def run_m_script(m_file):
"""
Runs a matlab m file for SPM, determining automatically if it must be launched with SPM or SPM Standalone
If launch with spm standalone, the line 'spm_jobman('run', matlabbatch)' must be removed because unnecessary
Args:
m_file: (str) path to Matlab m file
Returns:
output_mat_file: (str) path to the SPM.mat file needed in SPM analysis
"""
import platform
from os import system
from os.path import abspath, basename, dirname, isfile, join
from nipype.interfaces.matlab import MatlabCommand, get_matlab_command
import clinica.pipelines.statistics_volume.statistics_volume_utils as utls
from clinica.utils.spm import spm_standalone_is_available
assert isinstance(m_file, str), "[Error] Argument must be a string"
if not isfile(m_file):
raise FileNotFoundError("[Error] File " + m_file + "does not exist")
assert m_file[-2:] == ".m", (
"[Error] " + m_file + " is not a Matlab file (extension must be .m)")
# Generate command line to run
if spm_standalone_is_available():
utls.delete_last_line(m_file)
# SPM standalone must be run directly from its root folder
if platform.system().lower().startswith("darwin"):
# Mac OS
cmdline = (
"cd $SPMSTANDALONE_HOME && ./run_spm12.sh $MCR_HOME batch " +
m_file)
elif platform.system().lower().startswith("linux"):
# Linux OS
cmdline = "$SPMSTANDALONE_HOME/run_spm12.sh $MCR_HOME batch " + m_file
else:
raise SystemError("Clinica only support Mac OS and Linux")
system(cmdline)
else:
MatlabCommand.set_default_matlab_cmd(get_matlab_command())
matlab = MatlabCommand()
if platform.system().lower().startswith("linux"):
matlab.inputs.args = "-nosoftwareopengl"
matlab.inputs.paths = dirname(m_file)
matlab.inputs.script = basename(m_file)[:-2]
matlab.inputs.single_comp_thread = False
matlab.inputs.logfile = abspath("./matlab_output.log")
matlab.run()
output_mat_file = abspath(
join(dirname(m_file), "..", "2_sample_t_test", "SPM.mat"))
if not isfile(output_mat_file):
raise RuntimeError("Output matrix " + output_mat_file +
" was not produced")
return output_mat_file
def run_matlab(caps_dir, output_dir, subjects_visits_tsv, pipeline_parameters):
"""
Wrap the call of SurfStat using clinicasurfstat.m Matlab script.
Args:
caps_dir (str): CAPS directory containing surface-based features
output_dir (str): Output directory that will contain outputs of clinicasurfstat.m
subjects_visits_tsv (str): TSV file containing the GLM information
pipeline_parameters (dict): parameters of StatisticsSurface pipeline
"""
import os
from nipype.interfaces.matlab import MatlabCommand, get_matlab_command
import clinica.pipelines as clinica_pipelines
from clinica.utils.check_dependency import check_environment_variable
from clinica.pipelines.statistics_surface.statistics_surface_utils import covariates_to_design_matrix, get_string_format_from_tsv
path_to_matlab_script = os.path.join(
os.path.dirname(clinica_pipelines.__path__[0]), 'lib',
'clinicasurfstat')
freesurfer_home = check_environment_variable('FREESURFER_HOME',
'FreeSurfer')
MatlabCommand.set_default_matlab_cmd(get_matlab_command())
matlab = MatlabCommand()
matlab.inputs.paths = path_to_matlab_script
matlab.inputs.script = """
clinicasurfstat('%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', %d, '%s', %.3f, '%s', %.3f, '%s', %.3f);
""" % (os.path.join(caps_dir, 'subjects'), output_dir, subjects_visits_tsv,
covariates_to_design_matrix(pipeline_parameters['contrast'],
pipeline_parameters['covariates']),
pipeline_parameters['contrast'],
get_string_format_from_tsv(subjects_visits_tsv),
pipeline_parameters['glm_type'], pipeline_parameters['group_label'],
freesurfer_home, pipeline_parameters['custom_file'],
pipeline_parameters['measure_label'], 'sizeoffwhm',
pipeline_parameters['full_width_at_half_maximum'],
'thresholduncorrectedpvalue', 0.001, 'thresholdcorrectedpvalue',
0.05, 'clusterthreshold', pipeline_parameters['cluster_threshold'])
