- ('amplified_from_sample'),
- ('gel_cut_size', 'insert_size',
- 'undiluted_concentration'),
+ 'fields' : (('made_by', 'creation_date', 'stopping_point'),
+ ('amplified_from_sample'),
+ ('gel_cut_size', 'insert_size',
+ 'undiluted_concentration'),
('bioanalyzer_concentration','bioanalyzer_image_url'),
- ('bioanalyzer_summary'),
+ ('bioanalyzer_summary'),
('notes'))
}),
('Library/Project Affiliation:', {
LaneLibraryInline,
]
actions = ['action_print_library_labels']
-
+
def action_print_library_labels(self, request, queryset):
"""
Django action which prints labels for the selected set of labels from the
Django Admin interface.
"""
-
+
#Probably should ask if the user really meant to print all selected
# libraries if the count is above X. X=10 maybe?
-
+
# Grab the library template
#FIXME: Hardcoding library template name. Not a good idea... *sigh*.
EVIL_HARDCODED_LIBRARY_TEMPLATE_NAME = "Library"
-
+
try:
template = PrinterTemplate.objects.get(item_type__name=EVIL_HARDCODED_LIBRARY_TEMPLATE_NAME)
except PrinterTemplate.DoesNotExist:
self.message_user(request, "Could not find a library template with ItemType.name of '%s'" % \
(EVIL_HARDCODED_LIBRARY_TEMPLATE_NAME))
return
-
+
# ZPL Template
t = Template(template.template)
-
+
zpl_list = []
#Iterate over selected labels to print
for library in queryset.all():
-
+
# Django Template Context
c = Context({'library': library})
-
+
# Send rendered template to the printer that the template
# object has been attached to in the database.
zpl_list.append(t.render(c))
-
+
print_zpl_socket(zpl_list, host=template.printer.ip_address)
-
+
self.message_user(request, "%s labels printed." % (len(queryset)))
-
+
action_print_library_labels.short_description = "Print Labels"
def formfield_for_dbfield(self, db_field, **kwargs):
class TagOptions(admin.ModelAdmin):
list_display = ('tag_name', 'context')
- fieldsets = (
+ fieldsets = (
(None, {
'fields': ('tag_name', 'context')
}),
admin.site.register(ExperimentType, ExperimentTypeOptions)
#admin.site.register(HTSUser, HTSUserOptions)
admin.site.register(LibraryType, LibraryTypeOptions)
+admin.site.register(MultiplexIndex, MultiplexIndexOptions)
admin.site.register(Species, SpeciesOptions)
#admin.site.register(Tag, TagOptions)
"pk": 1,
"fields": {
"cellline_name": "Unknown",
- "notes": "Unknown"
+ "notes": "Unknown"
}
},
{
"pk": 2,
"fields": {
"cellline_name": "C2C12 Exponential",
- "notes": ""
+ "notes": ""
}
},
{
"pk": 3,
"fields": {
"cellline_name": "C2C12 60 hrs",
- "notes": "Unknown"
+ "notes": "Unknown"
}
},
{
"model": "samples.LibraryType",
"pk": 1,
"fields": {
- "name": "Single End"
+ "name": "Single End",
+ "can_multiplex": false,
+ "is_paired_end": false
}
},
{
"model": "samples.LibraryType",
"pk": 2,
"fields": {
- "name": "Paired End"
+ "name": "Paired End",
+ "can_multiplex": false,
+ "is_paired_end": true
+ }
+ },
+ {
+ "model": "samples.LibraryType",
+ "pk": 5,
+ "fields": {
+ "name": "Barcoded",
+ "can_multiplex": true,
+ "is_paired_end": true
}
},
{
"fields": {
"scientific_name": "Strongylocentrotus purpuratus"
}
+ },
+ {
+ "pk": 1,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 1,
+ "adapter_type": 8,
+ "sequence": "ATCACG"
+ }
+ },
+ {
+ "pk": 2,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 2,
+ "adapter_type": 8,
+ "sequence": "CGATGT"
+ }
+ },
+ {
+ "pk": 3,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 3,
+ "adapter_type": 8,
+ "sequence": "TTAGGC"
+ }
+ },
+ {
+ "pk": 4,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 4,
+ "adapter_type": 8,
+ "sequence": "TGACCA"
+ }
+ },
+ {
+ "pk": 5,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 5,
+ "adapter_type": 8,
+ "sequence": "ACAGTG"
+ }
+ },
+ {
+ "pk": 6,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 6,
+ "adapter_type": 8,
+ "sequence": "GCCAAT"
+ }
+ },
+ {
+ "pk": 7,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 7,
+ "adapter_type": 8,
+ "sequence": "CAGATC"
+ }
+ },
+ {
+ "pk": 8,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 8,
+ "adapter_type": 8,
+ "sequence": "ACTTGA"
+ }
+ },
+ {
+ "pk": 9,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 9,
+ "adapter_type": 8,
+ "sequence": "GATCAG"
+ }
+ },
+ {
+ "pk": 10,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 10,
+ "adapter_type": 8,
+ "sequence": "TAGCTT"
+ }
+ },
+ {
+ "pk": 11,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 11,
+ "adapter_type": 8,
+ "sequence": "GGCTAC"
+ }
+ },
+ {
+ "pk": 12,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 12,
+ "adapter_type": 8,
+ "sequence": "CTTGTA"
+ }
+ },
+ {
+ "pk": 13,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 1,
+ "adapter_type": 7,
+ "sequence": "ATCACG"
+ }
+ },
+ {
+ "pk": 14,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 2,
+ "adapter_type": 7,
+ "sequence": "CGATGT"
+ }
+ },
+ {
+ "pk": 15,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 3,
+ "adapter_type": 7,
+ "sequence": "TTAGGC"
+ }
+ },
+ {
+ "pk": 16,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 4,
+ "adapter_type": 7,
+ "sequence": "TGACCA"
+ }
+ },
+ {
+ "pk": 17,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 5,
+ "adapter_type": 7,
+ "sequence": "ACAGTG"
+ }
+ },
+ {
+ "pk": 18,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 6,
