def pos(argv):
# default parameters
leg_file_name = None
in_only = False
# read arguments
try:
opts, args = getopt.getopt(argv[1:], "l:O")
except getopt.GetoptError as err:
sys.stderr.write("[E::" + __name__ + "] unknown command\n")
return 1
if len(args) == 0:
sys.stderr.write("Usage: dip-c leg [options] -l <in.leg> <in.3dg>\n")
sys.stderr.write("Options:\n")
sys.stderr.write(
" -l <in.leg> LEG file to convert to 3D positions (required)\n"
)
sys.stderr.write(" -O exclude out-of-bound legs\n")
return 1
for o, a in opts:
if o == "-l":
leg_file_name = a
if o == "-O":
in_only = True
if leg_file_name is None:
sys.stderr.write("[E::" + __name__ + "] -l is required\n")
return 1
# read 3DG file
g3d_data = file_to_g3d_data(open(args[0], "rb"))
g3d_data.sort_g3d_particles()
g3d_resolution = g3d_data.resolution()
sys.stderr.write(
"[M::" + __name__ + "] read a 3D structure with " +
str(g3d_data.num_g3d_particles()) + " particles at " +
("N.A." if g3d_resolution is None else str(g3d_resolution)) +
" bp resolution\n")
g3d_data.prepare_interpolate()
# convert LEG file to 3DG particles
for leg_file_line in open(leg_file_name, "rb"):
is_out, position = g3d_data.interpolate_leg(
string_to_leg(leg_file_line.strip()))
if position is None or (is_out and in_only):
sys.stdout.write("None\n")
else:
sys.stdout.write("\t".join(map(str, position)) + "\n")
return 0
def vis(argv):
# default parameters
color_file_name = None
missing_value = -1.0
discard_missing = False
# read arguments
try:
opts, args = getopt.getopt(argv[1:], "c:m:M")
except getopt.GetoptError as err:
sys.stderr.write("[E::" + __name__ + "] unknown command\n")
return 1
if len(args) == 0:
sys.stderr.write("Usage: dip-c vis [options] <in.3dg>\n")
sys.stderr.write("Options:\n")
sys.stderr.write(
" -c <color.txt> color by a list of locus-color pairs (tab-delimited: homolog, locus, color)\n"
)
sys.stderr.write(
" -m FLOAT color for particles that are missing from the color scheme ["
+ str(missing_value) + "]\n")
sys.stderr.write(
" -M discard particles that are missing from the color scheme\n\n"
)
sys.stderr.write("Output mmCIF format:\n")
sys.stderr.write(
" label_asym_id homolog name (e.g. \"1(mat)\")\n")
sys.stderr.write(
" label_comp_id locus // 1 Mb, 3 digits with leading zeros\n")
sys.stderr.write(" label_seq_id 1\n")
sys.stderr.write(
" label_atom_id locus % 1 Mb // 1 kb, 3 digits with leading zeros\n"
)
sys.stderr.write(" B_iso_or_equiv scalar color\n")
sys.stderr.write(" covale backbone bond\n")
return 1
num_color_schemes = 0
for o, a in opts:
if o == "-m":
missing_value = float(a)
elif o == "-c":
color_file_name = a
elif o == "-M":
discard_missing = True
# read 3DG file
g3d_data = file_to_g3d_data(open(args[0], "rb"))
g3d_data.sort_g3d_particles()
g3d_resolution = g3d_data.resolution()
sys.stderr.write(
"[M::" + __name__ + "] read a 3D structure with " +
str(g3d_data.num_g3d_particles()) + " particles at " +
("N.A." if g3d_resolution is None else str(g3d_resolution)) +
" bp resolution\n")
# read color file
color_data = {}
if not color_file_name is None:
color_file = open(color_file_name, "rb")
for color_file_line in color_file:
hom_name, ref_locus, color = color_file_line.strip().split("\t")
ref_locus = int(ref_locus)
color = float(color)
color_data[(hom_name, ref_locus)] = color
# open mmCIF file to write
myDataList = []
curContainer = DataContainer("myblock")
aCat = DataCategory("atom_site")
aCat.appendAttribute("group_PDB")
aCat.appendAttribute("type_symbol")
aCat.appendAttribute("id")
aCat.appendAttribute("label_asym_id")
aCat.appendAttribute("label_comp_id")
aCat.appendAttribute("label_seq_id")
aCat.appendAttribute("label_atom_id")
aCat.appendAttribute("Cartn_x")
aCat.appendAttribute("Cartn_y")
aCat.appendAttribute("Cartn_z")
aCat.appendAttribute("B_iso_or_equiv")
sCat = DataCategory("struct_conn")
sCat.appendAttribute("id")
sCat.appendAttribute("conn_type_id")
