--- /dev/null
+import sqlite3
+
+def map_library_ids(c):
+ lib_ids = {}
+ c.execute("""select id, library_id from samples_library""")
+ for row in c:
+ surrogate_id = unicode(row[0]) # auto key
+ artificial_id = unicode(row[1]) # the id printed on the library tubes
+ lib_ids[surrogate_id] = artificial_id
+ return lib_ids
+
+def convert_experiments_lane(c, lib_ids):
+ """
+ Change Library ID in experiments_lane table
+ """
+ c.execute('alter table experiments_lane rename to old_experiments_lane')
+ c.execute("""CREATE TABLE "experiments_lane" (
+ "id" integer NOT NULL PRIMARY KEY,
+ "flowcell_id" integer NOT NULL REFERENCES "experiments_flowcell" ("id"),
+ "lane_number" integer NOT NULL,
+ "library_id" varchar(10) NOT NULL REFERENCES "samples_library" ("library_id"),
+ "pM" decimal NOT NULL,
+ "cluster_estimate" integer,
+ "comment" text);""")
+
+ c.execute("""select id, flowcell_id, lane_number, library_id, pM, cluster_estimate, comment
+ from old_experiments_lane;""")
+
+ new_rows = []
+ for row in c:
+ new_rows.append({'id':row[0], 'flowcell_id':row[1], 'lane_number':row[2],
+ 'library_id':lib_ids[unicode(row[3])], 'pM':row[4],
+ 'cluster_estimate':row[5],
+ 'comment':row[6]})
+
+ sql = '''insert into experiments_lane
+ (id, flowcell_id, lane_number, library_id, pM, cluster_estimate, comment)
+ values
+ (:id, :flowcell_id, :lane_number, :library_id, :pM, :cluster_estimate, :comment)'''
+ c.executemany(sql, new_rows)
+
+ c.execute('drop table old_experiments_lane')
+
+def convert_samples_library_affiliations(c, lib_ids):
+ """
+ Change Library ID in experiments_lane table
+ """
+ c.execute('alter table samples_library_affiliations rename to old_samples_library_affiliations')
+ c.execute('''CREATE TABLE "samples_library_affiliations" (
+ "id" integer NOT NULL PRIMARY KEY,
+ "library_id" varchar(10) NOT NULL REFERENCES "samples_library" ("id"),
+ "affiliation_id" integer NOT NULL REFERENCES "samples_affiliation" ("id"),
+ UNIQUE ("library_id", "affiliation_id")
+);''')
+
+ c.execute("""select id, library_id, affiliation_id
+ from old_samples_library_affiliations;""")
+
+ new_rows = []
+ for row in c:
+ new_rows.append({'id':row[0], 'library_id': lib_ids[unicode(row[1])], 'affiliation_id':row[2],})
+
+ sql = '''insert into samples_library_affiliations
+ (id, library_id, affiliation_id)
+ values
+ (:id, :library_id, :affiliation_id)'''
+ c.executemany(sql, new_rows)
+
+ c.execute('drop table old_samples_library_affiliations;')
+
+def convert_samples_library_tags(c, lib_ids):
+ """
+ Change Library ID in samples_library_tags table
+ """
+ c.execute('alter table samples_library_tags rename to old_samples_library_tags')
+ c.execute('''CREATE TABLE "samples_library_tags" (
+ "id" integer NOT NULL PRIMARY KEY,
+ "library_id" varchar(10) NOT NULL REFERENCES "samples_library" ("id"),
+ "tag_id" integer NOT NULL REFERENCES "samples_tag" ("id"),
+ UNIQUE ("library_id", "tag_id")
+);''')
+
+ c.execute("""select id, library_id, tag_id
+ from old_samples_library_tags;""")
+
+ new_rows = []
+ for row in c:
+ new_rows.append({'id':row[0], 'library_id': lib_ids[unicode(row[1])], 'tag_id':row[2]})
+
+ sql = '''insert into samples_library_tags
+ (id, library_id, tag_id)
+ values
+ (:id, :library_id, :tag_id)'''
+ c.executemany(sql, new_rows)
+
+ c.execute('drop table old_samples_library_tags;')
+
+
+def convert_samples_library(c, lib_ids):
+ """
+ Change Library ID in samples_library_tags table
+ """
+ c.execute('alter table samples_library rename to old_samples_library')
+ c.execute('''CREATE TABLE "samples_library" (
+ "id" varchar(10) NOT NULL PRIMARY KEY,
+ "library_name" varchar(100) NOT NULL UNIQUE,
+ "library_species_id" integer NOT NULL REFERENCES "samples_species" ("id"),
+ "hidden" bool NOT NULL,
+ "account_number" varchar(100),
+ "cell_line_id" integer REFERENCES "samples_cellline" ("id"),
+ "condition_id" integer REFERENCES "samples_condition" ("id"),
+ "antibody_id" integer REFERENCES "samples_antibody" ("id"),
+ "replicate" smallint unsigned NOT NULL,
+ "experiment_type_id" integer NOT NULL REFERENCES "samples_experimenttype" ("id"),
+ "library_type_id" integer REFERENCES "samples_librarytype" ("id"),
+ "creation_date" date,
+ "made_for" varchar(50) NOT NULL,
+ "made_by" varchar(50) NOT NULL,
+ "stopping_point" varchar(25) NOT NULL,
+ "amplified_from_sample_id" varchar(10),
+ "undiluted_concentration" decimal,
+ "successful_pM" decimal,
+ "ten_nM_dilution" bool NOT NULL,
+ "avg_lib_size" integer,