+ "adapter_type": 7,
+ "sequence": "GCCAAT"
+ }
+ },
+ {
+ "pk": 19,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 7,
+ "adapter_type": 7,
+ "sequence": "CAGATC"
+ }
+ },
+ {
+ "pk": 20,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 8,
+ "adapter_type": 7,
+ "sequence": "ACTTGA"
+ }
+ },
+ {
+ "pk": 21,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 9,
+ "adapter_type": 7,
+ "sequence": "GATCAG"
+ }
+ },
+ {
+ "pk": 22,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 10,
+ "adapter_type": 7,
+ "sequence": "TAGCTT"
+ }
+ },
+ {
+ "pk": 23,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 11,
+ "adapter_type": 7,
+ "sequence": "GGCTAC"
+ }
+ },
+ {
+ "pk": 24,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 12,
+ "adapter_type": 7,
+ "sequence": "CTTGTA"
+ }
+ },
+ {
+ "pk": 25,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 13,
+ "adapter_type": 7,
+ "sequence": "AGTCAA"
+ }
+ },
+ {
+ "pk": 26,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 14,
+ "adapter_type": 7,
+ "sequence": "AGTTCC"
+ }
+ },
+ {
+ "pk": 27,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 15,
+ "adapter_type": 7,
+ "sequence": "ATGTCA"
+ }
+ },
+ {
+ "pk": 28,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 16,
+ "adapter_type": 7,
+ "sequence": "CCGTCC"
+ }
+ },
+ {
+ "pk": 29,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 17,
+ "adapter_type": 7,
+ "sequence": "GTAGAG"
+ }
+ },
+ {
+ "pk": 30,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 18,
+ "adapter_type": 7,
+ "sequence": "GTCCGC"
+ }
+ },
+ {
+ "pk": 31,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 19,
+ "adapter_type": 7,
+ "sequence": "GTGAAA"
+ }
+ },
+ {
+ "pk": 32,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 20,
+ "adapter_type": 7,
+ "sequence": "GTGGCC"
+ }
+ },
+ {
+ "pk": 33,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 21,
+ "adapter_type": 7,
+ "sequence": "GTTTCG"
+ }
+ },
+ {
+ "pk": 34,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 22,
+ "adapter_type": 7,
+ "sequence": "CGTACG"
+ }
+ },
+ {
+ "pk": 35,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 23,
+ "adapter_type": 7,
+ "sequence": "GAGTGG"
+ }
+ },
+ {
+ "pk": 36,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 24,
+ "adapter_type": 7,
+ "sequence": "GGTAGC"
+ }
+ },
+ {
+ "pk": 37,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 25,
+ "adapter_type": 7,
+ "sequence": "ACTGAT"
+ }
+ },
+ {
+ "pk": 38,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 26,
+ "adapter_type": 7,
+ "sequence": "ATGAGC"
+ }
+ },
+ {
+ "pk": 39,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 27,
+ "adapter_type": 7,
+ "sequence": "ATTCCT"
+ }
+ },
+ {
+ "pk": 40,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 28,
+ "adapter_type": 7,
+ "sequence": "CAAAAG"
+ }
+ },
+ {
+ "pk": 41,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 29,
+ "adapter_type": 7,
+ "sequence": "CAACTA"
+ }
+ },
+ {
+ "pk": 42,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 30,
+ "adapter_type": 7,
+ "sequence": "CACCGG"
+ }
+ },
+ {
+ "pk": 43,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 31,
+ "adapter_type": 7,
+ "sequence": "CACGAT"
+ }
+ },
+ {
+ "pk": 44,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 32,
+ "adapter_type": 7,
+ "sequence": "CACTCA"
+ }
+ },
+ {
+ "pk": 45,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 33,
+ "adapter_type": 7,
+ "sequence": "CAGGCG"
+ }
+ },
+ {
+ "pk": 46,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 34,
+ "adapter_type": 7,
+ "sequence": "CATGGC"
+ }
+ },
+ {
+ "pk": 47,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 35,
+ "adapter_type": 7,
+ "sequence": "CATTTT"
+ }
+ },
+ {
+ "pk": 48,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 36,
+ "adapter_type": 7,
+ "sequence": "CCAACA"
+ }
+ },
+ {
+ "pk": 49,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 37,
+ "adapter_type": 7,
+ "sequence": "CGGAAT"
+ }
+ },
+ {
+ "pk": 50,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 38,
+ "adapter_type": 7,
+ "sequence": "CTAGCT"
+ }
+ },
+ {
+ "pk": 51,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 39,
+ "adapter_type": 7,
+ "sequence": "CTATAC"
+ }
+ },
+ {
+ "pk": 52,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 40,
+ "adapter_type": 7,
+ "sequence": "CTCAGA"
+ }
+ },
+ {
+ "pk": 53,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 41,
+ "adapter_type": 7,
+ "sequence": "GACGAC"
+ }
+ },
+ {
+ "pk": 54,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 42,
+ "adapter_type": 7,
+ "sequence": "TAATCG"
+ }
+ },
+ {
+ "pk": 55,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 43,
+ "adapter_type": 7,
+ "sequence": "TACAGC"
+ }
+ },
+ {
+ "pk": 56,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 44,
+ "adapter_type": 7,
+ "sequence": "TATAAT"
+ }
+ },
+ {
+ "pk": 57,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 45,
+ "adapter_type": 7,
+ "sequence": "TCATTC"
+ }
+ },
+ {
+ "pk": 58,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 46,
+ "adapter_type": 7,
+ "sequence": "TCCCGA"
+ }
+ },
+ {
+ "pk": 59,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 47,
+ "adapter_type": 7,
+ "sequence": "TCGAAG"
