def select_data_set(self, name):
size_pyramid = 9
factor = 3
self.hic_pyr = pyr.build_and_filter(
self.base_folder,
size_pyramid,
factor,
thresh_factor=self.thresh_factor,
)
print("pyramid loaded")
if not (os.path.exists(self.output_folder)):
os.mkdir(self.output_folder)
self.output_folder = os.path.join(self.output_folder, self.data_set)
if not (os.path.exists(self.output_folder)):
os.mkdir(self.output_folder)
self.output_folder = os.path.join(self.output_folder,
"test_mcmc_" + self.str_level)
if not (os.path.exists(self.output_folder)):
os.mkdir(self.output_folder)
self.new_fasta = os.path.join(self.output_folder, "genome.fasta")
self.info_frags = os.path.join(self.output_folder, "info_frags.txt")
self.output_matrix_em = os.path.join(self.output_folder,
"post_em.tiff")
self.output_matrix_mcmc = os.path.join(self.output_folder,
"post_mcmc.tiff")
self.input_matrix = os.path.join(self.output_folder, "pre_simu.tiff")
self.scrambled_input_matrix = os.path.join(self.output_folder,
"scrambled_simu.tiff")
def run(self):
"""Run Worker Thread."""
# This is the code executing in the new thread. Simulation of
# a long process (well, 10s here) as a simple loop - you will
# need to structure your processing so that you periodically
# peek at the abort variable
pyramid = pyr.build_and_filter(self.base_folder, self.size_pyramid, self.factor)
lev = pyr.level(pyramid, 2)
# Here's where the result would be returned (this is an
# example fixed result of the number 10, but it could be
# any Python object)
wx.PostEvent(self._notify_window, ResultEvent(pyramid))
def run(self):
"""Run Worker Thread."""
# This is the code executing in the new thread. Simulation of
# a long process (well, 10s here) as a simple loop - you will
# need to structure your processing so that you periodically
# peek at the abort variable
pyramid = pyr.build_and_filter(self.base_folder, self.size_pyramid, self.factor)
lev = pyr.level(pyramid, 2)
# Here's where the result would be returned (this is an
# example fixed result of the number 10, but it could be
# any Python object)
wx.PostEvent(self._notify_window, ResultEvent(pyramid))
def select_data_set(self, name):
hostname = socket.gethostname()
print "Host name:", hostname
ordi = hostname.split('.')[0]
if name == 'tricho' or name == 'tricho_rutc30' or name == 'tricho_qm6a':
size_pyramid = 6
elif name == 'ykf1246_new_hq' or name == 'ykf1246_new_ref_hq' or name == 'ykf1246_axel':
size_pyramid = 6
elif name == "amibes_full_2014":
size_pyramid = 7
elif name == "community_33" or name == "community_75" or name == 'community_24' or name == 'community_0' or name == 'community_axel':
size_pyramid = 6
elif name == 'yvette_comm_0':
size_pyramid = 6
elif name == 'yvette_comm_156':
size_pyramid = 6
elif name == 'yvette_comm_0_156':
size_pyramid = 6
elif name == 'yvette_comm_2':
size_pyramid = 5
elif name == 'meta_ecoli' or name == '3bacts' or name == 'com2_3bacts' :
size_pyramid = 6
else: # or name == '3bacts' or name == 'meta_ecoli'
size_pyramid = 4
if name == 'ykf1246_new_hq':
factor = 3
# elif name == 'ykf1246_new_ref_hq_2' or name == 'ykf1246_axel':
elif name == 'ykf1246_new_ref_hq_2':
factor = 2
else:
factor = 3
min_bin_per_contig = 1
size_chunk = 5000
self.data_set = dict()
self.data_set['malesian'] = 'malesian/'
self.data_set['community_0'] = 'community_0/'
self.data_set['community_33'] = 'community_33/'
self.data_set["community_75"] = "community_75"
self.data_set['community_24'] = 'community_24'
