def _compute_pools(self, plate_info):
self.plate_id = plate_info['plate-id']
self.func_name = plate_info['pool-func']
self.plate_type = plate_info['plate-type']
self.quant_process_id = plate_info['quant-process-id']
func_info = POOL_FUNCS[self.func_name]
self.function = func_info['function']
plate = Plate(self.plate_id)
quant_process = QuantificationProcess(self.quant_process_id)
# make params dictionary for function
params = {}
for arg, pfx in func_info['parameters']:
param_key = '%s%s' % (pfx, self.plate_id)
if param_key not in plate_info:
raise HTTPError(400, reason='Missing parameter %s' % param_key)
# empty strings are sent when we have disabled inputs.
# we are testing for them explicitly where expected.
if plate_info[param_key] != '':
params[arg] = float(plate_info[param_key])
else:
params[arg] = plate_info[param_key]
self.params = params
# compute molar concentrations
quant_process.compute_concentrations(size=params['size'])
# calculate pooled values
self.raw_concs, self.comp_concs, self.comp_blanks, \
self.plate_names = make_2D_arrays(plate, quant_process)
def post(self):
pool_name = self.get_argument('pool_name')
pools_info = json_decode(self.get_argument('pools_info'))
concentrations = []
input_compositions = []
for p_info in pools_info:
pool_comp = PoolComposition(p_info['pool_id'])
concentrations.append({
'composition': pool_comp,
'concentration': p_info['concentration']
})
input_compositions.append({
'composition':
pool_comp,
'input_volume':
p_info['volume'],
'percentage_of_output':
p_info['percentage']
})
# Create the quantification process (DNA conc)
q_process = QuantificationProcess.create_manual(
self.current_user, concentrations)
# Create the pool - Magic number 5 - > the volume for this pooling
# is always 5 according to the wet lab.
p_process = PoolingProcess.create(self.current_user, q_process,
pool_name, 5, input_compositions, {
"function": "amplicon_pool",
"parameters": {}
})
self.write({'process': p_process.id})
def create_pool_quantification_process(user, pools):
concentrations = np.around(np.random.rand(len(pools)), 6)
concentrations = [{
'composition': p,
'concentration': c
} for p, c in zip(pools, concentrations)]
return QuantificationProcess.create_manual(user, concentrations)
def post(self):
plates_info = json_decode(self.get_argument('plates-info'))
results = []
for pinfo in plates_info:
plate_result = self._compute_pools(pinfo)
plate = Plate(plate_result['plate_id'])
# calculate estimated molar fraction for each element of pool
amts = plate_result['comp_vals'] * plate_result['pool_vals']
pcts = amts / amts.sum()
quant_process = QuantificationProcess(
plate_result['quant-process-id'])
pool_name = 'Pool from plate %s (%s)' % (
plate.external_id, datetime.now().strftime(
quant_process.get_date_format()))
input_compositions = []
for comp, _, _ in quant_process.concentrations:
well = comp.container
row = well.row - 1
column = well.column - 1
input_compositions.append({
'composition':
comp,
'input_volume':
plate_result['pool_vals'][row][column],
'percentage_of_output':
pcts[row][column]
})
robot = (Equipment(plate_result['robot'])
if plate_result['robot'] is not None else None)
process = PoolingProcess.create(
self.current_user,
quant_process,
pool_name,
plate_result['pool_vals'].sum(),
input_compositions,
plate_result['func_data'],
robot=robot,
destination=plate_result['destination'])
results.append({'plate-id': plate.id, 'process-id': process.id})
self.write(json_encode(results))
def post(self):
# We will receive as many files as plates the user has selected
# The key of the self.request.files dictionary is of the form
# plate-file-<PLATE_ID> so use the keys to know the plates
# that we need to quantify
plates = []
for key in self.request.files:
plate_id = key.rsplit('-', 1)[1]
# The 0 is because for each key we have a single file
file_content = self.request.files[key][0]['body'].decode('utf-8')
plate = Plate(plate_id)
pc = plate.plate_configuration
concentrations = QuantificationProcess.parse(
file_content, rows=pc.num_rows, cols=pc.num_columns)
names = np.empty_like(plate.layout, dtype='object')
blanks = np.zeros_like(plate.layout, dtype=bool)