+ }
+ },
+ {
+ "pk": 60,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 48,
+ "adapter_type": 7,
+ "sequence": "TCGGCA"
+ }
+ },
+ {
+ "pk": 61,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 1,
+ "adapter_type": 5,
+ "sequence": "ATCACG"
+ }
+ },
+ {
+ "pk": 62,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 2,
+ "adapter_type": 5,
+ "sequence": "CGATGT"
+ }
+ },
+ {
+ "pk": 63,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 3,
+ "adapter_type": 5,
+ "sequence": "TTAGGC"
+ }
+ },
+ {
+ "pk": 64,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 4,
+ "adapter_type": 5,
+ "sequence": "TGACCA"
+ }
+ },
+ {
+ "pk": 65,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 5,
+ "adapter_type": 5,
+ "sequence": "ACAGTG"
+ }
+ },
+ {
+ "pk": 66,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 6,
+ "adapter_type": 5,
+ "sequence": "GCCAAT"
+ }
+ },
+ {
+ "pk": 67,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 7,
+ "adapter_type": 5,
+ "sequence": "CAGATC"
+ }
+ },
+ {
+ "pk": 68,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 8,
+ "adapter_type": 5,
+ "sequence": "ACTTGA"
+ }
+ },
+ {
+ "pk": 69,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 9,
+ "adapter_type": 5,
+ "sequence": "GATCAG"
+ }
+ },
+ {
+ "pk": 70,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 10,
+ "adapter_type": 5,
+ "sequence": "TAGCTT"
+ }
+ },
+ {
+ "pk": 71,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 11,
+ "adapter_type": 5,
+ "sequence": "GGCTAC"
+ }
+ },
+ {
+ "pk": 72,
+ "model": "samples.MultiplexIndex",
+ "fields": {
+ "multiplex_id": 12,
+ "adapter_type": 5,
+ "sequence": "CTTGTA"
+ }
}
]
class Antibody(models.Model):
antigene = models.CharField(max_length=500, db_index=True)
# New field Aug/20/08
- # SQL to add column:
+ # SQL to add column:
# alter table fctracker_antibody add column "nickname" varchar(20) NULL;
nickname = models.CharField(
max_length=20,
blank=True,
- null=True,
+ null=True,
db_index=True
)
catalog = models.CharField(max_length=50, blank=True, null=True)
cellline_name = models.CharField(max_length=100, unique=True, db_index=True)
nickname = models.CharField(max_length=20,
blank=True,
- null=True,
+ null=True,
db_index=True)
-
+
notes = models.TextField(blank=True)
def __unicode__(self):
return unicode(self.cellline_name)
max_length=2000, unique=True, db_index=True)
nickname = models.CharField(max_length=20,
blank=True,
- null=True,
+ null=True,
db_index=True,
verbose_name = 'Short Name')
notes = models.TextField(blank=True)
class Meta:
ordering = ["condition_name"]
-
+
class ExperimentType(models.Model):
name = models.CharField(max_length=50, unique=True)
def __unicode__(self):
return unicode(self.name)
-class Tag(models.Model):
- tag_name = models.CharField(max_length=100, db_index=True,blank=False,null=False)
- TAG_CONTEXT = (
- #('Antibody','Antibody'),
- #('Cellline', 'Cellline'),
- #('Condition', 'Condition'),
- ('Library', 'Library'),
- ('ANY','ANY'),
- )
- context = models.CharField(max_length=50,
- choices=TAG_CONTEXT, default='Library')
-
- def __unicode__(self):
- return u'%s' % (self.tag_name)
-
- class Meta:
- ordering = ["context","tag_name"]
-
+class Tag(models.Model):
+ tag_name = models.CharField(max_length=100, db_index=True,blank=False,null=False)
+ TAG_CONTEXT = (
+ #('Antibody','Antibody'),
+ #('Cellline', 'Cellline'),
+ #('Condition', 'Condition'),
+ ('Library', 'Library'),
+ ('ANY','ANY'),
+ )
+ context = models.CharField(max_length=50,
+ choices=TAG_CONTEXT, default='Library')
+
+ def __unicode__(self):
+ return u'%s' % (self.tag_name)
+
+ class Meta:
+ ordering = ["context","tag_name"]
+
class Species(models.Model):
- scientific_name = models.CharField(max_length=256,
- unique=False,
+ scientific_name = models.CharField(max_length=256,
+ unique=False,
db_index=True
)
common_name = models.CharField(max_length=256, blank=True)
def __unicode__(self):
return u'%s (%s)' % (self.scientific_name, self.common_name)
-
+
class Meta:
verbose_name_plural = "species"
ordering = ["scientific_name"]
@models.permalink
def get_absolute_url(self):
return ('htsworkflow.frontend.samples.views.species', [str(self.id)])
-
+
class Affiliation(models.Model):
name = models.CharField(max_length=256, db_index=True, verbose_name='Name')
- contact = models.CharField(max_length=256, null=True, blank=True,verbose_name='Lab Name')
+ contact = models.CharField(max_length=256, null=True, blank=True,verbose_name='Lab Name')
email = models.EmailField(null=True,blank=True)
users = models.ManyToManyField('HTSUser', null=True, blank=True)
users.admin_order_field = "username"
-
+
def __unicode__(self):
str = unicode(self.name)
if self.contact is not None and len(self.contact) > 0:
- str += u' ('+self.contact+u')'
+ str += u' ('+self.contact+u')'
return str
def Users(self):
unique_together = (("name", "contact"),)
class LibraryType(models.Model):
- name = models.CharField(max_length=255, unique=True)
+ name = models.CharField(max_length=255, unique=True,
+ name="Adapter Type")
+ is_paired_end = models.BooleanField(default=True,
+ help_text="can you do a paired end run with this adapter")
+ can_multiplex = models.BooleanField(default=True,
+ help_text="Does this adapter provide multiplexing?")