# This will create a file: pyscript.m , the pyscript.m is the default name
matlab.inputs.mfile = True
# This will stop running with single thread
matlab.inputs.single_comp_thread = False
matlab.inputs.logfile = 'group-' + pipeline_parameters[
'group_label'] + '_matlab.log'
# cprint("Matlab logfile is located at the following path: %s" % matlab.inputs.logfile)
# cprint("Matlab script command = %s" % matlab.inputs.script)
# cprint("MatlabCommand inputs flag: single_comp_thread = %s" % matlab.inputs.single_comp_thread)
# cprint("MatlabCommand choose which matlab to use(matlab_cmd): %s" % get_matlab_command())
matlab.run()
return output_dir
def run_m_script(m_file):
"""
Runs a matlab m file for SPM, determining automatically if it must be launched with SPM or SPM Standalone
If launch with spm standalone, the line 'spm_jobman('run', matlabbatch)' must be removed because unnecessary
Args:
m_file: (str) path to Matlab m file
Returns:
output_mat_file: (str) path to the SPM.mat file needed in SPM analysis
"""
from os.path import isfile, dirname, basename, abspath, join
from os import system
from clinica.utils.spm import use_spm_standalone
import clinica.pipelines.statistics_volume.statistics_volume_utils as utls
from nipype.interfaces.matlab import MatlabCommand, get_matlab_command
import platform
assert isinstance(m_file, str), '[Error] Argument must be a string'
if not isfile(m_file):
raise FileNotFoundError('[Error] File ' + m_file + 'does not exist')
assert m_file[-2:] == '.m', '[Error] ' + m_file + ' is not a Matlab file (extension must be .m)'
# Generate command line to run
if use_spm_standalone():
utls.delete_last_line(m_file)
# SPM standalone must be run directly from its root folder
if platform.system().lower().startswith('darwin'):
# Mac OS
cmdline = 'cd $SPMSTANDALONE_HOME && ./run_spm12.sh $MCR_HOME batch ' + m_file
elif platform.system().lower().startswith('linux'):
# Linux OS
cmdline = '$SPMSTANDALONE_HOME/run_spm12.sh $MCR_HOME batch ' + m_file
else:
raise SystemError('Clinica only support Mac OS and Linux')
system(cmdline)
else:
MatlabCommand.set_default_matlab_cmd(get_matlab_command())
matlab = MatlabCommand()
if platform.system().lower().startswith('linux'):
matlab.inputs.args = '-nosoftwareopengl'
matlab.inputs.paths = dirname(m_file)
matlab.inputs.script = basename(m_file)[:-2]
matlab.inputs.single_comp_thread = False
matlab.inputs.logfile = abspath('./matlab_output.log')
matlab.run()
output_mat_file = abspath(join(dirname(m_file), '..', '2_sample_t_test', 'SPM.mat'))
if not isfile(output_mat_file):
raise RuntimeError('Output matrix ' + output_mat_file + ' was not produced')
return output_mat_file
import matplotlib.pyplot as plt
import numpy as np
from nipype.pipeline.engine import Workflow, Node, MapNode
from nipype.interfaces.io import SelectFiles, DataSink
from os.path import join as opj
from nipype.interfaces.utility import IdentityInterface, Function, Select, Merge
import nipype.interfaces.spm as spm
import nipype.interfaces.ants as ants
import nipype.interfaces.afni as afni
import nipype.interfaces.fsl as fsl
from nipype import config
cfg = dict(execution={'remove_unnecessary_outputs': False})
config.update_config(cfg)
MatlabCommand.set_default_paths('/Users/amr/Downloads/spm12')
MatlabCommand.set_default_matlab_cmd("matlab -nodesktop -nosplash")
# import nipype.interfaces.matlab as mlab
# mlab.MatlabCommand.set_default_matlab_cmd("matlab -nodesktop -nosplash")
# mlab.MatlabCommand.set_default_paths('/home/amr/Documents/MATLAB/toolbox/spm8')
# ========================================================================================================
# In[2]:
experiment_dir = '/media/amr/Amr_4TB/Work/stimulation'
subject_list = [
'005', '007', '008', '010', '013', '024', '025', '026', '027', '028',
'038', '040', '041', '042', '051', '052', '053', '054', '055', '059',
'060', '061', '079', '081'
]