+ "notes" text NOT NULL
+);''')
+
+ c.execute("""
+ select library_id, library_name, library_species_id, hidden, account_number, cell_line_id,
+ condition_id, antibody_id, replicate, experiment_type_id, library_type_id,
+ creation_date, made_for, made_by, stopping_point, amplified_from_sample_id,
+ undiluted_concentration, successful_pM, ten_nM_dilution, avg_lib_size, notes
+ from old_samples_library;""")
+
+ new_rows = []
+ for row in c:
+ new_rows.append({
+ 'id': row[0],
+ 'library_name': row[1],
+ 'library_species_id': row[2],
+ 'hidden': row[3],
+ 'account_number': row[4],
+ 'cell_line_id': row[5],
+ 'condition_id': row[6],
+ 'antibody_id': row[7],
+ 'replicate': row[8],
+ 'experiment_type_id': row[9],
+ 'library_type_id': row[10],
+ 'creation_date': row[11],
+ 'made_for': row[12],
+ 'made_by': row[13],
+ 'stopping_point': row[14],
+ 'amplified_from_sample_id': row[15],
+ 'undiluted_concentration': row[16],
+ 'successful_pM': row[17],
+ 'ten_nM_dilution': row[18],
+ 'avg_lib_size': row[19],
+ 'notes': row[20],
+ })
+
+ sql = '''insert into samples_library
+ (id, library_name, library_species_id, hidden, account_number, cell_line_id,
+ condition_id, antibody_id, replicate, experiment_type_id, library_type_id,
+ creation_date, made_for, made_by, stopping_point, amplified_from_sample_id,
+ undiluted_concentration, successful_pM, ten_nM_dilution, avg_lib_size, notes)
+ values
+ (:id, :library_name, :library_species_id, :hidden, :account_number, :cell_line_id,
+ :condition_id, :antibody_id, :replicate, :experiment_type_id, :library_type_id,
+ :creation_date, :made_for, :made_by, :stopping_point, :amplified_from_sample_id,
+ :undiluted_concentration, :successful_pM, :ten_nM_dilution, :avg_lib_size, :notes);
+ '''
+ c.executemany(sql, new_rows)
+
+ c.execute('drop table old_samples_library;')
+
+def convert_library_id(db_path):
+ conn = sqlite3.connect(db_path)
+ c = conn.cursor()
+
+ lib_ids = map_library_ids(c)
+
+ convert_experiments_lane(c, lib_ids)
+ convert_samples_library_affiliations(c, lib_ids)
+ convert_samples_library_tags(c, lib_ids)
+ convert_samples_library(c, lib_ids)
+
+ conn.commit()
+
+def main():
+ db_path = '/Users/diane/proj/solexa/gaworkflow/svn/woldlab.db'
+ convert_library_id(db_path)
+
+if __name__ == "__main__":
+ main()
class ProjectOptions(admin.ModelAdmin):
list_display = ('ProjTitle','ProjectTasks')
list_filter = ()
- search_fieldsets = ['project_name','=tasks__subject1__library_id','=tasks__subject2__library_id','tasks__subject1__library_name','tasks__subject2__library_name','project_notes']
+ search_fieldsets = ['project_name','=tasks__subject1__id','=tasks__subject2__id','tasks__subject1__library_name','tasks__subject2__library_name','project_notes']
fieldsets = (
(None, {
'fields': (('project_name'),('tasks'),('project_notes'))}),
class TaskOptions(admin.ModelAdmin):
list_display = ('task_name','apply_calc','subject1','subject2','task_params','InProjects','submitted_on','task_status')
list_filter = ('apply_calc',)
- search_fieldsets = ['task_name','id','=subject1__library_id','=subject2__library_id']
+ search_fieldsets = ['task_name','id','=subject1__id','=subject2__id']
fieldsets = (
(None, {
'fields': (('task_name'),('apply_calc'),('subject1'),('subject2'),('task_params'))
if (t.apply_calc == 'QuEST' or t.apply_calc == 'WingPeaks' or t.apply_calc == 'MACS'):
outputfile += '\n<PeakCalling TaskId="'+t.id.__str__()+'" Name="'+t.task_name+'" Caller="'+t.apply_calc+'" Genome="'+t.subject1.library_species.use_genome_build+'">'
if t.subject1:
- outputfile += '\n<Signal Library="'+t.subject1.library_id+'"/>'
+ outputfile += '\n<Signal Library="'+t.subject1.id+'"/>'
if t.subject2:
- outputfile += '\n<Background Library="'+t.subject2.library_id+'"/>'
+ outputfile += '\n<Background Library="'+t.subject2.id+'"/>'
else:
outputfile += '\n<Err>Background Library Missing</Err>'
else:
if (t.apply_calc == 'Methylseq'):
outputfile += '\n<Methylseq TaskId="'+t.id.__str__()+'" Name="'+t.task_name+'" Genome="'+t.subject1.library_species.use_genome_build+'">'
if t.subject1:
- outputfile += '\n<Hpa2 Library="'+t.subject1.library_id+'"/>'
+ outputfile += '\n<Hpa2 Library="'+t.subject1.id+'"/>'
if t.subject2:
- outputfile += '\n<Msp1 Library="'+t.subject2.library_id+'"/>'
+ outputfile += '\n<Msp1 Library="'+t.subject2.id+'"/>'
else:
outputfile += '\n<Err>Msp1 Library Missing</Err>'
else:
outputfile += '\n</Methylseq>'
if (t.apply_calc == 'ProfileReads' or t.apply_calc == 'qPCR'):