# fetch the sample names and whether or not the samples are blanks
# by default these are set to be None and False.
for i, full_row in enumerate(plate.layout):
for j, well in enumerate(full_row):
# some wells have no compositions at all so skip those
if well is None:
continue
comp = well.composition
# cache the sample compositions to avoid extra intermediate
# queries
if isinstance(comp, GDNAComposition):
smp = comp.sample_composition
elif isinstance(comp, (CompressedGDNAComposition,
LibraryPrep16SComposition)):
smp = comp.gdna_composition.sample_composition
elif isinstance(comp, LibraryPrepShotgunComposition):
smp = comp.normalized_gdna_composition\
.compressed_gdna_composition.gdna_composition\
.sample_composition
else:
raise ValueError('This composition type is not '
'supported')
blanks[i][j] = smp.sample_composition_type == 'blank'
names[i][j] = smp.sample_id
plates.append({'plate_name': plate.external_id,
'plate_id': plate_id,
'concentrations': concentrations.tolist(),
'names': names.tolist(),
'blanks': blanks.tolist(),
'type': plate.process._process_type
})
self.render('quantification.html', plates=plates)
def post(self):
plates_info = json_decode(self.get_argument('plates-info'))
processes = []
for pinfo in plates_info:
plate = Plate(pinfo['plate_id'])
concentrations = np.asarray(pinfo['concentrations'])
processes.append(QuantificationProcess.create(
self.current_user, plate, concentrations).id)
self.write({'processes': processes})
def post(self):
user = self.current_user
plates_info = self.get_argument('plates_info')
water = self.get_argument('water')
total_vol = self.get_argument('total_vol')
ng = self.get_argument('ng')
min_vol = self.get_argument('min_vol')
max_vol = self.get_argument('max_vol')
resolution = self.get_argument('resolution')
reformat = self.get_argument('reformat')
# NB: JavaScript uses true and false, posting converts them to strings
reformat = reformat == 'true'
processes = [
[plate_id, NormalizationProcess.create(
user, QuantificationProcess(quantification_process_id),
ReagentComposition.from_external_id(water),
plate_name, total_vol=float(total_vol), ng=float(ng),
min_vol=float(min_vol), max_vol=float(max_vol),
resolution=float(resolution), reformat=reformat).id]
for plate_id, plate_name, quantification_process_id in
json_decode(plates_info)]
self.write({'processes': processes})
def _compute_pools(self, plate_info):
plate_id = plate_info['plate-id']
func_name = plate_info['pool-func']
plate_type = plate_info['plate-type']
quant_process_id = plate_info['quant-process-id']
func_info = POOL_FUNCS[func_name]
function = func_info['function']
plate = Plate(plate_id)
quant_process = QuantificationProcess(quant_process_id)
# make params dictionary for function
params = {}
for arg, pfx in func_info['parameters']:
param_key = '%s%s' % (pfx, plate_id)
if param_key not in plate_info:
raise HTTPError(
400, reason='Missing parameter %s' % param_key)
# empty strings are sent when we have disabled inputs.
# we are testing for them explicitly where expected.
if plate_info[param_key] != '':
params[arg] = float(plate_info[param_key])
else:
params[arg] = plate_info[param_key]
# compute molar concentrations
quant_process.compute_concentrations(size=params['size'])
# calculate pooled values
raw_concs, comp_concs, comp_blanks, \
plate_names = make_2D_arrays(plate, quant_process)
# for 16S, we calculate each sample independently
pool_type = PLATE_TYPE_TO_POOL_TYPE[plate_type]
