def sample(batch_id):
NCV_db = NCV.query.filter(NCV.batch_id == batch_id)
sample_db = Sample.query.filter(Sample.batch_id == batch_id)
batch = Batch.query.filter(Batch.batch_id == batch_id).first()
DC = DataClasifyer()
DC.handle_NCV(NCV_db)
DC.get_QC_warnings(sample_db)
DC.get_manually_classified(sample_db)
PP = PlottPage(batch_id)
PP.make_NCV_stat()
PP.make_chrom_abn()
PP.make_cov_plot_data()
return render_template('batch_page.html',
NCV_samples = NCV.query.filter(NCV.batch_id == batch_id),
batch_name = batch.batch_name,
man_class = DC.man_class,
NCV_stat = PP.NCV_stat,
NCV_sex = DC.NCV_sex,
seq_date = batch.date,
nr_validation_samps = PP.nr_validation_samps,
samp_range = range(len(PP.NCV_stat['NCV_X']['NCV_cases'])),
tris_chrom_abn = PP.tris_chrom_abn,
sex_chrom_abn = PP.sex_chrom_abn,
abn_status_list = ['Verified','False Positive', 'Probable', 'Suspected'],
many_colors = PP.many_colors,
sex_abn_colors = PP.sex_abn_colors,
sex_tresholds = DC.sex_tresholds,
tris_thresholds = DC.tris_thresholds,
seq_warnings = DC.QC_warnings,
warnings = DC.NCV_classified,
NCV_rounded = DC.NCV_data,
samp_cov_db = PP.coverage_plot,
sample_ids = ','.join(sample.sample_ID for sample in NCV_db))
def sample_page( sample_id):
sample = Sample.query.filter_by(sample_ID = sample_id).first()
batch_id = sample.batch_id
batch = Batch.query.filter_by(batch_id = batch_id).first()
NCV_db = NCV.query.filter(NCV.batch_id == batch_id)
DC = DataClasifyer()
DC.handle_NCV(NCV_db)
NCV_dat = NCV.query.filter_by(sample_ID = sample_id).first()
chrom_abnorm = ['T13','T18', 'T21', 'X0', 'XXX','XXY','XYY']
db_entries = {c:sample.__dict__['status_'+c].replace('\r\n', '').strip() for c in chrom_abnorm }
db_entries_change = {c:sample.__dict__['status_change_'+c] for c in chrom_abnorm}
db_entries_comments = {c : sample.__dict__['comment_'+c] for c in chrom_abnorm}
PP = PlottPage(batch_id)
PP.make_NCV_stat()
PP.make_chrom_abn()
sample_state_dict = PP.sample_state_dict
for state in sample_state_dict:
sample_state_dict[state]['T_13'] = Sample.query.filter_by(status_T13 = state)
sample_state_dict[state]['T_18'] = Sample.query.filter_by(status_T18 = state)
sample_state_dict[state]['T_21'] = Sample.query.filter_by(status_T21 = state)
return render_template('sample_page.html',
NCV_dat = NCV_dat,
tris_abn = PP.tris_abn,
sex_chrom_abn = PP.sex_chrom_abn,
abn_status_list = ['Verified','False Positive', 'Probable', 'Suspected'],
sex_abn_colors = PP.sex_abn_colors,
sample = sample,
NCV_db = NCV.query.filter_by(sample_ID = sample_id).first(),
batch_id = batch_id,
batch_name = batch.batch_name,
batch = batch,
nr_validation_samps = PP.nr_validation_samps,
sample_id = sample_id,
chrom_abnorm = chrom_abnorm,
db_entries = db_entries,
db_entries_comments = db_entries_comments,
db_entries_change = db_entries_change,
NCV_stat = PP.NCV_stat,
NCV_131821 = ['NCV_13', 'NCV_18', 'NCV_21'],
state_dict = sample_state_dict,
sex_tresholds = DC.sex_tresholds,
tris_thresholds = DC.tris_thresholds,
NCV_sex = DC.NCV_sex[sample_id],