- outputfile += '\n<'+t.apply_calc+' TaskId="'+t.id.__str__()+'" Name="'+t.task_name+'" Genome="'+t.subject1.library_species.use_genome_build+'" Library="'+t.subject1.library_id+'"/>'
+ outputfile += '\n<'+t.apply_calc+' TaskId="'+t.id.__str__()+'" Name="'+t.task_name+'" Genome="'+t.subject1.library_species.use_genome_build+'" Library="'+t.subject1.id+'"/>'
if (t.apply_calc == 'CompareLibs'):
outputfile += '\n<CompareLibraries TaskId="'+t.id.__str__()+'" TF="'+t.task_name+'" Genome="'+t.subject1.library_species.use_genome_build+'">'
if t.subject1:
- outputfile += '\n<Library Library="'+t.subject1.library_id+'"/>'
+ outputfile += '\n<Library Library="'+t.subject1.id+'"/>'
else:
outputfile += '\n<Err>Library Missing</Err>'
if t.subject2:
- outputfile += '\n<Library Library="'+t.subject2.library_id+'"/>'
+ outputfile += '\n<Library Library="'+t.subject2.id+'"/>'
else:
outputfile += '\n<Err>Library Missing</Err>'
outputfile += '\n<params>'+t.task_params.__str__()+'</params>'
tstr += '<table><tr><th>Tasks</th><th>Job Status</th>'
isregistered = False
for t in ptasks:
- taskdesc = t.task_name+'<div style="font-size:80%">Details: '+t.apply_calc+' on '+t.subject1.library_id
+ taskdesc = t.task_name+'<div style="font-size:80%">Details: '+t.apply_calc+' on '+t.subject1.id
if t.subject2 is not None:
- taskdesc += ' and '+t.subject2.library_id
+ taskdesc += ' and '+t.subject2.id
taskdesc += ' (TaskId:'+t.id.__str__()+')'
tstr += '<tr><td width=250>%s</td><td>%s</td></tr>' % (taskdesc,replace(t.task_status,'Complete','<span style="color:green;font-weight:bolder">Complete</span>'))
if t.task_status != 'defined': isregistered = True
#Convert all newline conventions to unix style
for lane in fcObj.lane_set.all():
data.append("# Lane%d: %s | %s" % \
- (lane.lane_number, unicode(lane.library.library_id), lane.library.library_name.replace('%', '%%')))
+ (lane.lane_number, unicode(lane.library.id), lane.library.library_name.replace('%', '%%')))
#data.append("GENOME_DIR %s" % (BASE_DIR))
#data.append("CONTAM_DIR %s" % (BASE_DIR))
'run_folder',
'run_note',
'config_params',
- '=fcid__lane_1_library__library_id',
- '=fcid__lane_2_library__library_id',
- '=fcid__lane_3_library__library_id',
- '=fcid__lane_4_library__library_id',
- '=fcid__lane_5_library__library_id',
- '=fcid__lane_6_library__library_id',
- '=fcid__lane_7_library__library_id',
- '=fcid__lane_8_library__library_id'
+ '=fcid__lane_1_library__id',
+ '=fcid__lane_2_library__id',
+ '=fcid__lane_3_library__id',
+ '=fcid__lane_4_library__id',
+ '=fcid__lane_5_library__id',
+ '=fcid__lane_6_library__id',
+ '=fcid__lane_7_library__id',
+ '=fcid__lane_8_library__id'
'fcid__lane_1_library__library_name',
'fcid__lane_2_library__library_name',
'fcid__lane_3_library__library_name',
search_fields = ('flowcell_id',
'sequencer__name',
'cluster_station__name',
- '=lane__library__library_id',
+ '=lane__library__id',
'lane__library__library_name')
list_display = ('flowcell_id','run_date','Lanes')
list_filter = ('sequencer','cluster_station')
'fields': ('run_date', ('flowcell_id','cluster_station','sequencer'), ('read_length', 'control_lane', 'paired_end'),)
}),
#('Lanes:', {
- # 'fields' : (('lane__library__library_id', 'lane__pM', 'lane__cluster_estimate'),)
+ # 'fields' : (('lane__library__id', 'lane__pM', 'lane__cluster_estimate'),)
#}),
('Notes:', { 'fields': ('notes',),}),
)
'flowcell': lane.flowcell.flowcell_id,
'lane_number': int(lane.lane_number),
'library_name': lane.library.library_name,
- 'library_id': lane.library.library_id,
+ 'library_id': lane.library.id,
'library_species': lane.library.library_species.scientific_name,
'pM': float(lane.pM),
'read_length': fc.read_length
mydate = year+month+day
outputfile = '<?xml version="1.0" ?>'
outputfile += '\n<SolexaResult Date="'+mydate+'" Flowcell="'+fcid+'" Client="'+settings.ALLOWED_IPS[ClIP]+'">'
- outputfile += '\n<Lane Index="1" Name="'+rec.lane_1_library.library_name+'" Library="'+rec.lane_1_library.library_id+'" Genome="'+rec.lane_1_library.library_species.use_genome_build+'" PrimerName="" PrimerSeq=""/>'
- outputfile += '\n<Lane Index="2" Name="'+rec.lane_2_library.library_name+'" Library="'+rec.lane_2_library.library_id+'" Genome="'+rec.lane_2_library.library_species.use_genome_build+'" PrimerName="" PrimerSeq=""/>'
- outputfile += '\n<Lane Index="3" Name="'+rec.lane_3_library.library_name+'" Library="'+rec.lane_3_library.library_id+'" Genome="'+rec.lane_3_library.library_species.use_genome_build+'" PrimerName="" PrimerSeq=""/>'