def __unicode__(self):
- return unicode(self.name)
+ return unicode(self.name)
+
+ class Meta:
+ ordering = ["-id"]
+
+class MultiplexIndex(models.Model):
+ """Map adapter types to the multiplex sequence"""
+ adapter_type = models.ForeignKey(LibraryType)
+ multiplex_id = models.CharField(max_length=3, null=False)
+ sequence = models.CharField(max_length=12, blank=True, null=True)
+
+ class Meta:
+ unique_together = ('adapter_type', 'multiplex_id')
class Library(models.Model):
id = models.CharField(max_length=10, primary_key=True)
blank=True,null=True)
REPLICATE_NUM = ((1,1),(2,2),(3,3),(4,4))
replicate = models.PositiveSmallIntegerField(choices=REPLICATE_NUM,
- blank=True,null=True)
+ blank=True,null=True)
experiment_type = models.ForeignKey(ExperimentType)
- library_type = models.ForeignKey(LibraryType, blank=True, null=True)
+ library_type = models.ForeignKey(LibraryType, blank=True, null=True,
+ verbose_name="Adapter Type")
+ multiplex_id = models.CharField(max_length=128,
+ blank=True, null=True,
+ verbose_name="Index ID")
creation_date = models.DateField(blank=True, null=True)
- made_for = models.CharField(max_length=50, blank=True,
+ made_for = models.CharField(max_length=50, blank=True,
verbose_name='ChIP/DNA/RNA Made By')
made_by = models.CharField(max_length=50, blank=True, default="Lorian")
-
+
PROTOCOL_END_POINTS = (
('?', 'Unknown'),
('Sample', 'Raw sample'),
stopping_point = models.CharField(max_length=25,
choices=PROTOCOL_END_POINTS,
default='Done')
-
+
amplified_from_sample = models.ForeignKey('self',
related_name='amplified_into_sample',
blank=True, null=True)
-
- undiluted_concentration = models.DecimalField("Concentration",
+
+ undiluted_concentration = models.DecimalField("Concentration",
max_digits=5, decimal_places=2, blank=True, null=True,
- help_text=u"Undiluted concentration (ng/\u00b5l)")
+ help_text=u"Undiluted concentration (ng/\u00b5l)")
# note \u00b5 is the micro symbol in unicode
successful_pM = models.DecimalField(max_digits=9,
decimal_places=1, blank=True, null=True)
notes = models.TextField(blank=True)
bioanalyzer_summary = models.TextField(blank=True,default="")
- bioanalyzer_concentration = models.DecimalField(max_digits=5,
+ bioanalyzer_concentration = models.DecimalField(max_digits=5,
decimal_places=2, blank=True, null=True,
help_text=u"(ng/\u00b5l)")
bioanalyzer_image_url = models.URLField(blank=True,default="")
-
+
def __unicode__(self):
return u'#%s: %s' % (self.id, self.library_name)
-
+
class Meta:
verbose_name_plural = "libraries"
- #ordering = ["-creation_date"]
+ #ordering = ["-creation_date"]
ordering = ["-id"]
-
+
def antibody_name(self):
- str ='<a target=_self href="/admin/samples/antibody/'+self.antibody.id.__str__()+'/" title="'+self.antibody.__str__()+'">'+self.antibody.label+'</a>'
+ str ='<a target=_self href="/admin/samples/antibody/'+self.antibody.id.__str__()+'/" title="'+self.antibody.__str__()+'">'+self.antibody.label+'</a>'
return str
antibody_name.allow_tags = True
def organism(self):
return self.library_species.common_name
+ def index_sequences(self):
+ """Return a dictionary of multiplex index id to sequence
+ Return None if the library can't multiplex,
+
+ """
+ if self.library_type is None:
+ return None
+ if not self.library_type.can_multiplex:
+ return None
+ if self.multiplex_id is None or len(self.multiplex_id) == 0:
+ return 'Err: id empty'
+ sequences = {}
+ multiplex_ids = self.multiplex_id.split(',')
+ for multiplex_id in multiplex_ids:
+ try:
+ multiplex = MultiplexIndex.objects.get(
+ adapter_type = self.library_type.id,
+ multiplex_id = multiplex_id)
+ sequences[multiplex_id] = multiplex.sequence
+ except MultiplexIndex.DoesNotExist, e:
+ sequences[multiplex_id] = 'Err: index not found'
+ return sequences
+
+ def index_sequence_text(self, seperator=' '):
+ """Return formatted multiplex index sequences"""
+ sequences = self.index_sequences()
+ multiplex_ids = sequences.keys()
+ multiplex_ids.sort()
+ return seperator.join(( "%s:%s" %(i,sequences[i]) for i in multiplex_ids))
+ index_sequence_text.short_description = "Index"
+
+
def affiliation(self):
affs = self.affiliations.all().order_by('name')
tstr = ''
for t in affs:
ar.append(t.__unicode__())
return '%s' % (", ".join(ar))
-
+
def is_archived(self):
"""
returns True if archived else False
name = "Lookup Error"
logger.error("protocol stopping point in database didn't match names in library model")
return name
-
+
