def testRoundtripWithBeadCalibration(self):
self.cwd = os.path.dirname(os.path.abspath(__file__))
self.ex = flow.ImportOp(conditions={
'Dox': 'float'
},
tubes=[
flow.Tube(file=self.cwd +
'/data/tasbe/rby.fcs',
conditions={'Dox': 1.0})
]).apply()
op = flow.BeadCalibrationOp(
units={"PE-Tx-Red-YG-A": "MEPTR"},
beads_file=self.cwd + '/data/tasbe/beads.fcs',
beads=flow.BeadCalibrationOp.BEADS[
"Spherotech RCP-30-5A Lot AA01-AA04, AB01, AB02, AC01, GAA01-R"]
)
op.estimate(self.ex)
ex2 = op.apply(self.ex)
flow.ExportFCS(path=self.directory, by=['Dox']).export(ex2)
tube1 = flow.Tube(file=self.directory + '/Dox_1.0.fcs',
conditions={"Dox": 1.0})
ex_rt = flow.ImportOp(conditions={
'Dox': 'float'
}, tubes=[tube1]).apply()
self.assertNotIn('voltage', ex_rt.metadata['PE-Tx-Red-YG-A'])
def testChooseChannels(self):
tube1 = flow.Tube(file = self.cwd + '/data/Plate01/RFP_Well_A3.fcs', conditions = {"Dox" : 10.0})
ex = flow.ImportOp(conditions = {"Dox" : "float"},
tubes = [tube1],
channels = {'Y2-A' : "Yellow"}).apply()
self.assertTrue(ex.channels == ["Yellow"])
with self.assertRaises(RuntimeError):
flow.ImportOp(conditions = {"Dox" : "float"},
tubes = [tube1],
channels = {'Y2-B' : "Blue"}).apply()
def setUp(self):
import os
self.cwd = os.path.dirname(
os.path.abspath(__file__)) + "/data/Plate01/"
tube1 = flow.Tube(file=self.cwd + 'RFP_Well_A3.fcs', conditions={})
import_op = flow.ImportOp(conditions={}, tubes=[tube1])
self.ex = import_op.apply()
def testMetadata(self):
tube1 = flow.Tube(file = self.cwd + '/data/Plate01/RFP_Well_A3.fcs', conditions = {"Dox" : 10.0})
tube2 = flow.Tube(file= self.cwd + '/data/Plate01/CFP_Well_A4.fcs', conditions = {"Dox" : 10.0})
import_op = flow.ImportOp(conditions = {"Dox" : "float"},
tubes = [tube1, tube2])
with self.assertRaises(RuntimeError):
import_op.apply()
def setUp(self):
self.cwd = os.path.dirname(os.path.abspath(__file__))
self.ex = flow.ImportOp(conditions = {},
tubes = [flow.Tube(file = self.cwd + '/data/tasbe/mkate.fcs',
conditions = {})]).apply()
self.op = flow.HlogTransformOp(channels = ["FSC-A", "Pacific Blue-A"])
def setUp(self):
self.cwd = os.path.dirname(
os.path.abspath(__file__)) + "/data/Plate01/"
tube1 = flow.Tube(file=self.cwd + 'RFP_Well_A3.fcs',
conditions={"Dox": 10.0})
tube2 = flow.Tube(file=self.cwd + 'CFP_Well_A4.fcs',
conditions={"Dox": 1.0})
import_op = flow.ImportOp(conditions={"Dox": "float"},
tubes=[tube1, tube2])
ex = import_op.apply()
# this works so much better on transformed data
logicle = flow.LogicleTransformOp()
logicle.name = "Logicle transformation"
logicle.channels = ['V2-A', 'Y2-A', 'B1-A']
logicle.estimate(ex)
self.ex = logicle.apply(ex)
self.gate = flow.Range2DOp(name="Range2D",
xchannel="V2-A",
ychannel="Y2-A",
xlow=0.0,
xhigh=0.4,
ylow=0.4,
yhigh=0.8)
def setUp(self):
self.cwd = os.path.dirname(os.path.abspath(__file__)) + "/data/Plate01/"
tube1 = flow.Tube(file = self.cwd + 'RFP_Well_A3.fcs', conditions = {"Dox" : 10.0, "Well" : "A"})
tube2 = flow.Tube(file= self.cwd + 'CFP_Well_A4.fcs', conditions = {"Dox" : 1.0, "Well" : "B"})
import_op = flow.ImportOp(conditions = {"Dox" : "float", "Well" : "category"},
tubes = [tube1, tube2])
self.ex = import_op.apply()
def testRoundtrip(self):
flow.ExportFCS(path=self.directory, by=['Dox']).export(self.ex)
tube1 = flow.Tube(file=self.directory / 'Dox_10.0.fcs',
conditions={
"Dox": 10.0,
"Well": "A"
})
tube2 = flow.Tube(file=self.directory / 'Dox_1.0.fcs',