- outputfile += '\n<Lane Index="4" Name="'+rec.lane_4_library.library_name+'" Library="'+rec.lane_4_library.library_id+'" Genome="'+rec.lane_4_library.library_species.use_genome_build+'" PrimerName="" PrimerSeq=""/>'
- outputfile += '\n<Lane Index="5" Name="'+rec.lane_5_library.library_name+'" Library="'+rec.lane_5_library.library_id+'" Genome="'+rec.lane_5_library.library_species.use_genome_build+'" PrimerName="" PrimerSeq=""/>'
- outputfile += '\n<Lane Index="6" Name="'+rec.lane_6_library.library_name+'" Library="'+rec.lane_6_library.library_id+'" Genome="'+rec.lane_6_library.library_species.use_genome_build+'" PrimerName="" PrimerSeq=""/>'
- outputfile += '\n<Lane Index="7" Name="'+rec.lane_7_library.library_name+'" Library="'+rec.lane_7_library.library_id+'" Genome="'+rec.lane_7_library.library_species.use_genome_build+'" PrimerName="" PrimerSeq=""/>'
- outputfile += '\n<Lane Index="8" Name="'+rec.lane_8_library.library_name+'" Library="'+rec.lane_8_library.library_id+'" Genome="'+rec.lane_8_library.library_species.use_genome_build+'" PrimerName="" PrimerSeq=""/>'
+ outputfile += '\n<Lane Index="1" Name="'+rec.lane_1_library.library_name+'" Library="'+rec.lane_1_library.id+'" Genome="'+rec.lane_1_library.library_species.use_genome_build+'" PrimerName="" PrimerSeq=""/>'
+ outputfile += '\n<Lane Index="2" Name="'+rec.lane_2_library.library_name+'" Library="'+rec.lane_2_library.id+'" Genome="'+rec.lane_2_library.library_species.use_genome_build+'" PrimerName="" PrimerSeq=""/>'
+ outputfile += '\n<Lane Index="3" Name="'+rec.lane_3_library.library_name+'" Library="'+rec.lane_3_library.id+'" Genome="'+rec.lane_3_library.library_species.use_genome_build+'" PrimerName="" PrimerSeq=""/>'
+ outputfile += '\n<Lane Index="4" Name="'+rec.lane_4_library.library_name+'" Library="'+rec.lane_4_library.id+'" Genome="'+rec.lane_4_library.library_species.use_genome_build+'" PrimerName="" PrimerSeq=""/>'
+ outputfile += '\n<Lane Index="5" Name="'+rec.lane_5_library.library_name+'" Library="'+rec.lane_5_library.id+'" Genome="'+rec.lane_5_library.library_species.use_genome_build+'" PrimerName="" PrimerSeq=""/>'
+ outputfile += '\n<Lane Index="6" Name="'+rec.lane_6_library.library_name+'" Library="'+rec.lane_6_library.id+'" Genome="'+rec.lane_6_library.library_species.use_genome_build+'" PrimerName="" PrimerSeq=""/>'
+ outputfile += '\n<Lane Index="7" Name="'+rec.lane_7_library.library_name+'" Library="'+rec.lane_7_library.id+'" Genome="'+rec.lane_7_library.library_species.use_genome_build+'" PrimerName="" PrimerSeq=""/>'
+ outputfile += '\n<Lane Index="8" Name="'+rec.lane_8_library.library_name+'" Library="'+rec.lane_8_library.id+'" Genome="'+rec.lane_8_library.library_species.use_genome_build+'" PrimerName="" PrimerSeq=""/>'
outputfile += '\n</SolexaResult>'
except ObjectDoesNotExist:
outputfile = 'Flowcell entry not found for: '+fcid
{"pk": 1193, "model": "experiments.lane",
"fields": {
"comment": "No change in cluster numbers, despite slight increase in pM",
- "library": 10984,
+ "library": "10981",
"cluster_estimate": 129000,
"flowcell": 153,
"lane_number": 1,
"pM": "8"
}
},
- {"pk": 10984, "model": "samples.library",
+ {"pk": "10981", "model": "samples.library",
"fields": {
- "library_id": "10981",
"ten_nM_dilution": false,
"avg_lib_size": 400,
"library_name": "Paired End Multiplexed Sp-BAC",
{"pk": 1194, "model": "experiments.lane",
"fields": {
"comment": "",
- "library": 11019,
+ "library": "11016",
"cluster_estimate": 152000,
"flowcell": 153,
"lane_number": 2,
}
},
{
- "pk": 11019,
+ "pk": "11016",
"model": "samples.library",
"fields": {
- "library_id": "11016",
"ten_nM_dilution": false,
"avg_lib_size": 325,
"library_name": "Paired End Pfl #3 MP 7/24/9 a",
{"pk": 1195, "model": "experiments.lane",
"fields": {
"comment": "",
- "library": 11042,
+ "library": "SL039",
"cluster_estimate": 162000,
"flowcell": 153,
"lane_number": 3,
}
},
{
- "pk": 11042,
+ "pk": "SL039",
"model": "samples.library",
"fields": {
- "library_id": "SL039",
"ten_nM_dilution": false,
"avg_lib_size": 300,
"library_name": "Paired ends 99 GM12892",
{"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)",
- "library": 11063,
+ "library": "11060",
"cluster_estimate": 24000,
"flowcell": 153,
"lane_number": 4,
}
},
{
- "pk": 11063,
+ "pk": "11060",
"model": "samples.library",
"fields": {
- "library_id": "11060",
"ten_nM_dilution": false,
"avg_lib_size": 300,
"library_name": "Paired ends 100 VC_CN_4_M_MBB1185_s1",