self.data_set['community_axel'] = 'community_axel'
self.data_set['S1'] = 'S1/'
self.data_set['3bacts'] = '3bacts/'
self.data_set['meta_ecoli'] = 'meta_ecoli/'
self.data_set['com2_3bacts'] = 'com2_3bacts/'
self.data_set['G1'] = 'G1/'
self.data_set['tricho'] = 'tricho/'
self.data_set['tricho_rutc30'] = 'tricho_rutc30'
self.data_set['tricho_qm6a'] = 'tricho_qm6a'
self.data_set['ykf1246'] = 'ykf1246'
self.data_set['ykf1246_new'] = 'ykf1246_new'
self.data_set['ykf1246_new_hq'] = 'ykf1246_new_hq'
self.data_set['ykf1246_new_ref_hq_2'] = 'ykf1246_new_ref_hq_2'
self.data_set['ykf1246_axel'] = 'ykf1246_axel'
self.data_set['ykf175n'] = 'ykf175n'
self.data_set['amibes_full_2014'] = 'amibes_full_2014'
self.data_set['yvette_comm_0'] = 'yvette_comm_0'
self.data_set['yvette_comm_156'] = 'yvette_comm_156'
self.data_set['yvette_comm_0_156'] = 'yvette_comm_0_156'
self.data_set['yvette_comm_2'] = 'yvette_comm_2'
selected = name
if ordi == 'matisse':
if selected == 'tricho' or selected == 'tricho_rutc30' or selected == 'tricho_qm6a':
self.data_set_root = '/media/hervemn/LaCie/data_hic/data_set_assembly/'
self.fasta = '/media/hervemn/LaCie/data_hic/fasta_genomes/trichoderma/trichoderma_new.fa'
else:
self.data_set_root = '/media/hervemn/data/data_set_assembly/'
if self.name == "community_33":
self.fasta = '/media/hervemn/data/genome_fasta/community_33/community_33.fasta'
elif self.name == "community_75":
self.fasta = '/media/hervemn/data/genome_fasta/community_75/community_75.fasta'
elif self.name == 'community_24':
self.fasta = '/media/hervemn/data/genome_fasta/community_24/community_24.fasta'
elif self.name == 'community_axel':
self.fasta = '/media/hervemn/data/genome_fasta/community_axel/community_axel.fasta'
else:
self.fasta = '/media/hervemn/LaCie/data_hic/fasta_genomes/cerevisiae_classic/new_ref_genome.fsa'
self.dir_home = '/home/hervemn/'
if ordi == 'rv-retina':
self.data_set_root = '/Volumes/VeryBigData/HiC/data_set_assembly'
self.dir_home = '/Users/hervemarie-nelly/'
if selected == "tricho" or selected == 'tricho_rutc30' or selected == 'tricho_qm6a':
self.fasta = '/Volumes/VeryBigData/HiC/fasta_genomes/trichoderma/trichoderma_new.fa'
else:
self.fasta = '/Volumes/VeryBigData/HiC/fasta_genomes/cerevisiae_classic/new_ref_genome.fsa'
if ordi == 'loopkin':
self.data_set_root = '/data/hervemn/data_set_assembly/'
self.dir_home = '/home/hervemn/'
if selected == "tricho" or selected == 'tricho_rutc30' or selected == 'tricho_qm6a':
self.fasta = '/data/hervemn/alignment_toolbox/fasta_genomes/trichoderma/trichoderma_new.fa'
elif selected == "amibes_full_2014":
self.fasta = '/data/hervemn/alignment_toolbox/fasta_genomes/amoeba/EHI_v13.fa'
elif selected == 'community_0':
self.fasta = '/data/hervemn/data_set_assembly/community_0/analysis/community_0.fasta'
elif selected == 'community_24':
self.fasta = '/data/hervemn/data_set_assembly/community_24/analysis/community_24.fasta'
elif selected == 'community_33':
self.fasta = '/data/hervemn/data_set_assembly/community_33/analysis/community_33.fasta'
elif selected == 'community_75':
self.fasta = '/data/hervemn/data_set_assembly/community_75/analysis/community_75.fasta'
elif selected == 'community_axel':
self.fasta = '/data/hervemn/data_set_assembly/community_axel/analysis/community_axel.fasta'
elif selected == 'yvette_comm_0':
self.fasta = '/data/hervemn/data_set_assembly/yvette_comm_0/analysis/community_0.fasta'
else:
self.fasta = '/data/hervemn/alignment_toolbox/fasta_genomes/cerevisiae_classic/new_ref_genome.fsa'
if ordi == 'duvel':
self.data_set_root = '/media/hervemn/data/HiC/data_set_assembly/'
self.dir_home = '/home/hervemn/'
if selected == 'tricho' or selected == 'tricho_rutc30' or selected == 'tricho_qm6a':
self.fasta = '/media/hervemn/data/HiC/fasta_genomes/trichoderma/trichoderma_new.fa'
elif selected == 'community_0':
self.fasta = '/media/hervemn/data/HiC/data_set_assembly/community_0/analysis/community_0.fasta'
elif selected == 'community_24':
self.fasta = '/media/hervemn/data/HiC/data_set_assembly/community_24/analysis/community_24.fasta'
elif selected == 'community_33':
self.fasta = '/media/hervemn/data/HiC/data_set_assembly/community_33/analysis/community_33.fasta'
elif selected == 'community_75':
self.fasta = '/media/hervemn/data/HiC/data_set_assembly/community_75/analysis/community_75.fasta'
elif selected == 'community_axel':
self.fasta = '/media/hervemn/data/HiC/data_set_assembly/community_axel/analysis/community_axel.fasta'
elif selected == '3bacts':
self.fasta = '/media/hervemn/data/HiC/data_set_assembly/3bacts/analysis/contigs_3bacts.fasta'
elif selected == 'meta_ecoli':
self.fasta = '/media/hervemn/data/HiC/data_set_assembly/meta_ecoli/analysis/community_1.fasta'
elif selected == 'com2_3bacts':
self.fasta = '/media/hervemn/data/HiC/data_set_assembly/com2_3bacts/analysis/community_2.fasta'
elif selected == 'yvette_comm_0':
self.fasta = '/media/hervemn/data/HiC/data_set_assembly/yvette_comm_0/analysis/community_0.fasta'
elif selected == 'yvette_comm_156':
self.fasta = '/media/hervemn/data/HiC/data_set_assembly/yvette_comm_156/analysis/community_156.fasta'
elif selected == 'yvette_comm_0_156':
self.fasta = '/media/hervemn/data/HiC/data_set_assembly/yvette_comm_0_156/analysis/community_0_156.fasta'
elif selected == 'yvette_comm_2':
self.fasta = '/media/hervemn/data/HiC/data_set_assembly/yvette_comm_2/analysis/community_2.fasta'
elif selected == 'amibes_full_2014':
self.fasta = '/media/hervemn/data/HiC/fasta_genomes/amoeba/EHI_v13.fa'
else:
self.fasta = '/media/hervemn/data/HiC/fasta_genomes/cerevisiae_classic/new_ref_genome.fsa'
default_level = size_pyramid - 1
self.base_folder = os.path.join(self.data_set_root, self.data_set[selected], 'analysis')
# self.hic_pyr = pyr.build_and_filter(self.base_folder, size_pyramid, factor, min_bin_per_contig, size_chunk,
# default_level)
self.hic_pyr = pyr.build_and_filter(self.base_folder, size_pyramid, factor)
print "pyramid loaded"
################################################################################################################
self.output_folder = os.path.join(self.data_set_root, 'results')
if not (os.path.exists(self.output_folder)):
os.mkdir(self.output_folder)
self.output_folder = os.path.join(self.data_set_root, 'results', self.data_set[selected])
if not (os.path.exists(self.output_folder)):
os.mkdir(self.output_folder)
if not (os.path.exists(self.output_folder)):
os.mkdir(self.output_folder)
self.output_folder = os.path.join(self.data_set_root, 'results', self.data_set[selected],
'test_mcmc_' + self.str_level)
if not (os.path.exists(self.output_folder)):
os.mkdir(self.output_folder)
if self.fact_sub_sampling > 0:
self.folder_sub_sampling = os.path.join(self.output_folder, 'sub_sampling')
if not (os.path.exists(self.folder_sub_sampling)):
os.mkdir(self.folder_sub_sampling)
self.output_folder = os.path.join(self.folder_sub_sampling, str(self.fact_sub_sampling))