NCV_warn = DC.NCV_classified[sample_id])
def sample_page( sample_id):
sample = Sample.query.filter_by(sample_ID = sample_id).first()
batch_id = sample.batch_id
batch = Batch.query.filter_by(batch_id = batch_id).first()
NCV_db = NCV.query.filter(NCV.batch_id == batch_id)
DC = DataClasifyer(NCV_db)
DC.handle_NCV()
DC.make_sex_tresholds(BDF.NCV_passed_X)
NCV_dat = NCV.query.filter_by(sample_ID = sample_id).first()
chrom_abnorm = ['T13','T18', 'T21', 'X0', 'XXX','XXY','XYY']
db_entries = {c:sample.__dict__['status_'+c].replace('\r\n', '').strip() for c in chrom_abnorm }
db_entries_change = {c:sample.__dict__['status_change_'+c] for c in chrom_abnorm}
PP = PlottPage(batch_id, BDF)
PP.make_NCV_stat()
PP.make_chrom_abn()
return render_template('sample_page.html',
## Header & Info Box
NCV_dat = NCV_dat,
sample = sample,
batch_id = batch_id,
batch_name = batch.batch_name,
batch = batch,
NCV_sex = DC.NCV_sex[sample_id],
NCV_warn = DC.NCV_classified[sample_id],
## Comment
NCV_db = NCV.query.filter_by(sample_ID = sample_id).first(),
## NCV Table
sample_id = sample_id,
chrom_abnorm = chrom_abnorm,
db_entries = db_entries,
db_entries_change = db_entries_change,
## Plots
tris_abn = PP.tris_abn,
sex_chrom_abn = PP.sex_chrom_abn,
case_size = PP.case_size,
abn_size = PP.abn_size,
abn_status_list = ['Other','False Positive','Suspected', 'Probable', 'Verified'],
ncv_abn_colors = PP.ncv_abn_colors,
NCV_stat = PP.NCV_stat,
NCV_131821 = ['NCV_13', 'NCV_18', 'NCV_21'],
sex_tresholds = DC.sex_tresholds,
tris_thresholds = DC.tris_thresholds,
tris_chrom_abn = PP.tris_chrom_abn)
def sample_page(sample_id):
sample = Sample.query.filter_by(sample_ID=sample_id).first()
batch_id = sample.batch_id
batch = Batch.query.filter_by(batch_id=batch_id).first()
NCV_db = NCV.query.filter(NCV.batch_id == batch_id)
DC = DataClasifyer()
DC.handle_NCV(NCV_db)
NCV_dat = NCV.query.filter_by(sample_ID=sample_id).first()
chrom_abnorm = ['T13', 'T18', 'T21', 'X0', 'XXX', 'XXY', 'XYY']
db_entries = {
c: sample.__dict__['status_' + c].replace('\r\n', '').strip()
for c in chrom_abnorm
}
db_entries_change = {
c: sample.__dict__['status_change_' + c]
for c in chrom_abnorm
}
db_entries_comments = {
c: sample.__dict__['comment_' + c]
for c in chrom_abnorm
}
PP = PlottPage(batch_id)
PP.make_NCV_stat()
PP.make_chrom_abn()
sample_state_dict = PP.sample_state_dict
for state in sample_state_dict:
sample_state_dict[state]['T_13'] = Sample.query.filter_by(
status_T13=state)
sample_state_dict[state]['T_18'] = Sample.query.filter_by(
status_T18=state)
sample_state_dict[state]['T_21'] = Sample.query.filter_by(
status_T21=state)
return render_template(
'sample_page.html',
NCV_dat=NCV_dat,
tris_abn=PP.tris_abn,
sex_chrom_abn=PP.sex_chrom_abn,
abn_status_list=[
'Verified', 'False Positive', 'Probable', 'Suspected'
],
sex_abn_colors=PP.sex_abn_colors,
sample=sample,
NCV_db=NCV.query.filter_by(sample_ID=sample_id).first(),
batch_id=batch_id,
batch_name=batch.batch_name,
batch=batch,
nr_validation_samps=PP.nr_validation_samps,