def libtags(self):
affs = self.tags.all().order_by('tag_name')
return u'%s' % ( ", ".join(ar))
def DataRun(self):
- str ='<a target=_self href="/admin/experiments/datarun/?q='+self.id+'" title="Check All Data Runs for This Specific Library ..." ">Data Run</a>'
+ str ='<a target=_self href="/admin/experiments/datarun/?q='+self.id+'" title="Check All Data Runs for This Specific Library ..." ">Data Run</a>'
return str
DataRun.allow_tags = True
if res[1] > rc_thr[1]:
bgcolor ='#00ccff' # Blue
else:
- if res[1] > rc_thr[2]:
+ if res[1] > rc_thr[2]:
bgcolor ='#ffcc33' # Orange
tstr = '<div style="background-color:'+bgcolor+';color:black">'
tstr += res[0].__unicode__()+' Lanes, '+rc+' M Reads'
tstr += '</div>'
- else: tstr = 'not processed yet'
+ else: tstr = 'not processed yet'
return tstr
aligned_reads.allow_tags = True
-
+
def public(self):
SITE_ROOT = '/'
summary_url = self.get_absolute_url()
return '<a href="%s">S</a>' % (summary_url,)
public.allow_tags = True
-
+
@models.permalink
def get_absolute_url(self):
return ('htsworkflow.frontend.samples.views.library_to_flowcells', [str(self.id)])
def __unicode__(self):
#return unicode(self.username) + u" (" + unicode(self.get_full_name()) + u")"
return unicode(self.get_full_name()) + u' (' + unicode(self.username) + ')'
-
+
def HTSUserInsertID(sender, instance, **kwargs):
"""
Force addition of HTSUsers when someone just modifies the auth_user object
cursor = connection.cursor()
cursor.execute('INSERT INTO samples_htsuser (user_ptr_id) VALUES (%s);' % (instance.id,))
cursor.close()
-
+
post_save.connect(HTSUserInsertID, sender=User)
<div id="librarydetail" about="{{lib.get_absolute_url}}">
<div class="library_identity">
- <h2>Library Name</h2>
- <b>Library ID</b>:
+ <h2>Library Name</h2>
+ <b>Library ID</b>:
<a href="{{lib.get_absolute_url}}"><span property="libns:library_id">{{ lib.id }}</span></a>
{% if user.is_staff %}<a href="{{lib.get_admin_url}}"><img class="icon_button" src="/media/img/admin/icon_changelink.gif"/></a>{% endif %}
<br/>
- <b>Name</b>:
+ <b>Name</b>:
<span property="libns:name">{{ lib.library_name }}</span>
<br/>
<b>Affiliations</b>:
</div>
<div class="library_sample_detail">
<h2>Sample Details</h2>
- <b>Species</b>:
+ <b>Species</b>:
<span property="libns:species" content="{{lib.library_species.scientific_name}}"><a href="{{lib.library_species.get_absolute_url}}">{{ lib.library_species.scientific_name }}</a></span>
<br/>
<b>Experiment Type</b>:
<br/>
{% endif %}
{% if lib.replicate %}
- <b>Replicate</b>:
+ <b>Replicate</b>:
<span property="libns:replicate">{{ lib.replicate }}</span>
<br/>
{% endif %}
<b>Library Type</b>:
<span property="libns:library_type">{{ lib.library_type }}</span>
<br/>
+ <b>Multiplex Index</b>:
+ <span property="libns:multiplex_index">{{ lib.index_sequence_text }}</span>
+ <br/>
<b>Creation Date</b>
<span property="libns:date" content="{{lib.creation_date|date:'Y-m-d'}}T00:00:00" datatype="xsd:dateTime">{{ lib.creation_date }}</span>
- <br/>
- <b>Made By</b>:
+ <br/>
+ <b>Made By</b>:
<span property="libns:made_by">{{ lib.made_by }}</span>
<br/>
{% if lib.gel_cut_size %}
- <b>Gel Cut Size</b>:
+ <b>Gel Cut Size</b>:
<span property="libns:gel_cut" datatype="xsd:decimal">{{ lib.gel_cut_size }}</span>
<br/>
{% endif %}
{% if lib.insert_size %}
- <b>Insert Size</b>:
+ <b>Insert Size</b>:
<span property="libns:insert_size" datatype="xsd:decimal">{{ lib.insert_size }}</span>
<br/>
{% endif %}
{% if lib.undiluted_concentration %}
- <b>Concentration</b>:
+ <b>Concentration</b>:
<span property="libns:concentration">{{ lib.undiluted_concentration }} ng/µl</span>
<br/>
{% endif %}
#!/usr/bin/env python
+import csv
from ConfigParser import RawConfigParser
import logging
from optparse import OptionParser, IndentedHelpFormatter
import os
import sys
+import types
import urllib
import urllib2
from htsworkflow.frontend.auth import apidata
from htsworkflow.util import api
from htsworkflow.util.url import normalize_url
-from htsworkflow.pipelines.genome_mapper import getAvailableGenomes
-from htsworkflow.pipelines.genome_mapper import constructMapperDict
+from htsworkflow.pipelines.genome_mapper import \
+ getAvailableGenomes, \
+ constructMapperDict
+from htsworkflow.pipelines.runfolder import LANE_LIST
+# JSON dictionaries use strings
+LANE_LIST_JSON = [ str(l) for l in LANE_LIST ]
__docformat__ = "restructredtext en"
#Disable or enable commandline arg parsing; disabled by default.