if not (os.path.exists(self.output_folder)):
os.mkdir(self.output_folder)
def select_data_set(self, name):
hostname = socket.gethostname()
print "Host name:", hostname
ordi = hostname.split('.')[0]
if name == 'tricho' or name == 'tricho_rutc30' or name == 'tricho_qm6a':
size_pyramid = 6
elif name == 'ykf1246_new_hq' or name == 'ykf1246_new_ref_hq' or name == 'ykf1246_axel':
size_pyramid = 6
elif name == "amibes_full_2014":
size_pyramid = 7
elif name == "community_33" or name == "community_75" or name == 'community_24' or name == 'community_0' or name == 'community_axel':
size_pyramid = 6
elif name == 'yvette_comm_0':
size_pyramid = 6
elif name == 'yvette_comm_156':
size_pyramid = 6
elif name == 'yvette_comm_0_156':
size_pyramid = 6
elif name == 'yvette_comm_2':
size_pyramid = 5
elif name == 'meta_ecoli' or name == '3bacts' or name == 'com2_3bacts' :
size_pyramid = 6
else: # or name == '3bacts' or name == 'meta_ecoli'
size_pyramid = 4
if name == 'ykf1246_new_hq':
factor = 3
# elif name == 'ykf1246_new_ref_hq_2' or name == 'ykf1246_axel':
elif name == 'ykf1246_new_ref_hq_2':
factor = 2
else:
factor = 3
min_bin_per_contig = 1
size_chunk = 5000
self.data_set = dict()
self.data_set['malesian'] = 'malesian/'
self.data_set['community_0'] = 'community_0/'
self.data_set['community_33'] = 'community_33/'
self.data_set["community_75"] = "community_75"
self.data_set['community_24'] = 'community_24'
self.data_set['community_axel'] = 'community_axel'
self.data_set['S1'] = 'S1/'
self.data_set['3bacts'] = '3bacts/'
self.data_set['meta_ecoli'] = 'meta_ecoli/'
self.data_set['com2_3bacts'] = 'com2_3bacts/'
self.data_set['G1'] = 'G1/'
self.data_set['tricho'] = 'tricho/'
self.data_set['tricho_rutc30'] = 'tricho_rutc30'
self.data_set['tricho_qm6a'] = 'tricho_qm6a'
self.data_set['ykf1246'] = 'ykf1246'
self.data_set['ykf1246_new'] = 'ykf1246_new'
self.data_set['ykf1246_new_hq'] = 'ykf1246_new_hq'
self.data_set['ykf1246_new_ref_hq_2'] = 'ykf1246_new_ref_hq_2'
self.data_set['ykf1246_axel'] = 'ykf1246_axel'
self.data_set['ykf175n'] = 'ykf175n'
self.data_set['amibes_full_2014'] = 'amibes_full_2014'
self.data_set['yvette_comm_0'] = 'yvette_comm_0'
self.data_set['yvette_comm_156'] = 'yvette_comm_156'
self.data_set['yvette_comm_0_156'] = 'yvette_comm_0_156'
self.data_set['yvette_comm_2'] = 'yvette_comm_2'
selected = name
if ordi == 'matisse':
if selected == 'tricho' or selected == 'tricho_rutc30' or selected == 'tricho_qm6a':
self.data_set_root = '/media/hervemn/LaCie/data_hic/data_set_assembly/'
self.fasta = '/media/hervemn/LaCie/data_hic/fasta_genomes/trichoderma/trichoderma_new.fa'
else:
self.data_set_root = '/media/hervemn/data/data_set_assembly/'
if self.name == "community_33":
self.fasta = '/media/hervemn/data/genome_fasta/community_33/community_33.fasta'
elif self.name == "community_75":
self.fasta = '/media/hervemn/data/genome_fasta/community_75/community_75.fasta'
elif self.name == 'community_24':
self.fasta = '/media/hervemn/data/genome_fasta/community_24/community_24.fasta'
elif self.name == 'community_axel':
self.fasta = '/media/hervemn/data/genome_fasta/community_axel/community_axel.fasta'
else:
self.fasta = '/media/hervemn/LaCie/data_hic/fasta_genomes/cerevisiae_classic/new_ref_genome.fsa'
self.dir_home = '/home/hervemn/'
if ordi == 'rv-retina':
self.data_set_root = '/Volumes/VeryBigData/HiC/data_set_assembly'
self.dir_home = '/Users/hervemarie-nelly/'
if selected == "tricho" or selected == 'tricho_rutc30' or selected == 'tricho_qm6a':