params['total_each'] = POOL_TYPE_PARAMS[pool_type]['total_each']
params['vol_constant'] = POOL_TYPE_PARAMS[pool_type]['vol_constant']
pool_vals = function(raw_concs, **params)
# if adjust blank volume, do that
if params['blank_vol'] != '':
pool_vals = PoolingProcess.adjust_blank_vols(pool_vals,
comp_blanks,
params['blank_vol'])
# if only pool some blanks, do that
if params['blank_num'] != '':
pool_vals = PoolingProcess.select_blanks(pool_vals,
raw_concs,
comp_blanks,
int(params['blank_num']))
# estimate pool volume and concentration
total_c, total_v = PoolingProcess.estimate_pool_conc_vol(pool_vals,
comp_concs)
# store output values
output = {}
output['func_data'] = {'function': func_name,
'parameters': params}
output['raw_vals'] = raw_concs
output['comp_vals'] = comp_concs
output['pool_vals'] = pool_vals
output['pool_blanks'] = comp_blanks.tolist()
output['plate_names'] = plate_names.tolist()
output['plate_id'] = plate_id
output['destination'] = params['destination']
output['robot'] = params['robot']
output['blank_vol'] = params['blank_vol']
output['blank_num'] = params['blank_num']
output['total_conc'] = total_c
output['total_vol'] = total_v
output['quant-process-id'] = quant_process_id
return output
def test_properties(self):
# Plate 21 - Defined in the test DB
tester = Plate(21)
obs = tester.creation_timestamp
obs = str(datetime.datetime(obs.year, obs.month, obs.day))
exp = datetime.datetime.now()
exp = str(datetime.datetime(exp.year, exp.month, exp.day))
self.assertEqual(obs, exp)
self.assertEqual(tester.external_id, 'Test plate 1')
self.assertEqual(tester.plate_configuration, PlateConfiguration(1))
self.assertFalse(tester.discarded)
tester.discarded = True
self.assertTrue(tester.discarded)
self.assertIsNone(tester.notes)
obs_layout = tester.layout
self.assertEqual(len(obs_layout), 8)
for row in obs_layout:
self.assertEqual(len(row), 12)
self.assertEqual(tester.studies, {Study(1)})
self.assertListEqual(tester.quantification_processes, [])
self.assertEqual(tester.process, SamplePlatingProcess(11))
# Test changing the name of the plate
tester.external_id = 'Some new name'
self.assertEqual(tester.external_id, 'Some new name')
tester.external_id = 'Test plate 1'
self.assertEqual(tester.external_id, 'Test plate 1')
self.assertEqual(len(Plate(23).quantification_processes), 1)
self.assertEqual(
Plate(23).quantification_processes[0], QuantificationProcess(1))
self.assertEqual(Plate(22).process, GDNAExtractionProcess(1))
exp = {
'1.SKB1.640202': [[Well(3073), '1.SKB1.640202.Test.plate.1.A1'],
[Well(3121), '1.SKB1.640202.Test.plate.1.A2'],
[Well(3169), '1.SKB1.640202.Test.plate.1.A3'],
[Well(3217), '1.SKB1.640202.Test.plate.1.A4'],
[Well(3265), '1.SKB1.640202.Test.plate.1.A5'],
[Well(3313), '1.SKB1.640202.Test.plate.1.A6'],
[Well(3361), '1.SKB1.640202.Test.plate.1.A7'],
[Well(3409), '1.SKB1.640202.Test.plate.1.A8'],
[Well(3457), '1.SKB1.640202.Test.plate.1.A9'],
[Well(3505), '1.SKB1.640202.Test.plate.1.A10'],
[Well(3553), '1.SKB1.640202.Test.plate.1.A11'],
[Well(3601), '1.SKB1.640202.Test.plate.1.A12']],
'1.SKB2.640194': [[Well(3079), '1.SKB2.640194.Test.plate.1.B1'],
[Well(3127), '1.SKB2.640194.Test.plate.1.B2'],
[Well(3175), '1.SKB2.640194.Test.plate.1.B3'],
[Well(3223), '1.SKB2.640194.Test.plate.1.B4'],
[Well(3271), '1.SKB2.640194.Test.plate.1.B5'],
[Well(3319), '1.SKB2.640194.Test.plate.1.B6'],
[Well(3367), '1.SKB2.640194.Test.plate.1.B7'],
[Well(3415), '1.SKB2.640194.Test.plate.1.B8'],
[Well(3463), '1.SKB2.640194.Test.plate.1.B9'],