sample_id=sample_id,
chrom_abnorm=chrom_abnorm,
db_entries=db_entries,
db_entries_comments=db_entries_comments,
db_entries_change=db_entries_change,
NCV_stat=PP.NCV_stat,
NCV_131821=['NCV_13', 'NCV_18', 'NCV_21'],
state_dict=sample_state_dict,
sex_tresholds=DC.sex_tresholds,
tris_thresholds=DC.tris_thresholds,
NCV_sex=DC.NCV_sex[sample_id],
NCV_warn=DC.NCV_classified[sample_id])
def sample(batch_id):
NCV_db = NCV.query.filter(NCV.batch_id == batch_id)
sample_db = Sample.query.filter(Sample.batch_id == batch_id)
batch = Batch.query.filter(Batch.batch_id == batch_id).first()
DC = DataClasifyer(NCV_db)
DC.handle_NCV()
DC.make_sex_tresholds(BDF.NCV_passed_X)
DC.get_QC_warnings(sample_db)
DC.get_manually_classified(sample_db)
PP = PlottPage(batch_id, BDF)
PP.make_NCV_stat()
PP.make_chrom_abn()
PP.make_cov_plot_data()
return render_template('batch_page.html',
## Header
batch_name = batch.batch_name,
seq_date = batch.date,
## Warnings Table
seq_warnings = DC.QC_warnings,
## NCV Table
NCV_samples = NCV.query.filter(NCV.batch_id == batch_id),
man_class = DC.man_class_merged,
NCV_sex = DC.NCV_sex,
warnings = DC.NCV_classified,
NCV_rounded = DC.NCV_data,
## Plotts
NCV_stat = PP.NCV_stat,
case_size = PP.case_size,
abn_size = PP.abn_size,
samp_range = range(len(PP.NCV_stat['NCV_X']['NCV_cases'])),
tris_chrom_abn = PP.tris_chrom_abn,
sex_chrom_abn = PP.sex_chrom_abn,
abn_status_list = ['Other','False Positive','Suspected', 'Probable', 'Verified'],
cov_colors = PP.cov_colors,
many_colors = PP.many_colors,
ncv_abn_colors = PP.ncv_abn_colors,
sex_tresholds = DC.sex_tresholds,
tris_thresholds = DC.tris_thresholds,
## Coverage
bool_warns = filter(None, DC.NCV_classified.values()),
samp_cov_db = PP.coverage_plot,
## Buttons
batch_id = batch_id,
sample_ids = ','.join(sample.sample_ID for sample in NCV_db))
def sample(batch_id):
NCV_db = NCV.query.filter(NCV.batch_id == batch_id)
sample_db = Sample.query.filter(Sample.batch_id == batch_id)
batch = Batch.query.filter(Batch.batch_id == batch_id).first()
DC = DataClasifyer()
DC.handle_NCV(NCV_db)
DC.get_QC_warnings(sample_db)
DC.get_manually_classified(sample_db)
PP = PlottPage(batch_id)
PP.make_NCV_stat()
PP.make_chrom_abn()
PP.make_cov_plot_data()
return render_template(
'batch_page.html',
NCV_samples=NCV.query.filter(NCV.batch_id == batch_id),
batch_name=batch.batch_name,
man_class=DC.man_class,
NCV_stat=PP.NCV_stat,
NCV_sex=DC.NCV_sex,
seq_date=batch.date,
nr_validation_samps=PP.nr_validation_samps,
samp_range=range(len(PP.NCV_stat['NCV_X']['NCV_cases'])),
tris_chrom_abn=PP.tris_chrom_abn,
sex_chrom_abn=PP.sex_chrom_abn,
abn_status_list=[
'Verified', 'False Positive', 'Probable', 'Suspected'
],
many_colors=PP.many_colors,
sex_abn_colors=PP.sex_abn_colors,
sex_tresholds=DC.sex_tresholds,
tris_thresholds=DC.tris_thresholds,
seq_warnings=DC.QC_warnings,
warnings=DC.NCV_classified,
NCV_rounded=DC.NCV_data,
samp_cov_db=PP.coverage_plot,
sample_ids=','.join(sample.sample_ID for sample in NCV_db))