sCat.appendAttribute("ptnr1_label_asym_id")
sCat.appendAttribute("ptnr1_label_comp_id")
sCat.appendAttribute("ptnr1_label_seq_id")
sCat.appendAttribute("ptnr1_label_atom_id")
sCat.appendAttribute("ptnr2_label_asym_id")
sCat.appendAttribute("ptnr2_label_comp_id")
sCat.appendAttribute("ptnr2_label_seq_id")
sCat.appendAttribute("ptnr2_label_atom_id")
# write atoms
atom_id = 0
for g3d_particle in g3d_data.get_g3d_particles():
atom_id += 1
try:
color = color_data[(g3d_particle.get_hom_name(),
g3d_particle.get_ref_locus())]
except KeyError:
if discard_missing:
continue
color = missing_value
aCat.append(g3d_particle_to_atom_data(g3d_particle, atom_id, color))
# write backbond bonds
conn_id = 0
for g3d_particle_tuple in g3d_data.get_adjacent_g3d_particle_tuples(
g3d_resolution):
conn_id += 1
sCat.append(
g3d_particle_tuple_to_conn_data(g3d_particle_tuple, conn_id))
# write output
curContainer.append(sCat)
curContainer.append(aCat)
myDataList.append(curContainer)
pdbxW = PdbxWriter(sys.stdout)
pdbxW.write(myDataList)
return 0
def exp(argv):
# default parameters
expansion_factor = 3.0
centers_only = False
# read arguments
try:
opts, args = getopt.getopt(argv[1:], "f:c")
except getopt.GetoptError as err:
sys.stderr.write("[E::" + __name__ + "] unknown command\n")
return 1
if len(args) == 0:
sys.stderr.write("Usage: dip-c exp [options] <in.3dg>\n")
sys.stderr.write("Options:\n")
sys.stderr.write(
" -f FLOAT expansion factor for translating away from nuclear center ["
+ str(expansion_factor) + "]\n")
sys.stderr.write(" -c output centers of mass\n")
return 1
for o, a in opts:
if o == "-f":
expansion_factor = float(a)
if o == "-c":
centers_only = True
# read 3DG file
g3d_data = file_to_g3d_data(open(args[0], "rb"))
g3d_data.sort_g3d_particles()
g3d_resolution = g3d_data.resolution()
sys.stderr.write(
"[M::" + __name__ + "] read a 3D structure with " +
str(g3d_data.num_g3d_particles()) + " particles at " +
("N.A." if g3d_resolution is None else str(g3d_resolution)) +
" bp resolution\n")
# center of nucleus
nuc_center = center_g3d_particles(g3d_data.get_g3d_particles())
# process data
if centers_only:
center_g3d_data = G3dData()
for hom_name in g3d_data.get_hom_names():
center_position = center_g3d_particles(
g3d_data.get_g3d_particles_from_hom_name(hom_name))
center_position += (center_position -
nuc_center) * expansion_factor
center_g3d_data.add_g3d_particle(
G3dParticle(hom_name, 0, center_position.tolist()))
g3d_data = center_g3d_data
else:
hom_centers = {}
# center of each homologs
for hom_name in g3d_data.get_hom_names():
hom_centers[hom_name] = center_g3d_particles(
g3d_data.get_g3d_particles_from_hom_name(hom_name))
sys.stderr.write("extract " + hom_name_to_object_name(hom_name) +
", chain \"" + hom_name + "\"\n")
# translate
for hom_name in g3d_data.get_hom_names():
translation_vector = (hom_centers[hom_name] -
nuc_center) * expansion_factor
for g3d_particle in g3d_data.get_g3d_particles_from_hom_name(
hom_name):
g3d_particle.set_position(
(np.array(g3d_particle.get_position()) +
translation_vector).tolist())
#sys.stderr.write("translate [" + ",".join(map(str, translation_vector)) + "], chain \"" + hom_name + "\"\n")
sys.stderr.write("translate [" +
",".join(map(str, translation_vector)) +
"], object=" + hom_name_to_object_name(hom_name) +
", camera=0\n")
for hom_name in g3d_data.get_hom_names():
sys.stderr.write("mview store, object=" +
hom_name_to_object_name(hom_name) + "\n")
# output
sys.stderr.write("[M::" + __name__ + "] writing output for " +
str(g3d_data.num_g3d_particles()) + " particles\n")
sys.stdout.write(g3d_data.to_string() + "\n")
return 0
def impute3(argv):
# default parameters
g3d_file_name = None
vio_file_name = None
max_impute3_distance = 20
max_impute3_ratio = 0.5
min_impute3_separation_factor = 1.0
max_clean_distance = 10000000
min_clean_count = 2
is_male = False