conditions={
"Dox": 1.0,
"Well": "B"
})
ex_rt = flow.ImportOp(conditions={
"Dox": "float",
"Well": "category"
},
tubes=[tube1, tube2]).apply()
self.assertTrue((self.ex.data == ex_rt.data).all().all())
for channel in self.ex.channels:
self.assertEqual(self.ex.metadata[channel]['range'],
ex_rt.metadata[channel]['range'])
def setUp(self):
self.cwd = os.path.dirname(os.path.abspath(__file__))
self.ex = flow.ImportOp(conditions={},
tubes=[
flow.Tube(file=self.cwd +
'/data/tasbe/mkate.fcs',
conditions={})
]).apply()
def testImport(self):
tube1 = flow.Tube(file=self.cwd + '/data/Plate01/RFP_Well_A3.fcs',
conditions={"Dox": 10.0})
tube2 = flow.Tube(file=self.cwd + '/data/Plate01/CFP_Well_A4.fcs',
conditions={"Dox": 1.0})
import_op = flow.ImportOp(conditions={"Dox": "float"},
tubes=[tube1, tube2])
import_op.apply()
def testCategories(self):
tube1 = flow.Tube(file=self.cwd + '/data/Plate01/RFP_Well_A3.fcs',
conditions={"Dox": "one"})
tube2 = flow.Tube(file=self.cwd + '/data/Plate01/CFP_Well_A4.fcs',
conditions={"Dox": "two"})
import_op = flow.ImportOp(conditions={"Dox": "category"},
tubes=[tube1, tube2])
import_op.apply()
def load_experimental_data(self,
keyfile,
datadir="",
inducer="Inducer Level"):
"""
We detect experimental file by the control column being empty
"""
#Set indices of keyfile columns
file_col = 0
part_col = 1
control_col = 2
condition_col = 3
time_col = 4
regulation_col = 5
all_experiments = [] #experiments will be added to this list
#Keep track of replicates with 2-level dict with default count of 0.
# Dict[media_conditions][time] = 0
replicates_dict = defaultdict(lambda: defaultdict(lambda: 0))
num_rows = keyfile.shape[0]
for row in range(num_rows):
if keyfile[row][control_col] == "":
filename = keyfile[row][file_col]
experiment_time = keyfile[row][time_col]
#Parse Media conditions which are numbers. Ignore units like nM or ul/M
condition = keyfile[row][condition_col]
condition = re.search(r'[\d|.]{1,}', condition).group()
#Check for replicate experiments
replicates_dict[str(condition)][str(experiment_time)] += 1
rep = replicates_dict[str(condition)][str(experiment_time)]
#Set the metadata for the experiment
#print("Loading replicate: %i" % rep)
tube = flow.Tube(file=os.path.join(datadir, filename),
conditions={
inducer: float(condition),
'Replicate': int(rep)
})
all_experiments.append(tube)
##Load data
### Combine files into single dataframe and import data
import_op = flow.ImportOp(conditions={
'Dox': "float",
'Replicate': "int"
},
tubes=all_experiments,
coarse=False,
coarse_events=10000)
cytometry_experiments = import_op.apply()
print("Successfully loaded %i experimental files." %
len(all_experiments))
return cytometry_experiments
def setUp(self):
from cytoflow import Tube
self.cwd = os.path.dirname(os.path.abspath(__file__)) + "/data/tasbe/"
tube = Tube(file = self.cwd + "rby.fcs")
self.ex = flow.ImportOp(tubes = [tube])
def setUp(self):
import os
self.cwd = os.path.dirname(os.path.abspath(__file__))
self.ex = flow.ImportOp(conditions = {},
tubes = [flow.Tube(file = self.cwd + '/data/tasbe/rby.fcs',
conditions = {})]).apply()
self.op = flow.BleedthroughPiecewiseOp(
controls = {"FITC-A" : self.cwd + '/data/tasbe/eyfp.fcs',
"PE-Tx-Red-YG-A" : self.cwd + '/data/tasbe/mkate.fcs'})
def createExperiment(self, fcsfile, condition):
"""
Data processing for an individual FCS file, allowing for data transformations to be applied at this time.