DISABLE_CMDLINE = True
-LANE_LIST = ['1','2','3','4','5','6','7','8']
-
class FlowCellNotFound(Exception): pass
class WebError404(Exception): pass
def retrieve_flowcell_info(base_host_url, flowcell):
"""
- Return a dictionary describing a
+ Return a dictionary describing a
"""
url = api.flowcell_url(base_host_url, flowcell)
-
+
try:
apipayload = urllib.urlencode(apidata)
web = urllib2.urlopen(url, apipayload)
logging.error(errmsg)
logging.error('opened %s' % (url,))
raise IOError(errmsg)
-
+
contents = web.read()
headers = web.info()
if web.code == 403:
msg = "403 - Forbbidden, probably need api key"
raise FlowCellNotFound(msg)
-
+
if web.code == 404:
msg = "404 - Not Found: Flowcell (%s); base_host_url (%s);\n full url(%s)\n " \
"Did you get right port #?" % (flowcell, base_host_url, url)
raise FlowCellNotFound(msg)
-
+
if len(contents) == 0:
msg = "No information for flowcell (%s) returned; full url(%s)" % (flowcell, url)
raise FlowCellNotFound(msg)
return True
else:
return False
-
+
def group_lane_parameters(flowcell_info):
"""
goup lanes that can share GERALD configuration blocks.
(The same species, read length, and eland vs sequencing)
"""
lane_groups = {}
- for lane_number, lane_info in flowcell_info['lane_set'].items():
- index = (lane_info['read_length'],
- lane_info['library_species'],
- is_sequencing(lane_info))
- lane_groups.setdefault(index, []).append(lane_number)
+ for lane_number, lane_contents in flowcell_info['lane_set'].items():
+ for lane_info in lane_contents:
+ index = (lane_info['read_length'],
+ lane_info['library_species'],
+ is_sequencing(lane_info))
+ lane_groups.setdefault(index, []).append(lane_number)
return lane_groups
def format_gerald_header(flowcell_info):
config += ['Flowcell Notes:']
config.extend(flowcell_info['notes'].split('\r\n'))
config += ['']
- for lane_number in LANE_LIST:
- lane_info = flowcell_info['lane_set'][lane_number]
- config += ['Lane%s: %s | %s' % (lane_number, lane_info['library_id'],
- lane_info['library_name'])]
+ for lane_number in LANE_LIST_JSON:
+ lane_contents = flowcell_info['lane_set'][lane_number]
+ for lane_info in lane_contents:
+ config += ['Lane%s: %s | %s' % (lane_number,
+ lane_info['library_id'],
+ lane_info['library_name'])]
config += ['']
return "\n# ".join(config)
read_length, species, is_sequencing = lane_index
lane_numbers.sort()
lane_prefix = u"".join(lane_numbers)
-
+
species_path = genome_map.get(species, None)
logging.debug("Looked for genome '%s' got location '%s'" % (species, species_path))
if not is_sequencing and species_path is None:
no_genome_msg = "Forcing lanes %s to sequencing as there is no genome for %s"
logging.warning(no_genome_msg % (lane_numbers, species))
is_sequencing = True
-
+
if is_sequencing:
config += ['%s:ANALYSIS sequence%s' % (lane_prefix, sequence_suffix)]
else:
#config += ['%s:READ_LENGTH %s' % ( lane_prefix, read_length ) ]
config += ['%s:USE_BASES Y%s' % ( lane_prefix, read_length ) ]
- # add in option for running script after
+ # add in option for running script after
if not (options.post_run is None or options.runfolder is None):
runfolder = os.path.abspath(options.runfolder)
post_run = options.post_run % {'runfolder': runfolder}
config += ['POST_RUN_COMMAND %s' % (post_run,) ]
-
+
config += [''] # force trailing newline
-
+
return "\n".join(config)
-
+
class DummyOptions:
"""
Used when command line parsing is disabled; default
self.genome_dir = None
class PreformattedDescriptionFormatter(IndentedHelpFormatter):
-
+
#def format_description(self, description):
- #
+ #
# if description:
# return description + "\n"
# else:
# return ""
-
+
def format_epilog(self, epilog):
"""
It was removing my preformated epilog, so this should override
parser = OptionParser(formatter=PreformattedDescriptionFormatter())
parser.set_description('Retrieves eland config file from hts_frontend web frontend.')
-
+
parser.epilog = """
Config File:
* %s (System wide)
* %s (User specific; overrides system)
* command line overrides all config file options
-
+
Example Config File:
-
+
[%s]
config_host: http://somewhere.domain:port
genome_dir: /path to search for genomes
post_run: runfolder -o <destdir> %%(runfolder)s
-
+
""" % (CONFIG_SYSTEM, CONFIG_USER, GERALD_CONFIG_SECTION)
-
+
#Special formatter for allowing preformatted description.