par_data = None
# presets
h_par = ParData("X", "Y")
h_par.add_par(Par("X", 60000, 2699520, "Y", 10000))
h_par.add_par(Par("X", 154931043, 155260560, "Y", 59034049))
m_par = ParData("chrX", "chrY")
m_par.add_par(Par("chrX", 169969758, 170931299, "chrY", 90745844))
presets = {
"f": [False, None],
"hf": [False, None],
"mf": [False, None],
"hm": [True, h_par],
"mm": [True, m_par]
}
preset_descriptions = {
"f": "female",
"hf": "human female (same as f)",
"mf": "mouse female (same as f)",
"hm": "human male (hg19, no \"chr\" prefix)",
"mm": "mouse male (mm10)"
}
# progress display parameters
display_max_num_legs = 20
display_num_cons = 10000
# read arguments
try:
opts, args = getopt.getopt(argv[1:], "3:v:d:r:s:D:C:p:")
except getopt.GetoptError as err:
sys.stderr.write("[E::" + __name__ + "] unknown command\n")
return 1
if len(args) == 0:
sys.stderr.write(
"Usage: dip-c impute3 [options] -3 <in.3dg> [-v <out.vio>] <in.con>\n"
)
sys.stderr.write("Options:\n")
sys.stderr.write(
" -3 <in.3dg> 3D genome file for imputing haplotypes (required)\n"
)
sys.stderr.write(
" -v <out.vio> output statistics to a contact violation file:\n"
)
sys.stderr.write(
" tab-delimited: leg 1, leg 2, num of compatible haplotypes,\n"
)
sys.stderr.write(
" shortest 3D distance, ratio between the shortest and the 2nd shortest distance\n\n"
)
sys.stderr.write(
" -d FLOAT max 3D distance for imputing haplotypes [" +
str(max_impute3_distance) + "]\n")
sys.stderr.write(
" -r FLOAT max ratio between 3D distances for the best and 2nd best haplotypes ["
+ str(max_impute3_ratio) + "]\n")
sys.stderr.write(
" -s FLOAT min separation (unit: 3D genome resolution) for imputing\n"
)
sys.stderr.write(
" completely unphased, intra-chromosomal contacts ["
+ str(min_impute3_separation_factor) + "]\n\n")
sys.stderr.write(
" -D INT max distance (bp, L-1/2 norm) for removing isolated contacts ["
+ str(max_clean_distance) + "]\n")
sys.stderr.write(
" -C INT min neighbor count for an unisolated contact [" +
str(min_clean_count) + "]\n\n")
sys.stderr.write(" -p STR presets for PARs and sex: [f]\n")
for preset in sorted(presets.keys()):
sys.stderr.write(" " + preset + " = " +
preset_descriptions[preset] + "\n")
return 1
for o, a in opts:
if o == "-3":
g3d_file_name = a
elif o == "-v":
vio_file_name = a
elif o == "-d":
max_impute3_distance = float(a)
elif o == "-r":
max_impute3_ratio = float(a)
elif o == "-s":
min_impute3_separation_factor = float(a)
elif o == "-D":
max_clean_distance = int(a)
elif o == "-C":
min_clean_count = int(a)
elif o == "-p":
try:
is_male, par_data = presets[a]
sys.stderr.write("[M::" + __name__ + "] use preset " + a +
" = " + preset_descriptions[a] + "\n")
except KeyError:
sys.stderr.write("[E::" + __name__ + "] unknown preset\n")
return 1
if g3d_file_name is None:
sys.stderr.write("[E::" + __name__ + "] -3 is required\n")
return 1
# read 3DG file
g3d_data = file_to_g3d_data(open(g3d_file_name, "rb"))
g3d_data.sort_g3d_particles()
g3d_resolution = g3d_data.resolution()
sys.stderr.write(
"[M::" + __name__ + "] read a 3D structure with " +
str(g3d_data.num_g3d_particles()) + " particles at " +
("N.A." if g3d_resolution is None else str(g3d_resolution)) +
" bp resolution\n")
g3d_data.prepare_interpolate()
# read CON file
con_file = gzip.open(args[0], "rb") if args[0].endswith(".gz") else open(
args[0], "rb")
con_data = file_to_con_data(con_file)
sys.stderr.write(
"[M::" + __name__ + "] read " + str(con_data.num_cons()) +
" contacts (" +
str(round(100.0 * con_data.num_intra_chr() / con_data.num_cons(), 2)) +
"% intra-chromosomal, " + str(
round(100.0 * con_data.num_phased_legs() / con_data.num_cons() /
2, 2)) + "% legs phased)\n")
# impute3
vio_file = None
if not vio_file_name is None:
vio_file = open(vio_file_name, "wb")
con_data.impute_from_g3d_data(g3d_data, max_impute3_distance,
max_impute3_ratio,
max_impute3_ratio * g3d_resolution, is_male,