Reads the data through the CytoFlow API,
Converts the data into a numPy dataset, applies transformations as requested through the Flow Utils API,
and then converts it back into a pandas Dataframe, adding it to the SQL database file in the process.
This step can be optimized in the future to reduce memory and increase the speed of transformations.
Parameters
----------
fcsfile : str
Name of the FCS file to process
condition : int
Value of a classificiation column for future potential machine learning implementations.
"""
tube1 = flow.Tube(file=os.path.join(self.file_loc, fcsfile),
conditions={'NN': condition})
import_op = flow.ImportOp(conditions={'NN': 'float'}, tubes=[tube1])
exp = import_op.apply()
allDat = exp.data
def convertToDF(nparr, columns):
data = pd.DataFrame(columns=columns)
for i in range(len(nparr)):
data.loc[i] = list(nparr[i])
return data
def hyperlog(df):
nparr = df.values
mod_events = fu.transforms.hyperlog(nparr,
np.arange(0, len(df.columns)))
mod_pd = convertToDF(mod_events, df.columns)
return mod_pd
def logicle(df):
nparr = df.values
mod_events = fu.transforms.logicle(nparr,
np.arange(0, len(df.columns)))
mod_pd = convertToDF(mod_events, df.columns)
return mod_pd
if (self.transformation == "hyperlog"):
allDat = hyperlog(allDat)
elif (self.transformation == "logicle"):
allDat = logicle(allDat)
#Export to SQLDB
try:
allDat.to_sql(fcsfile, self.conn)
except Error as e:
print(e)
return allDat
def main():
parser = argparse.ArgumentParser()
parser.add_argument("fcs_file", help="FCS file to analyze")
args = parser.parse_args()
op = flow.ImportOp(tubes=[flow.Tube(file=args.fcs_file, conditions={})])
ex = op.apply()
for c in ex.channels:
m = ex.metadata[c]
if "voltage" in m:
print "{0}\t{1}".format(c, m["voltage"])
def setUp(self):
import os
self.cwd = os.path.dirname(os.path.abspath(__file__))
self.ex = flow.ImportOp(conditions = {},
tubes = [flow.Tube(file = self.cwd + '/data/tasbe/blank.fcs',
conditions = {})]).apply()
self.op = flow.AutofluorescenceOp(
blank_file = self.cwd + '/data/tasbe/blank.fcs',
channels = ["Pacific Blue-A", "FITC-A", "PE-Tx-Red-YG-A"])
self.op.estimate(self.ex)
def setUp(self):
self.cwd = os.path.dirname(os.path.abspath(__file__)) + "/data/Plate01/"
tube1 = flow.Tube(file = self.cwd + 'RFP_Well_A3.fcs', conditions = {"Dox" : 10.0})
tube2 = flow.Tube(file= self.cwd + 'CFP_Well_A4.fcs', conditions = {"Dox" : 1.0})
import_op = flow.ImportOp(conditions = {"Dox" : "float"},
tubes = [tube1, tube2])
self.ex = import_op.apply()
self.gate = flow.ThresholdOp(name = "Threshold",
channel = "Y2-A",
threshold = 500)
def testApply(self):
ex = flow.ImportOp(tubes = [flow.Tube(file = self.cwd + '/data/tasbe/blank.fcs')]).apply()
ex2 = self.op.apply(ex)
import numpy as np
self.assertAlmostEqual(np.median(ex2["FITC-A"]), 0.0)
self.assertAlmostEqual(np.median(ex2["Pacific Blue-A"]), 0.0)