self.fasta = '/Volumes/VeryBigData/HiC/fasta_genomes/trichoderma/trichoderma_new.fa'
else:
self.fasta = '/Volumes/VeryBigData/HiC/fasta_genomes/cerevisiae_classic/new_ref_genome.fsa'
if ordi == 'loopkin':
self.data_set_root = '/data/hervemn/data_set_assembly/'
self.dir_home = '/home/hervemn/'
if selected == "tricho" or selected == 'tricho_rutc30' or selected == 'tricho_qm6a':
self.fasta = '/data/hervemn/alignment_toolbox/fasta_genomes/trichoderma/trichoderma_new.fa'
elif selected == "amibes_full_2014":
self.fasta = '/data/hervemn/alignment_toolbox/fasta_genomes/amoeba/EHI_v13.fa'
elif selected == 'community_0':
self.fasta = '/data/hervemn/data_set_assembly/community_0/analysis/community_0.fasta'
elif selected == 'community_24':
self.fasta = '/data/hervemn/data_set_assembly/community_24/analysis/community_24.fasta'
elif selected == 'community_33':
self.fasta = '/data/hervemn/data_set_assembly/community_33/analysis/community_33.fasta'
elif selected == 'community_75':
self.fasta = '/data/hervemn/data_set_assembly/community_75/analysis/community_75.fasta'
elif selected == 'community_axel':
self.fasta = '/data/hervemn/data_set_assembly/community_axel/analysis/community_axel.fasta'
elif selected == 'yvette_comm_0':
self.fasta = '/data/hervemn/data_set_assembly/yvette_comm_0/analysis/community_0.fasta'
else:
self.fasta = '/data/hervemn/alignment_toolbox/fasta_genomes/cerevisiae_classic/new_ref_genome.fsa'
if ordi == 'duvel':
self.data_set_root = '/media/hervemn/data/HiC/data_set_assembly/'
self.dir_home = '/home/hervemn/'
if selected == 'tricho' or selected == 'tricho_rutc30' or selected == 'tricho_qm6a':
self.fasta = '/media/hervemn/data/HiC/fasta_genomes/trichoderma/trichoderma_new.fa'
elif selected == 'community_0':
self.fasta = '/media/hervemn/data/HiC/data_set_assembly/community_0/analysis/community_0.fasta'
elif selected == 'community_24':
self.fasta = '/media/hervemn/data/HiC/data_set_assembly/community_24/analysis/community_24.fasta'
elif selected == 'community_33':
self.fasta = '/media/hervemn/data/HiC/data_set_assembly/community_33/analysis/community_33.fasta'
elif selected == 'community_75':
self.fasta = '/media/hervemn/data/HiC/data_set_assembly/community_75/analysis/community_75.fasta'
elif selected == 'community_axel':
self.fasta = '/media/hervemn/data/HiC/data_set_assembly/community_axel/analysis/community_axel.fasta'
elif selected == '3bacts':
self.fasta = '/media/hervemn/data/HiC/data_set_assembly/3bacts/analysis/contigs_3bacts.fasta'
elif selected == 'meta_ecoli':
self.fasta = '/media/hervemn/data/HiC/data_set_assembly/meta_ecoli/analysis/community_1.fasta'
elif selected == 'com2_3bacts':
self.fasta = '/media/hervemn/data/HiC/data_set_assembly/com2_3bacts/analysis/community_2.fasta'
elif selected == 'yvette_comm_0':
self.fasta = '/media/hervemn/data/HiC/data_set_assembly/yvette_comm_0/analysis/community_0.fasta'
elif selected == 'yvette_comm_156':
self.fasta = '/media/hervemn/data/HiC/data_set_assembly/yvette_comm_156/analysis/community_156.fasta'
elif selected == 'yvette_comm_0_156':
self.fasta = '/media/hervemn/data/HiC/data_set_assembly/yvette_comm_0_156/analysis/community_0_156.fasta'
elif selected == 'yvette_comm_2':
self.fasta = '/media/hervemn/data/HiC/data_set_assembly/yvette_comm_2/analysis/community_2.fasta'
elif selected == 'amibes_full_2014':
self.fasta = '/media/hervemn/data/HiC/fasta_genomes/amoeba/EHI_v13.fa'
else:
self.fasta = '/media/hervemn/data/HiC/fasta_genomes/cerevisiae_classic/new_ref_genome.fsa'
default_level = size_pyramid - 1
self.base_folder = os.path.join(self.data_set_root, self.data_set[selected], 'analysis')
# self.hic_pyr = pyr.build_and_filter(self.base_folder, size_pyramid, factor, min_bin_per_contig, size_chunk,
# default_level)
self.hic_pyr = pyr.build_and_filter(self.base_folder, size_pyramid, factor)
print "pyramid loaded"
################################################################################################################
self.output_folder = os.path.join(self.data_set_root, 'results')
if not (os.path.exists(self.output_folder)):
os.mkdir(self.output_folder)
self.output_folder = os.path.join(self.data_set_root, 'results', self.data_set[selected])
if not (os.path.exists(self.output_folder)):
os.mkdir(self.output_folder)
if not (os.path.exists(self.output_folder)):
os.mkdir(self.output_folder)
self.output_folder = os.path.join(self.data_set_root, 'results', self.data_set[selected],
'test_mcmc_' + self.str_level)
if not (os.path.exists(self.output_folder)):
os.mkdir(self.output_folder)
if self.fact_sub_sampling > 0:
self.folder_sub_sampling = os.path.join(self.output_folder, 'sub_sampling')
if not (os.path.exists(self.folder_sub_sampling)):
os.mkdir(self.folder_sub_sampling)
self.output_folder = os.path.join(self.folder_sub_sampling, str(self.fact_sub_sampling))
if not (os.path.exists(self.output_folder)):
os.mkdir(self.output_folder)
def select_data_set(self, name, size_pyramid=7):
factor = 3
self.data_set = dict()
self.data_set['tricho_qm6a_sparse'] = 'tricho_qm6a_sparse'
self.data_set['S1'] = 'S1'
self.data_set['amoeba'] = 'amoeba'
self.data_set['mosquito'] = 'mosquito'
self.data_set['de_novo_chr14_jff'] = 'de_novo_chr14_jff'
self.data_set['de_novo_chr14'] = 'de_novo_chr14'
self.data_set['s1_de_novo'] = 's1_de_novo'
self.data_set['s1_de_novo_0_1'] = 's1_de_novo_0_1'
self.data_set['human_chr4_chr14'] = 'human_chr4_chr14'
self.data_set['human_chr19_to_22'] = 'human_chr19_to_22'
self.data_set['human_chr7_chr22'] = 'human_chr7_chr22'
selected = name
toolbox_directory = os.path.dirname(os.path.abspath(__file__))
self.fasta = os.path.join(toolbox_directory, 'fasta', selected + '.fa')
self.data_set = dict({selected: selected})
self.data_set_root = toolbox_directory
if hostname == 'duvel':
self.dir_home = '/mirror/'
self.data_set_root = '/mirror/data/'
if selected == 'mosquito':
self.dir_home = '/media/hervemn/data/HiC/'
self.data_set_root = '/media/hervemn/data/HiC/data_set_assembly'
if selected == 'tricho_qm6a_sparse':
self.fasta = os.path.join(
self.dir_home,
'fasta_genomes/trichoderma/trichoderma_new.fa')
elif selected == 'S1':
self.fasta = os.path.join(
self.dir_home,
'fasta_genomes/cerevisiae_classic/new_ref_genome.fsa')
elif selected == 'amoeba':
self.fasta = os.path.join(self.dir_home,
'fasta_genomes/amoeba/EHI_v13.fa')
elif selected == 'mosquito':
self.fasta = os.path.join(
self.dir_home,
'fasta_genomes/aedes_aegypti/Aedes_aegypti.fa.parsed')
elif selected == 'de_novo_chr14' or selected == 'de_novo_chr14_jff':
self.fasta = os.path.join(
self.dir_home,
'fasta_genomes/de_novo_chr14/genome.ctg.fasta')
elif selected == 'human_chr4_chr14':
self.fasta = os.path.join(
self.dir_home,
'fasta_genomes/human_chr4_chr14/human_4_14.fa')
elif selected == 'human_chr19_to_22':
self.fasta = os.path.join(
self.dir_home,
'fasta_genomes/human_chr19_to_22/chr19_chr20_chr21_chr22.fa'
)