[Well(3511), '1.SKB2.640194.Test.plate.1.B10'],
[Well(3559), '1.SKB2.640194.Test.plate.1.B11'],
[Well(3607), '1.SKB2.640194.Test.plate.1.B12']],
'1.SKB3.640195': [[Well(3085), '1.SKB3.640195.Test.plate.1.C1'],
[Well(3133), '1.SKB3.640195.Test.plate.1.C2'],
[Well(3181), '1.SKB3.640195.Test.plate.1.C3'],
[Well(3229), '1.SKB3.640195.Test.plate.1.C4'],
[Well(3277), '1.SKB3.640195.Test.plate.1.C5'],
[Well(3325), '1.SKB3.640195.Test.plate.1.C6'],
[Well(3373), '1.SKB3.640195.Test.plate.1.C7'],
[Well(3421), '1.SKB3.640195.Test.plate.1.C8'],
[Well(3469), '1.SKB3.640195.Test.plate.1.C9'],
[Well(3517), '1.SKB3.640195.Test.plate.1.C10'],
[Well(3565), '1.SKB3.640195.Test.plate.1.C11'],
[Well(3613), '1.SKB3.640195.Test.plate.1.C12']],
'1.SKB4.640189': [[Well(3091), '1.SKB4.640189.Test.plate.1.D1'],
[Well(3139), '1.SKB4.640189.Test.plate.1.D2'],
[Well(3187), '1.SKB4.640189.Test.plate.1.D3'],
[Well(3235), '1.SKB4.640189.Test.plate.1.D4'],
[Well(3283), '1.SKB4.640189.Test.plate.1.D5'],
[Well(3331), '1.SKB4.640189.Test.plate.1.D6'],
[Well(3379), '1.SKB4.640189.Test.plate.1.D7'],
[Well(3427), '1.SKB4.640189.Test.plate.1.D8'],
[Well(3475), '1.SKB4.640189.Test.plate.1.D9'],
[Well(3523), '1.SKB4.640189.Test.plate.1.D10'],
[Well(3571), '1.SKB4.640189.Test.plate.1.D11'],
[Well(3619), '1.SKB4.640189.Test.plate.1.D12']],
'1.SKB5.640181': [[Well(3097), '1.SKB5.640181.Test.plate.1.E1'],
[Well(3145), '1.SKB5.640181.Test.plate.1.E2'],
[Well(3193), '1.SKB5.640181.Test.plate.1.E3'],
[Well(3241), '1.SKB5.640181.Test.plate.1.E4'],
[Well(3289), '1.SKB5.640181.Test.plate.1.E5'],
[Well(3337), '1.SKB5.640181.Test.plate.1.E6'],
[Well(3385), '1.SKB5.640181.Test.plate.1.E7'],
[Well(3433), '1.SKB5.640181.Test.plate.1.E8'],
[Well(3481), '1.SKB5.640181.Test.plate.1.E9'],
[Well(3529), '1.SKB5.640181.Test.plate.1.E10'],
[Well(3577), '1.SKB5.640181.Test.plate.1.E11'],
[Well(3625), '1.SKB5.640181.Test.plate.1.E12']],
'1.SKB6.640176': [[Well(3103), '1.SKB6.640176.Test.plate.1.F1'],
[Well(3151), '1.SKB6.640176.Test.plate.1.F2'],
[Well(3199), '1.SKB6.640176.Test.plate.1.F3'],
[Well(3247), '1.SKB6.640176.Test.plate.1.F4'],
[Well(3295), '1.SKB6.640176.Test.plate.1.F5'],
[Well(3343), '1.SKB6.640176.Test.plate.1.F6'],
[Well(3391), '1.SKB6.640176.Test.plate.1.F7'],
[Well(3439), '1.SKB6.640176.Test.plate.1.F8'],
[Well(3487), '1.SKB6.640176.Test.plate.1.F9'],
[Well(3535), '1.SKB6.640176.Test.plate.1.F10'],
[Well(3583), '1.SKB6.640176.Test.plate.1.F11']]
}
self.assertEqual(tester.duplicates, exp)
self.assertEqual(tester.unknown_samples, [])
exp = tester.get_well(1, 1)
exp.composition.update('Unknown')
self.assertEqual(tester.unknown_samples, [exp])
exp.composition.update('1.SKB1.640202')
# test that the quantification_processes attribute correctly
# orders multiple processes in order from oldest to newest
tester2 = Plate(26)
self.assertEqual(len(tester2.quantification_processes), 2)
# we are going to test the dates as string because in the database we
# have the full date (including seconds)
obs_date = str(tester2.quantification_processes[0].date)
self.assertEqual(obs_date, "2017-10-25 19:10:25")
obs_date = str(tester2.quantification_processes[1].date)
self.assertEqual(obs_date, "2017-10-26 03:10:25")
def create_quantification_process(user, plate):
plate_config = plate.plate_configuration
concentrations = np.around(
np.random.rand(plate_config.num_rows, plate_config.num_columns), 6)
quant_process = QuantificationProcess.create(user, plate, concentrations)
return quant_process