##parser.format_epilog(PreformattedDescriptionFormatter())
parser.add_option("-u", "--url",
action="store", type="string", dest="url")
-
+
parser.add_option("-o", "--output-file",
action="store", type="string", dest="output_filepath",
help="config file destination. If runfolder is specified defaults "
"to <runfolder>/config-auto.txt" )
-
+
parser.add_option("-f", "--flowcell",
action="store", type="string", dest="flowcell")
action="store", type="string",
help="specify runfolder for post_run command ")
+ parser.add_option("--sample-sheet", default=None,
+ help="path to save demultiplexing sample sheet")
+
+ parser.add_option("--operator", default='', help="Name of sequencer operator")
+ parser.add_option("--recipe", default="Unknown",
+ help="specify recipe name")
+
parser.add_option('-v', '--verbose', action='store_true', default=False,
help='increase logging verbosity')
return parser
-
+
def constructConfigParser():
"""
returns a pre-setup config parser
parser.read([CONFIG_SYSTEM, CONFIG_USER])
if not parser.has_section(GERALD_CONFIG_SECTION):
parser.add_section(GERALD_CONFIG_SECTION)
-
+
return parser
options = DummyOptions()
else:
options, args = cl_parser.parse_args(argv)
-
+
if options.url is None:
if conf_parser.has_option(GERALD_CONFIG_SECTION, 'config_host'):
options.url = conf_parser.get(GERALD_CONFIG_SECTION, 'config_host')
-
+
options.url = normalize_url(options.url)
-
+
if options.genome_dir is None:
if conf_parser.has_option(GERALD_CONFIG_SECTION, 'genome_dir'):
options.genome_dir = conf_parser.get(GERALD_CONFIG_SECTION, 'genome_dir')
if options.output_filepath is None:
if options.runfolder is not None:
options.output_filepath = os.path.join(options.runfolder, 'config-auto.txt')
-
+
return options
logging.info(u' FC: %s' % (options.flowcell,))
#logging.info(': %s' % (options.genome_dir,))
logging.info(u'post_run: %s' % ( unicode(options.post_run),))
-
+
flowcell_info = retrieve_flowcell_info(options.url, options.flowcell)
logging.debug('genome_dir: %s' % ( options.genome_dir, ))
genome_map = constructMapperDict(available_genomes)
logging.debug('available genomes: %s' % ( unicode( genome_map.keys() ),))
- config = format_gerald_config(options, flowcell_info, genome_map)
-
- if options.output_filepath is not None:
- outstream = open(options.output_filepath, 'w')
- logging.info('Writing config file to %s' % (options.output_filepath,))
+ #config = format_gerald_config(options, flowcell_info, genome_map)
+ #
+ #if options.output_filepath is not None:
+ # outstream = open(options.output_filepath, 'w')
+ # logging.info('Writing config file to %s' % (options.output_filepath,))
+ #else:
+ # outstream = sys.stdout
+ #
+ #outstream.write(config)
+
+ if options.sample_sheet is None:
+ pass
+ elif options.sample_sheet == '-':
+ save_sample_sheet(sys.stdout, options, flowcell_info)
else:
- outstream = sys.stdout
-
- outstream.write(config)
-
+ stream = open(options.sample_sheet,'w')
+ save_sample_sheet(stream, options, flowcell_info)
+
+
+def save_sample_sheet(outstream, options, flowcell_info):
+ sample_sheet_fields = ['FCID', 'Lane', 'SampleID', 'SampleRef', 'Index',
+ 'Description', 'Control', 'Recipe', 'Operator',
+ 'SampleProject']
+ illumina_to_htsw_map = {'FCID': 'flowcell',
+ 'Lane': 'lane_number',
+ 'SampleID': 'library_id',
+ 'SampleRef': format_sampleref,
+ 'Description': 'library_name',
+ 'Control': format_control_lane,
+ 'Recipe': format_recipe_name,
+ 'Operator': format_operator_name}
+ out = csv.DictWriter(outstream, sample_sheet_fields)
+ out.writeheader()
+ for lane_number in LANE_LIST:
+ lane_contents = flowcell_info['lane_set'][str(lane_number)]
+
+ pooled_lane_contents = []
+ for library in lane_contents:
+ # build common attributes
+ renamed = {}
+ for illumina_name in sample_sheet_fields:
+ htsw_field = illumina_to_htsw_map.get(illumina_name, None)
+ if htsw_field is None:
+ continue
+ if callable(htsw_field):
+ renamed[illumina_name] = htsw_field(options,
+ flowcell_info,
+ library)
+ else:
+ renamed[illumina_name] = library[htsw_field]
+
+ pooled_lane_contents.extend(format_pooled_libraries(renamed, library))
+
+ if len(pooled_lane_contents) > 1:
+ for row in pooled_lane_contents:
+ out.writerow(row)
+
+
+def format_sampleref(options, flowcell_info, sample):
+ return sample['library_species'].replace(' ', '_')
+
+
+def format_control_lane(options, flowcell_info, sample):
+ if sample['lane_number'] == flowcell_info['control_lane']:
+ return 'Y'
+ else:
+ return 'N'
+
+
+def format_recipe_name(options, flowcell_info, sample):
+ return options.recipe
+
+
+def format_operator_name(options, flowcell_info, sample):
+ return options.operator
+
+
+def format_pooled_libraries(shared, library):
+ sequences = library.get('index_sequence', None)
+ if sequences is None:
+ return []
+ elif type(sequences) in types.StringTypes:
+ shared['Index'] = sequences
+ shared['SampleProject'] = library['library_id']
+ return [shared]