elif selected == 'human_chr7_chr22':
self.fasta = os.path.join(
self.dir_home,
'fasta_genomes/human_chr7_chr22/chr7_chr17_chr19_chr22.fa')
elif selected == 's1_de_novo' or selected == 's1_de_novo_0_1':
self.fasta = os.path.join(
self.dir_home,
'fasta_genomes/cerevisiae_de_novo/cerevisiae_de_novo.fa')
else:
self.dir_home = toolbox_directory
self.data_set_root = toolbox_directory
if selected == 'mosquito':
self.dir_home = '/media/hervemn/data/HiC/'
self.data_set_root = '/media/hervemn/data/HiC/data_set_assembly'
elif selected == 'tricho_qm6a_sparse':
self.fasta = os.path.join(
self.dir_home, 'alignment_toolbox',
'fasta_genomes/trichoderma/trichoderma_new.fa')
elif selected == 'S1':
self.fasta = os.path.join(
self.dir_home, 'alignment_toolbox',
'fasta_genomes/cerevisiae_classic/new_ref_genome.fsa')
elif selected == 'amoeba':
self.fasta = os.path.join(self.dir_home, 'alignment_toolbox',
'fasta_genomes/amoeba/EHI_v13.fa')
elif selected == 'mosquito':
self.fasta = os.path.join(
self.dir_home, 'alignment_toolbox',
'fasta_genomes/aedes_aegypti/Aedes_aegypti.fa.parsed')
elif selected == 'de_novo_chr14' or selected == 'de_novo_chr14_fjff':
self.fasta = os.path.join(
self.dir_home, 'alignment_toolbox',
'fasta_genomes/de_novo_chr14/genome.ctg.fasta')
elif selected == 'human_chr4_chr14':
self.fasta = os.path.join(
self.dir_home, 'alignment_toolbox',
'fasta_genomes/human_chr4_chr14/human_4_14.fa')
elif selected == 'human_chr19_to_22':
self.fasta = os.path.join(
self.dir_home, 'alignment_toolbox',
'fasta_genomes/human_chr19_to_22/chr19_chr20_chr21_chr22.fa'
)
elif selected == 'human_chr7_chr22':
self.fasta = os.path.join(
self.dir_home, 'alignment_toolbox',
'fasta_genomes/human_chr7_chr22/chr7_chr17_chr19_chr22.fa')
elif selected == 's1_de_novo' or selected == 's1_de_novo_0_1':
self.fasta = os.path.join(
self.dir_home, 'alignment_toolbox',
'fasta_genomes/cerevisiae_de_novo/cerevisiae_de_novo.fa')
else:
self.fasta = os.path.join(toolbox_directory, 'fasta',
selected + '.fa')
default_level = size_pyramid - 1
self.base_folder = os.path.join(self.data_set_root,
self.data_set[selected], 'analysis')
self.hic_pyr = pyr.build_and_filter(self.base_folder, size_pyramid,
factor)
print "pyramid loaded"
################################################################################################################
self.output_folder = os.path.join(self.data_set_root, 'results')
if not (os.path.exists(self.output_folder)):
os.mkdir(self.output_folder)
self.output_folder = os.path.join(self.data_set_root, 'results',
self.data_set[selected])
if not (os.path.exists(self.output_folder)):
os.mkdir(self.output_folder)
if not (os.path.exists(self.output_folder)):
os.mkdir(self.output_folder)
self.output_folder = os.path.join(self.data_set_root, 'results',
self.data_set[selected],
'test_mcmc_' + self.str_level)
if not (os.path.exists(self.output_folder)):
os.mkdir(self.output_folder)
################################################################################################################
self.new_fasta = os.path.join(self.output_folder, 'genome.fasta')
self.info_frags = os.path.join(self.output_folder, 'info_frags.txt')
self.output_matrix_em = os.path.join(self.output_folder,
'post_em.tiff')
self.output_matrix_mcmc = os.path.join(self.output_folder,
'post_mcmc.tiff')
self.input_matrix = os.path.join(self.output_folder, 'pre_simu.tiff')
self.scrambled_input_matrix = os.path.join(self.output_folder,
'scrambled_simu.tiff')