from nipype.interfaces.freesurfer import Resample, Binarize, MRIConvert
from nipype.algorithms.confounds import CompCor
from nipype.interfaces.afni.preprocess import Bandpass
from nipype.interfaces.afni.utils import AFNItoNIFTI
from nipype.interfaces.ants import ApplyTransforms, Registration
from nipype.algorithms.misc import Gunzip
from pandas import DataFrame, Series
#set output file type for FSL to NIFTI
from nipype.interfaces.fsl.preprocess import FSLCommand
FSLCommand.set_default_output_type('NIFTI')
# MATLAB setup - Specify path to current SPM and the MATLAB's default mode
from nipype.interfaces.matlab import MatlabCommand
MatlabCommand.set_default_paths('~/spm12')
MatlabCommand.set_default_matlab_cmd("matlab -nodesktop -nosplash")
# Set study variables
setup='sherlock'
sample='6mo' #6mo or newborn
sequence='spiral'#spiral or mux6
if setup=='sherlock':
studyhome = '/oak/stanford/groups/iang/BABIES_data/BABIES_rest'
raw_data = studyhome + '/subjDir/all'
output_dir = studyhome + '/processed/preproc'
workflow_dir = studyhome + '/workflows'
elif setup=='Cat':
studyhome = '/Users/catcamacho/Box/SNAP/BABIES/BABIES_rest'
raw_data = studyhome + '/rest_raw'
output_dir = studyhome + '/processed/preproc'
# ======================================================================
# define paths depending on the operating system (OS) platform:
project = 'highspeed'
# initialize empty paths:
path_root = None
sub_list = None
# path to the project root:
project_name = 'highspeed-glm'
path_root = os.getenv('PWD').split(project_name)[0] + project_name
if 'darwin' in sys.platform:
path_spm = '/Users/Shared/spm12'
path_matlab = '/Applications/MATLAB_R2017a.app/bin/matlab -nodesktop -nosplash'
# set paths for spm:
spm.SPMCommand.set_mlab_paths(paths=path_spm, matlab_cmd=path_matlab)
MatlabCommand.set_default_paths(path_spm)
MatlabCommand.set_default_matlab_cmd(path_matlab)
sub_list = ['sub-01']
elif 'linux' in sys.platform:
# path_matlab = '/home/mpib/wittkuhn/spm12.simg eval \$SPMMCRCMD'
# path_matlab = opj('/home', 'beegfs', 'wittkuhn', 'tools', 'spm', 'spm12.simg eval \$SPMMCRCMD')
singularity_cmd = 'singularity run -B /home/mpib/wittkuhn -B /mnt/beegfs/home/wittkuhn /home/mpib/wittkuhn/highspeed/highspeed-glm/tools/spm/spm12.simg'
singularity_spm = 'eval \$SPMMCRCMD'
path_matlab = ' '.join([singularity_cmd, singularity_spm])
spm.SPMCommand.set_mlab_paths(matlab_cmd=path_matlab, use_mcr=True)
# grab the list of subjects from the bids data set:
layout = BIDSLayout(opj(path_root, 'bids'))
# get all subject ids:
sub_list = sorted(layout.get_subjects())
# create a template to add the "sub-" prefix to the ids
sub_template = ['sub-'] * len(sub_list)
# add the prefix to all ids:
def runmatlab(output_dir, noddi_img, brain_mask, roi_mask, bval, bvec, prefix,
bStep, num_cores, path_to_matscript, noddi_toolbox_dir,
nifti_matlib_dir):
"""
The wrapper to call noddi matlab script.
Args:
output_dir:
noddi_img:
brain_mask:
roi_mask:
bval:
bvec:
prefix:
bStep:
num_cores:
Returns:
"""
from nipype.interfaces.matlab import MatlabCommand, get_matlab_command
from os.path import join
import sys
import os
# here, we check out the os, basically, clinica works for linux and MAC OS X.
if sys.platform.startswith('linux'):
print "###Note: your platform is linux, the default command line for Matlab(matlab_cmd) is matlab, but you can also export a variable MATLABCMD, which points to your matlab, in your .bashrc to set matlab_cmd, this can help you to choose which Matlab to run when you have more than one Matlab. "
elif sys.platform.startswith('darwin'):
try:
if 'MATLABCMD' not in os.environ:
raise RuntimeError(
"###Note: your platform is MAC OS X, the default command line for Matlab(matlab_cmd) is matlab, but it does not work on OS X, you mush export a variable MATLABCMD, which points to your matlab, in your .bashrc to set matlab_cmd. Note, Mac os x will always choose to use OpengGl hardware mode."