par_data, vio_file)
if not vio_file is None:
vio_file.close()
sys.stderr.write(
"[M::" + __name__ + "] imputed " + str(con_data.num_phased_cons()) +
" contacts (" +
str(round(100.0 * con_data.num_phased_cons() /
con_data.num_cons(), 2)) + "%)\n")
# clean imputed
con_data.sort_cons()
con_data.clean_unphased()
before_clean_num_cons = con_data.num_cons()
con_data.clean_isolated_phased(copy.deepcopy(con_data), max_clean_distance,
min_clean_count)
after_clean_num_cons = con_data.num_cons()
sys.stderr.write("[M::" + __name__ + "] removed " +
str(before_clean_num_cons - after_clean_num_cons) +
" isolated contacts (" + str(
round(
100.0 *
(before_clean_num_cons - after_clean_num_cons) /
before_clean_num_cons, 2)) + "%)\n")
# write output
sys.stderr.write(
"[M::" + __name__ + "] writing output for " +
str(con_data.num_cons()) + " contacts (" +
str(round(100.0 * con_data.num_intra_chr() / con_data.num_cons(), 2)) +
"% intra-chromosomal, " + str(
round(100.0 * con_data.num_phased_legs() / con_data.num_cons() /
2, 2)) + "% legs phased)\n")
sys.stdout.write(con_data.to_string() + "\n")
return 0
def color(argv):
# default parameters
color_file_name = None
color_mode = None
max_distance = None
smooth_distance = None
max_separation = None
# display parameters
disp_num_particles = 1000
# read arguments
try:
opts, args = getopt.getopt(argv[1:], "c:n:l:m:L:i:s:S:hd:r:I:C")
except getopt.GetoptError as err:
sys.stderr.write("[E::" + __name__ + "] unknown command\n")
return 1
if len(args) == 0:
sys.stderr.write("Usage: dip-c color [options] <in.3dg>\n")
sys.stderr.write("Options:\n")
sys.stderr.write(" -c <color.txt> color by a list of locus-color pairs (tab-delimited: chr, locus, color)\n")
sys.stderr.write(" -n <chr.txt> color by chromosome name (one chromosome per line)\n")
sys.stderr.write(" -l <chr.len> color by locus divided by chromosome length (tab-delimited: chr, len)\n")
sys.stderr.write(" -L <chr.cen> color by arm locus divided by arm length (tab-delimited: chr, len, center of centromere)\n")
sys.stderr.write(" -h color by distance to homologous locus\n\n")
sys.stderr.write(" -i FLOAT color by percentage of intra-homologous neighbors within a given distance\n")
sys.stderr.write(" -I FLOAT color by number of intra-homologous neighbors within a given distance\n")
sys.stderr.write(" -S INT (with \"-i\" or \"-I\") max separation (bp) for intra-homologous neighbors\n\n")
sys.stderr.write(" -d FLOAT color by homolog diversity within a given distance\n")
sys.stderr.write(" -r FLOAT color by homolog richness within a given distance\n\n")
sys.stderr.write(" -C color by distance to the nuclear center of mass\n")
sys.stderr.write(" -s FLOAT smooth color by averaging over a ball\n")
sys.stderr.write("Output:\n")
sys.stderr.write(" tab-delimited: homolog, locus, color\n")
return 1
num_color_schemes = 0
for o, a in opts:
if o == "-i" or o == "-I" or o == "-d" or o == "-r":
num_color_schemes += 1
color_mode = o[1:]
max_distance = float(a)
elif o == "-s":
smooth_distance = float(a)
elif o == "-S":
max_separation = int(a)
else:
num_color_schemes += 1
color_mode = o[1:]
if a != "":
color_file_name = a
if not max_separation is None and color_mode != "i":
sys.stderr.write("[E::" + __name__ + "] \"-S\" must be used with \"-i\"\n")
return 1
if num_color_schemes != 1:
sys.stderr.write("[E::" + __name__ + "] exactly one color scheme is needed\n")
return 1
# read 3DG file
g3d_data = file_to_g3d_data(open(args[0], "rb"))
g3d_data.sort_g3d_particles()
g3d_resolution = g3d_data.resolution()
sys.stderr.write("[M::" + __name__ + "] read a 3D structure with " + str(g3d_data.num_g3d_particles()) + " particles at " + ("N.A." if g3d_resolution is None else str(g3d_resolution)) + " bp resolution\n")
# open color file
if not color_file_name is None:
color_file = open(color_file_name, "rb")
# prepare
if color_mode is None:
pass
elif color_mode == "c":
ref_name_ref_locus_colors = {}
for color_file_line in color_file:
ref_name, ref_locus, color = color_file_line.strip().split("\t")
ref_locus = int(ref_locus)
color = float(color)
ref_name_ref_locus_colors[(ref_name, ref_locus)] = color
elif color_mode == "n":
ref_name_colors = {}
color_counter = 0
for color_file_line in color_file:
color_counter += 1
ref_name = color_file_line.strip()
ref_name_colors[ref_name] = color_counter
elif color_mode == "l":
ref_lens = {}
for color_file_line in color_file:
ref_name, ref_len = color_file_line.strip().split("\t")
ref_len = int(ref_len)
ref_lens[ref_name] = ref_len
elif color_mode == "L":
ref_lens = {}
ref_cens = {}
for color_file_line in color_file:
ref_name, ref_len, ref_cen = color_file_line.strip().split("\t")
ref_len = int(ref_len)
ref_cen = int(ref_cen)
ref_lens[ref_name] = ref_len
ref_cens[ref_name] = ref_cen
elif color_mode == "i" or color_mode == "I" or color_mode == "d" or color_mode == "r":
g3d_data.prepare_nearby()
elif color_mode == "C":
hom_names, loci_np_array, position_np_array = g3d_data.to_np_arrays()
center_mass = np.mean(position_np_array, axis = 0)
sys.stderr.write("[M::" + __name__ + "] center of mass is at (" + ", ".join(map(str, center_mass)) + ")\n")
# calculate colors for each particle
color_data = {}
atom_id = 0
for g3d_particle in g3d_data.get_g3d_particles():
atom_id += 1
if atom_id % disp_num_particles == 0:
sys.stderr.write("[M::" + __name__ + "] analyzed " + str(atom_id) + " particles (" + str(round(100.0 * atom_id / g3d_data.num_g3d_particles(), 2)) + "%)\n")
# color
if color_mode == "c":
try:
color = ref_name_ref_locus_colors[(g3d_particle.get_ref_name(), g3d_particle.get_ref_locus())]
except KeyError:
continue
elif color_mode == "n":
try:
color = ref_name_colors[g3d_particle.get_ref_name()]
except KeyError:
continue
elif color_mode == "l":
try:
color = float(g3d_particle.get_ref_locus()) / ref_lens[g3d_particle.get_ref_name()]
except KeyError:
continue
elif color_mode == "L":
try:
arm_locus = g3d_particle.get_ref_locus() - ref_cens[g3d_particle.get_ref_name()]
if arm_locus > 0:
arm_len = ref_lens[g3d_particle.get_ref_name()] - ref_cens[g3d_particle.get_ref_name()]
else:
arm_len = ref_cens[g3d_particle.get_ref_name()]
color = float(abs(arm_locus)) / arm_len
except KeyError:
continue
elif color_mode == "i":
color = intra_hom_fraction(g3d_particle, g3d_data.get_g3d_particles_near(g3d_particle.get_position(), max_distance), max_separation)
if color is None:
continue
elif color_mode == "I":
color = intra_hom_count(g3d_particle, g3d_data.get_g3d_particles_near(g3d_particle.get_position(), max_distance), max_separation)
elif color_mode == "h":
homologous_g3d_particle = g3d_data.get_g3d_particle_from_hom_name_ref_locus(homologous_hom_name(g3d_particle.get_hom_name()), g3d_particle.get_ref_locus())
if homologous_g3d_particle is None:
continue
color = math.sqrt((g3d_particle.get_x() - homologous_g3d_particle.get_x()) ** 2 + (g3d_particle.get_y() - homologous_g3d_particle.get_y()) ** 2 + (g3d_particle.get_z() - homologous_g3d_particle.get_z()) ** 2)
elif color_mode == "d":
color = hom_diversity(g3d_data.get_g3d_particles_near(g3d_particle.get_position(), max_distance))
elif color_mode == "r":
color = hom_richness(g3d_data.get_g3d_particles_near(g3d_particle.get_position(), max_distance))
elif color_mode == "C":
color = math.sqrt((g3d_particle.get_x() - center_mass[0]) ** 2 + (g3d_particle.get_y() - center_mass[1]) ** 2 + (g3d_particle.get_z() - center_mass[2]) ** 2)
#sys.stderr.write(str(color) + "\n")
color_data[g3d_particle.get_hom_name(), g3d_particle.get_ref_locus()] = color
# smoothing
if not smooth_distance is None:
g3d_data.prepare_nearby()
smooth_color_data = {}
atom_id = 0
for g3d_particle in g3d_data.get_g3d_particles():
atom_id += 1
if atom_id % disp_num_particles == 0:
sys.stderr.write("[M::" + __name__ + "] smoothed " + str(atom_id) + " particles (" + str(round(100.0 * atom_id / g3d_data.num_g3d_particles(), 2)) + "%)\n")
color = smooth_color(g3d_particle, g3d_data.get_g3d_particles_near(g3d_particle.get_position(), smooth_distance), color_data)
if not color is None:
smooth_color_data[g3d_particle.get_hom_name(), g3d_particle.get_ref_locus()] = color
color_data = smooth_color_data
# output
sys.stderr.write("[M::" + __name__ + "] writing " + str(len(color_data)) + " colors (" + str(round(100.0 * len(color_data) / g3d_data.num_g3d_particles(), 2)) + "%)\n")
for hom_name, ref_locus in sorted(color_data.keys()):
sys.stdout.write("\t".join([hom_name, str(ref_locus), str(color_data[(hom_name, ref_locus)])]) + "\n")
return 0
def rg(argv):
# default parameters
output_prefix = None
reg_file_name = None
reg_list = []
distance_mode = False
# display parameters
disp_num_particles = 100
# read arguments
try:
opts, args = getopt.getopt(argv[1:], "o:r:d")
except getopt.GetoptError as err:
sys.stderr.write("[E::" + __name__ + "] unknown command\n")
return 1
if len(args) == 0:
sys.stderr.write("Usage: dip-c rg [options] <in.3dg>\n")
sys.stderr.write("Options:\n")
sys.stderr.write(" -o STR output prefix [<in.3dg>.]\n")
sys.stderr.write(" -r <in.reg> only analyze certain regions\n")
sys.stderr.write(" (will output two regions if haplotype is \".\")\n")
sys.stderr.write(" -d output pairwise distances instead\n")
sys.stderr.write("Output:\n")
sys.stderr.write(" <prefix><region_name>.rg an N x N matrix of radii of gyration\n")
sys.stderr.write(" <prefix><region_name>.loc a list of N chromosomal loci\n")
return 1
for o, a in opts:
if o == "-o":
output_prefix = a
elif o == "-r":
reg_file_name = a
elif o == "-d":
distance_mode = True
if output_prefix is None:
output_prefix = args[0] + "."
# read 3DG file
g3d_data = file_to_g3d_data(open(args[0], "rb"))
g3d_data.sort_g3d_particles()
g3d_resolution = g3d_data.resolution()
sys.stderr.write("[M::" + __name__ + "] read a 3D structure with " + str(g3d_data.num_g3d_particles()) + " particles at " + str(g3d_resolution) + " bp resolution\n")
# prepare regions to analyze
if reg_file_name is None:
# analyze all homologs
for hom_name in g3d_data.get_hom_names():
ref_name, haplotype = hom_name_to_ref_name_haplotype(hom_name)
reg = Reg(ref_name)
reg.add_haplotype(haplotype)
reg_list.append(reg)
else:
reg_file = gzip.open(reg_file_name, "rb") if reg_file_name.endswith(".gz") else open(reg_file_name, "rb")
reg_list.extend(file_to_reg_list(reg_file))
reg_file.close()
reg_list = [reg for reg in get_phased_regs(reg_list)]
sys.stderr.write("[M::" + __name__ + "] will analyze the following regions:\n")
sys.stderr.write("name\tchr\thap\tstart\tend\n")
for reg in reg_list:
sys.stderr.write(reg.to_name_string() + "\t" + reg.to_string() + "\n")
# calculate Rg matrix for each region
for reg in reg_list:
reg_name = reg.to_name_string()
g3d_list = G3dList()
for g3d_particle in g3d_data.get_g3d_particles_in_reg(reg):
g3d_list.add_g3d_particle(g3d_particle)
g3d_list.sort_g3d_particles()
sys.stderr.write("[M::" + __name__ + "] processing region " + reg_name + ", with " + str(g3d_list.num_g3d_particles()) + " particles\n")
loci_np_array, position_np_array = g3d_list.to_np_arrays()
# write loci file
loci_file_name = output_prefix + reg_name + ".loc"
np.savetxt(loci_file_name, loci_np_array, fmt='%i', delimiter='\t')
# calculate Rg
rg_file_name = output_prefix + reg_name + ".rg"
if distance_mode:
output_matrix = squareform(pdist(position_np_array))
else:
output_matrix = position_np_array_to_rg_np_array(position_np_array, disp_num_particles)
np.savetxt(rg_file_name, output_matrix, delimiter='\t')
return 0
def dist(argv):
# default parameters
# display parameters
disp_num_particles = 100
# read arguments
try:
opts, args = getopt.getopt(argv[1:], "d")
except getopt.GetoptError as err:
sys.stderr.write("[E::" + __name__ + "] unknown command\n")
return 1
if len(args) == 0:
sys.stderr.write("Usage: dip-c dist [options] <in.3dg>\n")
sys.stderr.write("Options:\n")
sys.stderr.write(" -d diploid mode\n")
sys.stderr.write("Output:\n")
sys.stderr.write(
" tab-delimited: homolog (chr if \"-d\"), separation (in bp), #pairs, mean distance, r.m.s. distance\n"
)
return 1
for o, a in opts:
if o == "-o":
output_prefix = a
elif o == "-r":
reg_file_name = a
# read 3DG file
g3d_data = file_to_g3d_data(open(args[0], "rb"))
g3d_data.sort_g3d_particles()
g3d_resolution = g3d_data.resolution()
sys.stderr.write("[M::" + __name__ + "] read a 3D structure with " +
str(g3d_data.num_g3d_particles()) + " particles at " +
str(g3d_resolution) + " bp resolution\n")
# analyze each homolog
for hom_name in g3d_data.get_hom_names():
sys.stderr.write("analyzing " + hom_name + "\n")
loci_np_array, position_np_array = g3d_data.get_g3d_list_from_hom_name(
hom_name).to_np_arrays()
sep_np_array = pdist(loci_np_array)
dist_np_array = pdist(position_np_array)
uniq_seps, uniq_indices = np.unique(sep_np_array, return_inverse=True)
num_seps = len(uniq_seps)
# calculate statistics
nums_pairs = [0] * num_seps
sums = [0.0] * num_seps
sums_sq = [0.0] * num_seps
for i in range(len(sep_np_array)):
sep_index = uniq_indices[i]
nums_pairs[sep_index] += 1
sums[sep_index] += dist_np_array[i]
sums_sq[sep_index] += dist_np_array[i]**2
# print
for i in range(num_seps):
sys.stdout.write("\t".join([
hom_name,
str(int(uniq_seps[i])),
str(nums_pairs[i]),
str(sums[i] / nums_pairs[i]),
str(math.sqrt(sums_sq[i] / nums_pairs[i]))
]) + "\n")
return 0
def color(argv):
# default parameters
color_file_name = None
color_mode = None
max_distance = None
smooth_distance = None
max_separation = None
radial_mode = False
radial_min_num_particles = 10
radial_missing_value = -1.0
radial_max_r = 3.0
radial_bin_r = 0.05
# display parameters
disp_num_particles = 1000
# read arguments
try:
opts, args = getopt.getopt(
argv[1:], "c:n:l:m:L:i:s:S:hd:r:I:CD:R",
["min-num=", "missing=", "max-r=", "bin-size="])
except getopt.GetoptError as err:
sys.stderr.write("[E::" + __name__ + "] unknown command\n")
return 1
if len(args) == 0:
sys.stderr.write("Usage: dip-c color [options] <in.3dg>\n")
sys.stderr.write("Options:\n")
sys.stderr.write(
" -c <color.txt> color by a list of locus-color pairs (tab-delimited: chr, locus, color)\n"
)
sys.stderr.write(
" -n <chr.txt> color by chromosome name (one chromosome per line)\n"
)
sys.stderr.write(
" -l <chr.len> color by locus divided by chromosome length (tab-delimited: chr, len)\n"
)
sys.stderr.write(
" -L <chr.cen> color by arm locus divided by arm length (tab-delimited: chr, len, center of centromere)\n"
)
sys.stderr.write(
" -h color by distance to homologous locus\n\n")
sys.stderr.write(
" -i FLOAT color by percentage of intra-homologous neighbors within a given distance\n"
)
sys.stderr.write(
" -I FLOAT color by number of intra-homologous neighbors within a given distance\n"
)
sys.stderr.write(
" -S INT (with \"-i\" or \"-I\") max separation (bp) for intra-homologous neighbors\n\n"
)
sys.stderr.write(
" -d FLOAT color by homolog diversity within a given distance\n"
)
sys.stderr.write(
" -r FLOAT color by homolog richness within a given distance\n\n"
)
sys.stderr.write(
" -C color by distance to the nuclear center of mass\n"
)
sys.stderr.write(
" -D <in.leg> color by distance to a given locus (only the first line of the LEG file will be used)\n\n"
)
sys.stderr.write(
" -s FLOAT smooth color by averaging over a ball\n\n")
sys.stderr.write(
" -R special: output average color for different radial distances (normalized to 1.0)\n"
)
sys.stderr.write(
" --min-num=INT (with \"-R\") min number of particles per bin ["
+ str(radial_min_num_particles) + "]\n")
sys.stderr.write(
" --missing=FLOAT (with \"-R\") output value when \"--min-num\" is not met ["