{"pk": 1197, "model": "experiments.lane",
"fields": {
"comment": "",
- "library": 11064,
+ "library": "11061",
"cluster_estimate": 140000,
"flowcell": 153,
"lane_number": 5,
}
},
{
- "pk": 11064,
+ "pk": "11061",
"model": "samples.library",
"fields": {
- "library_id": "11061",
"ten_nM_dilution": false,
"avg_lib_size": 300,
"library_name": "Paired ends 101 VC_CN_4_M_MBB1185_s2",
{"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)",
- "library": 11065,
+ "library": "11062",
"cluster_estimate": 2000,
"flowcell": 153,
"lane_number": 6,
}
},
{
- "pk": 11065,
+ "pk": "11062",
"model": "samples.library",
"fields": {
- "library_id": "11062",
"ten_nM_dilution": false,
"avg_lib_size": 300,
"library_name": "Paired ends 102 VC_AU_8_M_MBB4721_s1",
{"pk": 1199, "model": "experiments.lane",
"fields": {
"comment": "",
- "library": 11066,
+ "library": "11063",
"cluster_estimate": 120000,
"flowcell": 153,
"lane_number": 7,
}
},
{
- "pk": 11066,
+ "pk": "11063",
"model": "samples.library",
"fields": {
- "library_id": "11063",
"ten_nM_dilution": false,
"avg_lib_size": 300,
"library_name": "Paired ends 103 VC_AU_8_M_MBB4721_s2",
{"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",
- "library": 11067,
+ "library": "11064",
"cluster_estimate": 157000,
"flowcell": 153,
"lane_number": 8,
}
},
{
- "pk": 11067,
+ "pk": "11064",
"model": "samples.library",
"fields": {
- "library_id": "11064",
"ten_nM_dilution": false,
"avg_lib_size": 300,
"library_name": "Paired ends 104 VC_CN_7_M_MBB4898_s1",
{"pk": 1185, "model": "experiments.lane",
"fields": {
"comment": "",
- "library": 11038,
+ "library": "11035",
"cluster_estimate": 174000,
"flowcell": 152,
"lane_number": 1,
}
},
{
- "pk": 11038,
+ "pk": "11035",
"model": "samples.library",
"fields": {
- "library_id": "11035",
"ten_nM_dilution": false,
"avg_lib_size": 300,
"library_name": "Paired ends 95 Gilberto_d3_control_LTA",
{"pk": 1186, "model": "experiments.lane",
"fields": {
"comment": "",
- "library": 11040,
+ "library": "11037",
"cluster_estimate": 173000,
"flowcell": 152,
"lane_number": 2,
}
},
{
- "pk": 11040,
+ "pk": "11037",
"model": "samples.library",
"fields": {
- "library_id": "11037",
"ten_nM_dilution": false,
"avg_lib_size": 300,
"library_name": "Paired ends 97 Kuntz_PDHT",
{"pk": 1187, "model": "experiments.lane",
"fields": {
"comment": "",
- "library": 11048,
+ "library": "11045",
"cluster_estimate": 198000,
"flowcell": 152,
"lane_number": 3,
}
},
{
- "pk": 11048,
+ "pk": "11045",
"model": "samples.library",
"fields": {
- "library_id": "11045",
"ten_nM_dilution": false,
"avg_lib_size": 250,
"library_name": "FLDN1 8/3/9 anti-AcH3 chip B6 a",
{"pk": 1188, "model": "experiments.lane",
"fields": {
"comment": "",
- "library": 11049,
+ "library": "11046",
"cluster_estimate": 212000,
"flowcell": 152,
"lane_number": 4,
"pM": "7"}
},
{
- "pk": 11049,
+ "pk": "11046",
"model": "samples.library",
"fields": {
- "library_id": "11046",
"ten_nM_dilution": false,
"avg_lib_size": 250,
"library_name": "FLDN1 7/8/9 anti-DiMeH3K4 chip B6 a",
{"pk": 1189, "model": "experiments.lane",
"fields": {
"comment": "",
- "library": 11057,
+ "library": "11054",
"cluster_estimate": 49000,
"flowcell": 152,
"lane_number": 5,
}
},
{
- "pk": 11057,
+ "pk": "11054",
"model": "samples.library",
"fields": {
- "library_id": "11054",
"ten_nM_dilution": false,
"avg_lib_size": 225,
"library_name": "HNDHT HLH hnd-1 strain HT115 fed anti-hlh-1 2% fix plate a",
{"pk": 1190, "model": "experiments.lane",
"fields": {
"comment": "",
- "library": 11059,
+ "library": "11056",
"cluster_estimate": 48000,
"flowcell": 152,
"lane_number": 6,
}
},
{
- "pk": 11059,
+ "pk": "11056",
"model": "samples.library",
"fields": {
- "library_id": "11056",
"ten_nM_dilution": false,
"avg_lib_size": 225,
"library_name": "HNDM3 HLH hnd-1 strain mex-3 fed anti-hlh-1 2% fix plate a",
{"pk": 1191, "model": "experiments.lane",
"fields": {
"comment": "",
- "library": 11060,
+ "library": "11057",
"cluster_estimate": 4000,
"flowcell": 152,
"lane_number": 7,
}
},
{
- "pk": 11060,
+ "pk": "11057",
"model": "samples.library",
"fields": {
- "library_id": "11057",
"ten_nM_dilution": false,
"avg_lib_size": 225,
"library_name": "HNDM3 4H8 hnd-1 strain mex-3 fed 4H8 2% fix plate a",
{"pk": 1192, "model": "experiments.lane",
"fields": {
"comment": "",
- "library": 11068,
+ "library": "11065",
"cluster_estimate": 5000,
"flowcell": 152,
"lane_number": 8,
}
},
{
- "pk": 11068,
+ "pk": "11065",