)
except Exception as e:
print(str(e))
exit(1)
else:
print "Clinica will not work on your platform "
MatlabCommand.set_default_matlab_cmd(
get_matlab_command()
) # this is to set the matlab_path(os.environ) in your bashrc file, to choose which version of matlab do you wanna use
# here, set_default_matlab_cmd is a @classmethod
matlab = MatlabCommand()
# add the dynamic traits
# openGL_trait = traits.Bool(True, argstr='-nosoftwareopengl', usedefault=True, desc='Switch on hardware openGL', nohash=True)
# matlab.input_spec.add_trait(matlab.input_spec(), 'nosoftwareopengl', openGL_trait() )
if sys.platform.startswith('linux'):
matlab.inputs.args = '-nosoftwareopengl' # Bug, for my laptop, it does not work, but the command line does have the flag -nosoftwareopengl, we should try on other computer's matlab to check if this flag works!
matlab.inputs.paths = path_to_matscript # CLINICA_HOME, this is the path to add into matlab, addpath
matlab.inputs.script = """
noddiprocessing('%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', %d');
""" % (
output_dir, noddi_img, brain_mask, roi_mask, bval, bvec, prefix, bStep,
noddi_toolbox_dir, nifti_matlib_dir, num_cores
) # here, we should define the inputs for the matlab function that you want to use
matlab.inputs.mfile = True # this will create a file: pyscript.m , the pyscript.m is the default name
matlab.inputs.single_comp_thread = False # this will stop runing with single thread
matlab.inputs.logfile = join(output_dir, prefix + "_matlab_output.log")
print "Matlab logfile is located in the folder: %s" % matlab.inputs.logfile
print "Matlab script command = %s" % matlab.inputs.script
print "MatlabCommand inputs flag: single_comp_thread = %s" % matlab.inputs.single_comp_thread
print "MatlabCommand choose which matlab to use(matlab_cmd): %s" % get_matlab_command(
)
if sys.platform.startswith('linux'):
print "MatlabCommand inputs flag: nosoftwareopengl = %s" % matlab.inputs.args
matlab.run()
# grab the output images
fit_icvf = os.path.join(output_dir, prefix + '_ficvf.nii')
fit_isovf = os.path.join(output_dir, prefix + '_fiso.nii')
fit_od = os.path.join(output_dir, prefix + '_odi.nii')
return fit_icvf, fit_isovf, fit_od
def runmatlab(input_directory,
output_directory,
subjects_visits_tsv,
design_matrix, contrast,
str_format,
glm_type,
group_label,
freesurfer_home,
surface_file,
path_to_matscript,
full_width_at_half_maximum,
threshold_uncorrected_pvalue,
threshold_corrected_pvalue,
cluster_threshold,
feature_label):
"""
a wrapper the matlab script of surfstat with nipype.
Args:
input_directory: surfstat_input_dir where containing all the subjects' output in CAPS directory
output_directory: output folder to contain the result in CAPS folder
subjects_visits_tsv: tsv file containing the glm information
design_matrix: str, the linear model that fits into the GLM, for example '1+group'.
contrast: string, the contrast matrix for GLM, if the factor you choose is categorized variable, clinica_surfstat will create two contrasts,
for example, contrast = 'Label', this will create contrastpos = Label.AD - Label.CN, contrastneg = Label.CN - Label.AD; if the fac-
tory that you choose is a continuous factor, clinica_surfstat will just create one contrast, for example, contrast = 'Age', but note,
the string name that you choose should be exactly the same with the columns names in your subjects_visits_tsv.
str_format:string, the str_format which uses to read your tsv file, the type of the string should corresponds exactly with the columns in the tsv file.
Defaut parameters, we set these parameters to be some default values, but you can also set it by yourself:
glm_type: based on the hypothesis, you should define one of the glm types, "group_comparison", "correlation"
group_label: current group name for this analysis
freesurfer_home: the environmental variable $FREESURFER_HOME
surface_file: Specify where to find the data surfaces file in the "CAPS/subject" directory, using specific keywords.