self.assertAlmostEqual(np.median(ex2["PE-Tx-Red-YG-A"]), 0.0)
with self.assertRaises(ValueError):
self.assertFalse((self.ex.data == ex2.data).all().all())
def setUp(self):
import os
self.cwd = os.path.dirname(os.path.abspath(__file__))
self.ex = flow.ImportOp(conditions = {},
tubes = [flow.Tube(file = self.cwd + '/data/tasbe/rby.fcs',
conditions = {})]).apply()
self.op = flow.BeadCalibrationOp(
units = {"PE-Tx-Red-YG-A" : "MEPTR"},
beads_file = self.cwd + '/data/tasbe/beads.fcs',
beads = flow.BeadCalibrationOp.BEADS["Spherotech RCP-30-5A Lot AA01-AA04, AB01, AB02, AC01, GAA01-R"])
self.op.estimate(self.ex)
def setUp(self):
self.cwd = os.path.dirname(os.path.abspath(__file__)) + "/data/Plate01/"
tube1 = flow.Tube(file = self.cwd + 'RFP_Well_A3.fcs', conditions = {"Dox" : 10.0})
tube2 = flow.Tube(file= self.cwd + 'CFP_Well_A4.fcs', conditions = {"Dox" : 1.0})
import_op = flow.ImportOp(conditions = {"Dox" : "float"},
tubes = [tube1, tube2])
self.ex = import_op.apply()
self.op = flow.FlowPeaksOp(name = "FP",
channels = ["V2-A", "Y2-A"],
scale = {"V2-A" : "logicle",
"Y2-A" : "logicle"},
h0 = 0.5)
def setUp(self):
import os
self.cwd = os.path.dirname(os.path.abspath(__file__))
self.ex = flow.ImportOp(conditions = {'Dox' : 'int'},
tubes = [flow.Tube(file = self.cwd + '/data/tasbe/rby.fcs',
conditions = {'Dox' : 10})]).apply()
self.op = flow.BleedthroughLinearOp(
controls = {"FITC-A" : self.cwd + '/data/tasbe/eyfp.fcs',
"PE-Tx-Red-YG-A" : self.cwd + '/data/tasbe/mkate.fcs',
"Pacific Blue-A" : self.cwd + '/data/tasbe/ebfp.fcs'})
self.op.estimate(self.ex)
def setUp(self):
self.cwd = os.path.dirname(os.path.abspath(__file__)) + "/data/Plate01/"
tube1 = flow.Tube(file = self.cwd + 'RFP_Well_A3.fcs', conditions = {"Dox" : 10.0})
tube2 = flow.Tube(file= self.cwd + 'CFP_Well_A4.fcs', conditions = {"Dox" : 1.0})
import_op = flow.ImportOp(conditions = {"Dox" : "float"},
tubes = [tube1, tube2])
self.ex = import_op.apply()
self.gate = flow.Range2DOp(name = "Range2D",
xchannel = "V2-A",
ychannel = "Y2-A",
xlow = -200, xhigh = 800,
ylow = 800, yhigh = 30000)
def testRoundtrip(self):
flow.ExportFCS(path=self.directory, by=['Dox']).export(self.ex)
tube1 = flow.Tube(file=self.directory + '/Dox_10.0.fcs',
conditions={"Dox": 10.0})
tube2 = flow.Tube(file=self.directory + '/Dox_1.0.fcs',
conditions={"Dox": 1.0})
ex_rt = flow.ImportOp(conditions={
"Dox": "float"
},
tubes=[tube1, tube2]).apply()
self.assertTrue((self.ex.data == ex_rt.data).all().all())
def setUp(self):
self.cwd = os.path.dirname(os.path.abspath(__file__)) + "/data/Plate01/"
tube1 = flow.Tube(file = self.cwd + 'RFP_Well_A3.fcs', conditions = {"Dox" : 10.0})
tube2 = flow.Tube(file= self.cwd + 'CFP_Well_A4.fcs', conditions = {"Dox" : 1.0})
import_op = flow.ImportOp(conditions = {"Dox" : "float"},
tubes = [tube1, tube2])
self.ex = import_op.apply()
self.gate = flow.GaussianMixtureOp(name = "Gauss",