"model": "samples.library",
"fields": {
- "library_id": "11065",
"ten_nM_dilution": false,
"avg_lib_size": 300,
"library_name": "Paired ends 105 Kuntz PDM3",
{"pk": 1177, "model": "experiments.lane",
"fields": {
"comment": "",
- "library": 11037,
+ "library": "11034",
"cluster_estimate": 177000,
"flowcell": 151,
"lane_number": 1,
{"pk": 1178, "model": "experiments.lane",
"fields": {
"comment": "",
- "library": 11039,
+ "library": "11036",
"cluster_estimate": 169000,
"flowcell": 151,
"lane_number": 2,
}
},
{
- "pk": 11039,
+ "pk": "11036",
"model": "samples.library",
"fields": {
- "library_id": "11036",
"ten_nM_dilution": false,
"avg_lib_size": 300,
"library_name": "Paired ends 96 Kuntz_PDE1",
}
},
{
- "pk": 11037,
+ "pk": "11034",
"model": "samples.library",
"fields": {
- "library_id": "11034",
"ten_nM_dilution": false,
"avg_lib_size": 300,
"library_name": "Paired ends 94 Gilberto_d3_denerv_LTA",
}
},
{
- "pk": 11047,
+ "pk": "11044",
"model": "samples.library",
"fields": {
- "library_id": "11044",
"ten_nM_dilution": false,
"avg_lib_size": 225,
"library_name": "p300 60h C2 FA KF 12/22/8 a",
"model": "experiments.lane",
"fields": {
"comment": "",
- "library": 11047,
+ "library": "11044",
"cluster_estimate": 196000,
"flowcell": 151,
"lane_number": 3,
}
},
{
- "pk": 11047,
+ "pk": "11044",
"model": "samples.library",
"fields": {
- "library_id": "11044",
"ten_nM_dilution": false,
"avg_lib_size": 225,
"library_name": "p300 60h C2 FA KF 12/22/8 a",
{"pk": 1180, "model": "experiments.lane",
"fields": {
"comment": "",
- "library": 11050,
+ "library": "11047",
"cluster_estimate": 200000,
"flowcell": 151,
"lane_number": 4,
}
},
{
- "pk": 11050,
+ "pk": "11047",
"model": "samples.library",
"fields": {
- "library_id": "11047",
"ten_nM_dilution": false,
"avg_lib_size": 250,
"library_name": "FLDN1 7/8/9 anti-TriMeH3K27 chip B6 a",
{"pk": 1181, "model": "experiments.lane",
"fields": {
"comment": "",
- "library": 11058,
+ "library": "11055",
"cluster_estimate": 104000,
"flowcell": 151,
"lane_number": 5,
}
},
{
- "pk": 11058,
+ "pk": "11055",
"model": "samples.library",
"fields": {
- "library_id": "11055",
"ten_nM_dilution": false,
"avg_lib_size": 225,
"library_name": "HNDHT 4H8 hnd-1 strain HT115 fed 4H8 2% fix plate a",
{"pk": 1182, "model": "experiments.lane",
"fields": {
"comment": "",
- "library": 11070,
+ "library": "11067",
"cluster_estimate": 168000,
"flowcell": 151,
"lane_number": 6,
}
},
{
- "pk": 11070,
+ "pk": "11067",
"model": "samples.library",
"fields": {
- "library_id": "11067",
"ten_nM_dilution": false,
"avg_lib_size": 325,
"library_name": "Paired End SP-BAC Barcoding test 250-300 bp",
{"pk": 1183, "model": "experiments.lane",
"fields": {
"comment": "",
- "library": 11072,
+ "library": "11069",
"cluster_estimate": 184000,
"flowcell": 151,
"lane_number": 7,
}
},
{
- "pk": 11072,
+ "pk": "11069",
"model": "samples.library",
"fields": {
- "library_id": "11069",
"ten_nM_dilution": false,
"avg_lib_size": 300,
"library_name": "Paired End AG-3d-1 AG domain of floral meristem day 3, rep 1",
{"pk": 1184, "model": "experiments.lane",
"fields": {
"comment": "",
- "library": 11073,
+ "library": "11070",
"cluster_estimate": 182000,
"flowcell": 151,
"lane_number": 8,
}
},
{
- "pk": 11073,
+ "pk": "11070",
"model": "samples.library",
"fields": {
- "library_id": "11070",
"ten_nM_dilution": false,
"avg_lib_size": 300,
"library_name": "Paired End AG-5d-1 AG domain of floral meristem day 5, rep 1",
import re
+from BeautifulSoup import BeautifulSoup
try:
import json
except ImportError, e:
from htsworkflow.frontend.experiments import experiments
from htsworkflow.frontend.auth import apidata
+LANE_SET = range(1,9)
+
class ExperimentsTestCases(TestCase):
fixtures = ['test_flowcells.json']
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.library_id)
+ self.failUnlessEqual(lane_dict['library_id'], lane.library.id)
self.failUnlessAlmostEqual(lane_dict['pM'], float(lane.pM))
self.failUnlessEqual(lane_dict['library_species'],
lane.library.library_species.scientific_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.library_id)
+ self.failUnlessEqual(lane_dict['library_id'], lane.library.id)
self.failUnlessAlmostEqual(lane_dict['pM'], float(lane.pM))
self.failUnlessEqual(lane_dict['library_species'],
lane.library.library_species.scientific_name)
self.failUnlessEqual(library_sl039['library_id'], 'SL039')
+ def test_raw_id_field(self):
+ """
+ Test ticket:147
+
+ 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.