For instance, to catch for each subject the cortical thickness, the string used will be:
'@subject/@session/t1/freesurfer_cross_sectional/@subject_@session/surf/@[email protected]'
More information is available on the documentation page of the surfstat pipelines. The keywords @subject @ session @hemi @fwhm
represents the variable parts.
path_to_matscript: path to find the matlab script
full_width_at_half_maximum: fwhm for the surface smoothing, default is 20, integer.
threshold_uncorrected_pvalue: threshold to display the uncorrected Pvalue, float, default is 0.001.
threshold_corrected_pvalue: the threshold to display the corrected cluster, default is 0.05, float.
cluster_threshold: threshold to define a cluster in the process of cluster-wise correction, default is 0.001, float.
Returns:
"""
from nipype.interfaces.matlab import MatlabCommand, get_matlab_command
from os.path import join
import sys
from clinica.utils.stream import cprint
MatlabCommand.set_default_matlab_cmd(
get_matlab_command()) # this is to set the matlab_path(os.environ) in your bashrc file, to choose which version of matlab do you wanna use
# here, set_default_matlab_cmd is a @classmethod
matlab = MatlabCommand()
# add the dynamic traits
# openGL_trait = traits.Bool(True, argstr='-nosoftwareopengl', usedefault=True, desc='Switch on hardware openGL', nohash=True)
# matlab.input_spec.add_trait(matlab.input_spec(), 'nosoftwareopengl', openGL_trait() )
if sys.platform.startswith('linux'):
matlab.inputs.args = '-nosoftwareopengl' # Bug, for my laptop, it does not work, but the command line does have the flag -nosoftwareopengl, we should try on other computer's matlab to check if this flag works!
matlab.inputs.paths = path_to_matscript # CLINICA_HOME, this is the path to add into matlab, addpath
matlab.inputs.script = """
clinicasurfstat('%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', %d, '%s', %.3f, '%s', %.3f, '%s', %.3f);
""" % (input_directory, output_directory, subjects_visits_tsv, design_matrix, contrast, str_format, glm_type, group_label, freesurfer_home, surface_file, feature_label, 'sizeoffwhm',
full_width_at_half_maximum,
'thresholduncorrectedpvalue', threshold_uncorrected_pvalue, 'thresholdcorrectedpvalue',
threshold_corrected_pvalue, 'clusterthreshold',
cluster_threshold) # here, we should define the inputs for the matlab function that you want to use
matlab.inputs.mfile = True # this will create a file: pyscript.m , the pyscript.m is the default name
matlab.inputs.single_comp_thread = False # this will stop runing with single thread
matlab.inputs.logfile = join(output_directory, "matlab_output.log")
cprint("Matlab logfile is located in the folder: %s" % matlab.inputs.logfile)
cprint("Matlab script command = %s" % matlab.inputs.script)
cprint("MatlabCommand inputs flag: single_comp_thread = %s" % matlab.inputs.single_comp_thread)
cprint("MatlabCommand choose which matlab to use(matlab_cmd): %s" % get_matlab_command())
if sys.platform.startswith('linux'):
cprint("MatlabCommand inputs flag: nosoftwareopengl = %s" % matlab.inputs.args)
out = matlab.run()
return out
from nipype.algorithms.rapidart import ArtifactDetect
from nipype.algorithms.misc import TSNR, Gunzip
from nipype.algorithms.modelgen import SpecifySPMModel
from nipype.pipeline.engine import Workflow, Node, MapNode
# MATLAB - Specify path to current SPM and the MATLAB's default mode
from nipype.interfaces.matlab import MatlabCommand
#change
##Edit as necessary