channels = ["Y2-A"],
sigma = 0.5,
num_components = 2,
scale = {"Y2-A" : "logicle"},
posteriors = True)
def setUp(self):
import os
self.cwd = os.path.dirname(os.path.abspath(__file__))
self.ex = flow.ImportOp(conditions = {'Dox' : 'int'},
tubes = [flow.Tube(file = self.cwd + '/data/tasbe/mkate.fcs',
conditions = {'Dox' : 3})]).apply()
self.op = flow.ColorTranslationOp(
controls = {("PE-Tx-Red-YG-A", "FITC-A") :
self.cwd + '/data/tasbe/rby.fcs',
("Pacific Blue-A", "FITC-A") :
self.cwd + '/data/tasbe/rby.fcs'},
mixture_model = True)
self.op.estimate(self.ex)
def setUp(self):
self.cwd = os.path.dirname(os.path.abspath(__file__)) + "/data/Plate01/"
tube1 = flow.Tube(file = self.cwd + 'RFP_Well_A3.fcs', conditions = {"Dox" : 10.0})
tube2 = flow.Tube(file= self.cwd + 'CFP_Well_A4.fcs', conditions = {"Dox" : 1.0})
import_op = flow.ImportOp(conditions = {"Dox" : "float"},
tubes = [tube1, tube2])
self.ex = import_op.apply()
self.op = flow.PCAOp(name = "PCA",
channels = ["V2-A", "V2-H", "Y2-A", "Y2-H"],
scale = {"V2-A" : "log",
"V2-H" : "log",
"Y2-A" : "log",
"Y2-H" : "log"},
num_components = 2)
def setUp(self):
self.cwd = os.path.dirname(
os.path.abspath(__file__)) + "/data/Plate01/"
tube1 = flow.Tube(file=self.cwd + 'RFP_Well_A3.fcs',
conditions={"Dox": 10.0})
tube2 = flow.Tube(file=self.cwd + 'CFP_Well_A4.fcs',
conditions={"Dox": 1.0})
import_op = flow.ImportOp(conditions={"Dox": "float"},
tubes=[tube1, tube2])
self.ex = import_op.apply()
self.gate = flow.DensityGateOp(name="D",
xchannel="V2-A",
ychannel="Y2-A",
xscale="logicle",
yscale="logicle",
keep=0.8)
def setUp(self):
self.cwd = os.path.dirname(os.path.abspath(__file__)) + "/data/Plate01/"
tube1 = flow.Tube(file = self.cwd + 'RFP_Well_A3.fcs', conditions = {"Dox" : 10.0})
tube2 = flow.Tube(file= self.cwd + 'CFP_Well_A4.fcs', conditions = {"Dox" : 1.0})
import_op = flow.ImportOp(conditions = {"Dox" : "float"},
tubes = [tube1, tube2])
self.ex = import_op.apply()
self.ex = flow.ThresholdOp(name = "T",
channel = "Y2-A",
threshold = 500).apply(self.ex)
self.ex = flow.ChannelStatisticOp(name = "ByDox",
by = ['Dox', 'T'],
channel = "Y2-A",
function = len).apply(self.ex)
def testManufacturers(self):
files = [
'Accuri - C6.fcs', 'Applied Biosystems - Attune.fcs',
'BD - FACS Aria II.fcs', 'Beckman Coulter - Cyan.fcs',
'Beckman Coulter - Cytomics FC500.LMD',
'Beckman Coulter - Gallios.LMD',
'Beckman Coulter - MoFlo Astrios - linear settings.fcs',
'Beckman Coulter - MoFlo Astrios - log settings.fcs',
'Beckman Coulter - MoFlo XDP.fcs', 'Cytek DxP10.fcs',
'Cytek xP5.fcs', 'iCyt - Eclipse.lmd', 'Millipore - Guava.fcs',
'Miltenyi Biotec - MACSQuant Analyzer.fcs', 'Partec - PAS.FCS',
'Stratedigm - S1400.fcs',
'System II listmode with extra info in bits D10-D15.LMD'
]
for file in files:
path = self.cwd + '/data/instruments/' + file
import_op = flow.ImportOp(tubes=[flow.Tube(file=path)])
import_op.apply()