+ else:
+ pooled = []
+ multiplex_ids = sequences.keys()
+ multiplex_ids.sort(key=int)
+ for multiplex_id in multiplex_ids:
+ sample = {}
+ sample.update(shared)
+ sample['Index'] = sequences[multiplex_id]
+ sample['SampleProject'] = format_project_name(library,
+ multiplex_id)
+ pooled.append(sample)
+ return pooled
+
+
+def format_project_name(library, multiplex_id):
+ library_id = library['library_id']
+ return "%s_index%s" % (library_id, multiplex_id)
-
+import csv
import os
import re
+from StringIO import StringIO
try:
import json
except ImportError, e:
import simplejson as json
-
+
from django.test import TestCase
from htsworkflow.frontend.auth import apidata
-from htsworkflow.pipelines.retrieve_config import format_gerald_config, getCombinedOptions
+from htsworkflow.pipelines.retrieve_config import \
+ format_gerald_config, \
+ getCombinedOptions, \
+ save_sample_sheet
class RetrieveTestCases(TestCase):
fixtures = ['test_flowcells.json']
def test_format_gerald(self):
flowcell_request = self.client.get('/experiments/config/FC12150/json', apidata)
self.failUnlessEqual(flowcell_request.status_code, 200)
-
- print dir(flowcell_request)
flowcell_info = json.loads(flowcell_request.content)
- options = getCombinedOptions(['-f','FC12150','-g',os.getcwd()])
+ options = getCombinedOptions(['-f','FC12150','-g',os.getcwd()])
genome_map = {u'Homo sapiens': '/tmp/hg18' }
-
+
config = format_gerald_config(options, flowcell_info, genome_map)
config_lines = config.split('\n')
lane3 = [ line for line in config_lines if re.search('Lane3', line) ]
sequencing = [ line for line in config_lines if re.search('sequence_pair', line) ]
self.failUnlessEqual(len(sequencing), 2)
-
-
-
+ def test_format_sample_sheet(self):
+ fcid = '42JU1AAXX'
+ url = '/experiments/config/%s/json' % (fcid,)
+ flowcell_request = self.client.get(url, apidata)
+ self.failUnlessEqual(flowcell_request.status_code, 200)
+ flowcell_info = json.loads(flowcell_request.content)
+
+ options = getCombinedOptions(['-f',fcid,'-g',os.getcwd(),])
+
+ output = StringIO()
+ save_sample_sheet(output, options, flowcell_info)
+ output.seek(0)
+ sheet = list(csv.DictReader(output))
+ expected = [{'SampleProject': '12044_index1', 'Index': 'ATCACG'},
+ {'SampleProject': '12044_index2', 'Index': 'CGATGT'},
+ {'SampleProject': '12044_index3', 'Index': 'TTAGGC'},
+ {'SampleProject': '11045_index1', 'Index': 'ATCACG'},
+ ]
+ for i in range(4):
+ self.assertEqual(sheet[i]['SampleProject'],
+ expected[i]['SampleProject'])
+ self.assertEqual(sheet[i]['Index'],
+ expected[i]['Index'])
+ self.assertEqual(sheet[i]['FCID'], fcid)
+ self.assertEqual(sheet[i]['Lane'], '3')
+
+
#!/usr/bin/env python
+import os
+if not 'DJANGO_SETTINGS_MODULE' in os.environ:
+ os.environ['DJANGO_SETTINGS_MODULE'] = 'htsworkflow.settings'
+
import logging
import sys
from htsworkflow.pipelines.retrieve_config import *
#Turn on built-in command-line parsing.
retrieve_config.DISABLE_CMDLINE = False
+
def main(argv=None):
- if argv is None:
- argv = sys.argv
-
- #Display help if no args are presented
- options = getCombinedOptions(argv)
-
- if options.verbose:
- logging.basicConfig(level=logging.DEBUG)
- else:
- logging.basicConfig(level=logging.INFO)
-
- msg_list = ['ERROR MESSAGES:']
- if options.flowcell is None:
- msg_list.append(" Flow cell argument required. -f <flowcell> or --flowcell=<flowcell>")
-
- if options.url is None:
- msg_list.append(" URL argument required (-u <url> or --url=<url>), or entry\n" \
- " in /etc/ga_frontend/ga_frontend.conf or ~/.ga_frontend.conf")
- if options.genome_dir is None:
- msg_list.append(" genome_dir argument required (-g <genome_dir> or \n" \
- " --genome_dir=<genome_dir>, or entry in \n" \
- " /etc/ga_frontend/ga_frontend.conf or ~/.ga_frontend.conf")
-
- if len(msg_list) > 1:
- print '\n'.join(msg_list)
- return 1
-
- saveConfigFile(options)
-
- return 0
-
+ if argv is None:
+ argv = sys.argv
+
+ #Display help if no args are presented
+ options = getCombinedOptions(argv)
+
+ if options.verbose:
+ logging.basicConfig(level=logging.DEBUG)
+ else:
+ logging.basicConfig(level=logging.INFO)
+
+ msg_list = ['ERROR MESSAGES:']
+ if options.flowcell is None:
+ msg_list.append(
+ " Flow cell argument required. -f <flowcell> or "\
+ "--flowcell=<flowcell>")
+
+ if options.url is None:
+ msg_list.append(
+ " URL argument required (-u <url> or --url=<url>), or entry\n" \
+ " in /etc/ga_frontend/ga_frontend.conf or ~/.ga_frontend.conf")
+
+ if options.genome_dir is None:
+ msg_list.append(
+ " genome_dir argument required (-g <genome_dir> or \n" \
+ " --genome_dir=<genome_dir>, or entry in \n" \
+ " /etc/ga_frontend/ga_frontend.conf or ~/.ga_frontend.conf")
+
+ if len(msg_list) > 1:
+ print '\n'.join(msg_list)
+ return 1
+
+ saveConfigFile(options)
+
+ return 0
+
if __name__ == "__main__":
- sys.exit(main(sys.argv[1:]))
+ sys.exit(main(sys.argv[1:]))
projects / htsworkflow.git / commitdiff