+
+ 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']
+ 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):
+ 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(':')
+ # strip leading '#' sign from name
+ library_id = library_id[1:]
+ self.failUnlessEqual(library_id, expected_ids[i])
+ self.failUnlessEqual(input_field['value'], library_id)
+
class TestEmailNotify(TestCase):
fixtures = ['test_flowcells.json']
save_as = True
save_on_top = True
search_fields = (
- 'library_id',
+ 'id',
'library_name',
'cell_line__cellline_name',
'library_species__scientific_name',
'library_species__common_name',
)
list_display = (
- 'library_id',
+ 'id',
#'aligned_reads',
#'DataRun',
'library_name',
'condition',
'stopping_point',
'hidden')
- list_display_links = ('library_id', 'library_name',)
+ list_display_links = ('id', 'library_name',)
fieldsets = (
(None, {
'fields': (
- ('library_id','library_name','hidden'),
+ ('id','library_name','hidden'),
('library_species'),
('library_type', 'experiment_type', 'replicate'),
('cell_line','condition','antibody'),)
"date_joined": "2009-01-01 00:01:01"
}
},
- {"pk": 10984, "model": "samples.library",
+ {"pk": "10981", "model": "samples.library",
"fields": {
- "library_id": "10981",
"ten_nM_dilution": false,
"avg_lib_size": 400,
"library_name": "Paired End Multiplexed Sp-BAC",
}
},
{
- "pk": 11019,
+ "pk": "11016",
"model": "samples.library",
"fields": {
- "library_id": "11016",
"ten_nM_dilution": false,
"avg_lib_size": 325,
"library_name": "Paired End Pfl #3 MP 7/24/9 a",
}
},
{
- "pk": 11042,
+ "pk": "11039",
"model": "samples.library",
"fields": {
- "library_id": "11039",
"ten_nM_dilution": false,
"avg_lib_size": 300,
"library_name": "Paired ends 99 GM12892",
}
},
{
- "pk": 11006,
+ "pk": "11003",
"model": "samples.library",
"fields": {
- "library_id": "11003",
"ten_nM_dilution": false,
"avg_lib_size": 325,
"library_name": "Paired End Pfl #3 MP 7/24/9",
return unicode(self.name)
class Library(models.Model):
- id = models.AutoField(primary_key=True)
- library_id = models.CharField(max_length=30, db_index=True, unique=True)
+ id = models.CharField(max_length=10, primary_key=True)
library_name = models.CharField(max_length=100, unique=True)
library_species = models.ForeignKey(Species)
# new field 2008 Mar 5, alter table samples_library add column "hidden" NOT NULL default 0;
notes = models.TextField(blank=True)
def __unicode__(self):
- return u'#%s: %s' % (self.library_id, self.library_name)
+ return u'#%s: %s' % (self.id, self.library_name)
class Meta:
verbose_name_plural = "libraries"
#ordering = ["-creation_date"]
- ordering = ["-library_id"]
+ ordering = ["-id"]
def antibody_name(self):
str ='<a target=_self href="/admin/samples/antibody/'+self.antibody.id.__str__()+'/" title="'+self.antibody.__str__()+'">'+self.antibody.nickname+'</a>'
return u'%s' % ( ", ".join(ar))
def DataRun(self):
- str ='<a target=_self href="/admin/experiments/datarun/?q='+self.library_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
def aligned_m_reads(self):
- return getLibReads(self.library_id)
+ return getLibReads(self.id)
def aligned_reads(self):
- res = getLibReads(self.library_id)
+ res = getLibReads(self.id)
# Check data sanity
if res[2] != "OK":
@models.permalink
def get_absolute_url(self):
- return ('htsworkflow.frontend.samples.views.library_to_flowcells', [str(self.library_id)])
+ return ('htsworkflow.frontend.samples.views.library_to_flowcells', [str(self.id)])
class HTSUser(User):
"""
Library.objects.all().delete()
obj.library_10001 = Library(
- library_id = 10001,
+ id = "10001",
library_name = 'C2C12 named poorly',
library_species = obj.species_human,
experiment_type = obj.experiment_rna_seq,
)
obj.library_10001.save()
obj.library_10002 = Library(
- library_id = 10002,
+ id = "10002",
library_name = 'Worm named poorly',
library_species = obj.species_human,
experiment_type = obj.experiment_rna_seq,
def test_library_info(self):
for lib in Library.objects.all():
- lib_dict = library_dict(lib.library_id)
- url = '/samples/library/%s/json' % (lib.library_id,)
+ lib_dict = library_dict(lib.id)
+ url = '/samples/library/%s/json' % (lib.id,)
lib_response = self.client.get(url, apidata)
self.failUnlessEqual(lib_response.status_code, 200)
lib_json = json.loads(lib_response.content)
for d in [lib_dict, lib_json]:
# amplified_from_sample is a link to the library table,
- # I want to use the "library_id" for the data lookups not
+ # I want to use the "id" for the data lookups not
# the embedded primary key.
# It gets slightly confusing on how to implement sending the right id
# since amplified_from_sample can be null
self.failUnlessEqual(d['experiment_type'], lib.experiment_type.name)
self.failUnlessEqual(d['experiment_type_id'], lib.experiment_type_id)
self.failUnlessEqual(d['id'], lib.id)
- self.failUnlessEqual(d['library_id'], lib.library_id)
self.failUnlessEqual(d['library_name'], lib.library_name)
self.failUnlessEqual(d['library_species'], lib.library_species.scientific_name)
self.failUnlessEqual(d['library_species_id'], lib.library_species_id)
#for lib in library_items.object_list:
for lib in cl.result_list:
summary = {}
- summary['library_id'] = lib.library_id
+ summary['library_id'] = lib.id
summary['library_name'] = lib.library_name
summary['species_name' ] = lib.library_species.scientific_name
if lib.amplified_from_sample is not None:
- summary['amplified_from'] = lib.amplified_from_sample.library_id
+ summary['amplified_from'] = lib.amplified_from_sample.id
else:
summary['amplified_from'] = ''
lanes_run = 0
# build changelist
fcl = ChangeList(request, Library,
list_filter=['affiliations', 'library_species'],
- search_fields=['library_id', 'library_name', 'amplified_from_sample__library_id'],
+ search_fields=['id', 'library_name', 'amplified_from_sample__id'],
list_per_page=200,
queryset=Library.objects.filter(hidden__exact=0)
)
"""
try:
- lib = Library.objects.get(library_id=lib_id)
+ lib = Library.objects.get(id=lib_id)
except:
return HttpResponse("Library %s does not exist" % (lib_id))
return '(' + '|'.join(output) + ')'
def library_id_to_admin_url(request, lib_id):
- lib = Library.objects.get(library_id=lib_id)
+ lib = Library.objects.get(id=lib_id)
return HttpResponseRedirect('/admin/samples/library/%s' % (lib.id,))
def library_dict(library_id):
return None if nothing was found
"""
try:
- lib = Library.objects.get(library_id = library_id)
+ lib = Library.objects.get(id = library_id)
except Library.DoesNotExist, e:
return None
'experiment_type': lib.experiment_type.name,
'experiment_type_id': lib.experiment_type_id,
'id': lib.id,
- 'library_id': lib.library_id,
+ 'library_id': lib.id,
'library_name': lib.library_name,
'library_species': lib.library_species.scientific_name,
'library_species_id': lib.library_species_id,
</tr>
<tr><td valign=middle nowrap>Solexa Library Number</td>
{% for lane in fc.lane_set.all %}
-<td bgcolor=#CCFFCC>{{ lane.library.library_id }}</td>
+<td bgcolor=#CCFFCC>{{ lane.library.id }}</td>
{% endfor %}
</tr>
</p>
<p>{% for lane in lanes %}
Lane #{{ lane.lane_number }} :
-<a href="https://jumpgate.caltech.edu/library/{{lane.library.library_id}}">
-{{ lane.library.library_id }}</a>
+<a href="https://jumpgate.caltech.edu/library/{{lane.library.id}}">
+{{ lane.library.id }}</a>
{{ lane.library.library_name }}<br/>
{% endfor %}</p>
<p>
Lane : (Library Id) Library Name (Cluster Estimate)
{% for lane in lanes %}
-Lane #{{ lane.lane_number }} : ({{ lane.library.library_id }}) {{ lane.library.library_name }} ({{ lane.cluster_estimate }})
- http://jumpgate.caltech.edu/library/{{ lane.library.library_id }}
+Lane #{{ lane.lane_number }} : ({{ lane.library.id }}) {{ lane.library.library_name }} ({{ lane.cluster_estimate }})
+ http://jumpgate.caltech.edu/library/{{ lane.library.id }}
{% endfor %}
The raw data should be available at the following link when
{% block content %}
<div id="librarydetail">
<h2>About this library</h2>
- <b>Library ID</b>: {{ lib.library_id }}<br/>
+ <b>Library ID</b>: {{ lib.id }}<br/>
<b>Name</b>: {{ lib.library_name }}<br/>
<b>Species</b>: {{ lib.library_species.scientific_name }}<br/>
<b>Affiliations</b>:
projects / htsworkflow.git / commitdiff