# preprocess(studyfile, startSubject, endSubject):
#Have to check this path
MatlabCommand.set_default_paths(
'/Users/lighthalllab/Documents/MATLAB/toolbox/spm12')
MatlabCommand.set_default_matlab_cmd(
"/Applications/MATLAB_R2015a.app/bin/matlab -nodesktop -nosplash")
"""
# FreeSurfer - Specify the location of the freesurfer folder
fs_dir = '/Volumes/Research2/Lighthall_Lab/experiments/cjfmri-1/data/fmri/Lucy_testing/Copy/Func/freesurfer'
FSCommand.set_default_subjects_dir(fs_dir)"""
###
# Specify variables
experiment_dir = '/Volumes/Research2/Lighthall_Lab/experiments/cjfmri-1/data/fmri/Lucy_testing/Copy/Func' # location of experiment folder
output_dir = 'output_fMRI_example_1st' # name of 1st-level output folder
working_dir = 'workingdir_fMRI_example_4rd' # name of 1st-level working directory
subject_list = ["1002", "1003"] # list of subject identifiers
session_list = ['Enc1', 'Jud2'] # list of session identifiers
number_of_slices = 38 # number of slices in volume
import os
import socket
from nipype.interfaces.matlab import MatlabCommand
if socket.gethostname() == 'malin':
os.environ['MATLABCMD'] = "/opt/matlab/R2015b/bin/matlab -nodesktop -nosplash"
MatlabCommand.set_default_paths('/opt/matlab/R2015b/toolbox/spm12')
MatlabCommand.set_default_matlab_cmd("/opt/matlab/R2015b/bin/matlab -nodesktop -nosplash")
TPM = '/opt/matlab/R2015b/toolbox/spm12/tpm/TPM.nii'
# os.environ['MATLABCMD'] = "/opt/matlab/R2012a/bin/matlab -nodesktop -nosplash"
# MatlabCommand.set_default_paths('/opt/matlab/R2012a/toolbox/spm12')
# MatlabCommand.set_default_matlab_cmd("/opt/matlab/R2012a/bin/matlab -nodesktop -nosplash")
elif socket.gethostname() == 'cala':
os.environ['MATLABCMD'] = "/opt/matlab/64bit/R2015a/bin/matlab -nodesktop -nosplash"
MatlabCommand.set_default_paths('/opt/matlab/64bit/R2015a/toolbox/spm12')
MatlabCommand.set_default_matlab_cmd("/opt/matlab/64bit/R2015a/bin/matlab -nodesktop -nosplash")
TPM = '/opt/matlab/64bit/R2015a/toolbox/spm12/tpm/TPM.nii'
def display_crash_files(crashfile, rerun=False):
from nipype.utils.filemanip import loadcrash
crash_data = loadcrash(crashfile)
node = crash_data['node']
tb = crash_data['traceback']
print("\n")
print("File: %s"%crashfile)
print("Node: %s"%node)
if node.base_dir:
print("Working directory: %s" % node.output_dir())
else:
print("Node crashed before execution")
print("\n")
#!/usr/bin/env python
import nipype.interfaces.spm as spm
import nipype.pipeline.engine as pe
from nipype.interfaces.matlab import MatlabCommand
matlab_cmd = '/usr/local/MATLAB/R2019a/bin/matlab'
default_mask = '/media/grg/home/grg/SPM/MNI_T1_brain_wo_csf.nii'
spm.SPMCommand.set_mlab_paths(matlab_cmd=matlab_cmd)
MatlabCommand.set_default_matlab_cmd('matlab -nodesktop -noplash')
def make_contrasts(names):
contrasts = []
cont1 = ('Effect of age (+)', 'T', ['age'], [1])
cont2 = ('Effect of age (-)', 'T', ['age'], [-1])
contrasts.append(cont1)
contrasts.append(cont2)
return contrasts
# cont1 = ('Apo2-3>Apo2-4', 'T', ['Apoe2-3', 'Apoe2-4'], [1, -1])
# cont2 = ('Apo2-4>Apo3-3', 'T', ['Apoe2-4', 'Apoe3-3'], [1, -1])
# cont3 = ('Apo3-3>Apo3-4', 'T', ['Apoe3-3', 'Apoe3-4'], [1, -1])
# cont4 = ('Apo3-4>Apo4-4', 'T', ['Apoe3-4', 'Apoe4-4'], [1, -1])
# cont4 = ('Apo4-4>Apo3-3', 'T', ['Apoe4-4', 'Apoe3-3'], [1, -1])
# cont5 = ('Main effect ApoE', 'F', [cont1, cont2, cont3, cont4])
# cont6 = ('C<NC', 'T', ['Apoe2-3', 'Apoe2-4', 'Apoe3-3', 'Apoe3-4', 'Apoe4-4'], [3, -2, 3, -2, -2])
# cont7 = ('C>NC', 'T', ['Apoe2-3', 'Apoe2-4', 'Apoe3-3', 'Apoe3-4', 'Apoe4-4'], [-3, 2, -3, 2, 2])