+ str(radial_missing_value) + "]\n")
sys.stderr.write(
" --max-r=FLOAT (with \"-R\") max radial distance [" +
str(radial_max_r) + "]\n")
sys.stderr.write(
" --bin-size=FLOAT (with \"-R\") bin size of radial distances ["
+ str(radial_bin_r) + "]\n\n")
sys.stderr.write("Output:\n")
sys.stderr.write(" tab-delimited: homolog, locus, color\n")
sys.stderr.write(
" (with \"-R\") tab-delimited: radial distance, average color, #particles\n"
)
return 1
num_color_schemes = 0
for o, a in opts:
if o == "-i" or o == "-I" or o == "-d" or o == "-r":
num_color_schemes += 1
color_mode = o[1:]
max_distance = float(a)
elif o == "-s":
smooth_distance = float(a)
elif o == "-S":
max_separation = int(a)
elif o == "--min-num":
radial_min_num_particles = int(a)
elif o == "--missing":
radial_missing_value = float(a)
elif o == "--max-r":
radial_max_r = float(a)
elif o == "--bin-size":
radial_bin_r = float(a)
elif o == "-R":
radial_mode = True
else:
num_color_schemes += 1
color_mode = o[1:]
if a != "":
color_file_name = a
if not max_separation is None and color_mode != "i":
sys.stderr.write("[E::" + __name__ +
"] \"-S\" must be used with \"-i\"\n")
return 1
if num_color_schemes != 1:
sys.stderr.write("[E::" + __name__ +
"] exactly one color scheme is needed\n")
return 1
# read 3DG file
g3d_data = file_to_g3d_data(open(args[0], "rb"))
g3d_data.sort_g3d_particles()
g3d_resolution = g3d_data.resolution()
sys.stderr.write(
"[M::" + __name__ + "] read a 3D structure with " +
str(g3d_data.num_g3d_particles()) + " particles at " +
("N.A." if g3d_resolution is None else str(g3d_resolution)) +
" bp resolution\n")
# open color file
if not color_file_name is None:
color_file = open(color_file_name, "rb")
# prepare
if color_mode is None:
pass
elif color_mode == "c":
ref_name_ref_locus_colors = {}
for color_file_line in color_file:
ref_name, ref_locus, color = color_file_line.strip().split("\t")
ref_locus = int(ref_locus)
color = float(color)
ref_name_ref_locus_colors[(ref_name, ref_locus)] = color
elif color_mode == "n":
ref_name_colors = {}
color_counter = 0
for color_file_line in color_file:
color_counter += 1
ref_name = color_file_line.strip()
ref_name_colors[ref_name] = color_counter
elif color_mode == "l":
ref_lens = {}
for color_file_line in color_file:
ref_name, ref_len = color_file_line.strip().split("\t")
ref_len = int(ref_len)
ref_lens[ref_name] = ref_len
elif color_mode == "L":
ref_lens = {}
ref_cens = {}
for color_file_line in color_file:
ref_name, ref_len, ref_cen = color_file_line.strip().split("\t")
ref_len = int(ref_len)
ref_cen = int(ref_cen)
ref_lens[ref_name] = ref_len
ref_cens[ref_name] = ref_cen
elif color_mode == "i" or color_mode == "I" or color_mode == "d" or color_mode == "r":
g3d_data.prepare_nearby()
elif color_mode == "C":
hom_names, loci_np_array, position_np_array = g3d_data.to_np_arrays()
ref_pos = np.mean(position_np_array, axis=0)
sys.stderr.write("[M::" + __name__ +
"] reference point (center of mass) is at (" +
", ".join(map(str, ref_pos)) + ")\n")
elif color_mode == "D":
# fine reference point position
ref_leg = string_to_leg(color_file.readline().strip())
g3d_data.prepare_interpolate()
is_out, ref_pos = g3d_data.interpolate_leg(ref_leg)
sys.stderr.write("[M::" + __name__ + "] reference point (" +
ref_leg.to_string() + ") is at (" +
", ".join(map(str, ref_pos)) + ")\n")
# calculate colors for each particle
color_data = {}
atom_id = 0
for g3d_particle in g3d_data.get_g3d_particles():
atom_id += 1
if atom_id % disp_num_particles == 0:
sys.stderr.write(
"[M::" + __name__ + "] analyzed " + str(atom_id) +
" particles (" +
str(round(100.0 * atom_id / g3d_data.num_g3d_particles(), 2)) +
"%)\n")
# color
if color_mode == "c":
try:
color = ref_name_ref_locus_colors[(
g3d_particle.get_ref_name(), g3d_particle.get_ref_locus())]
except KeyError:
continue
elif color_mode == "n":
try:
color = ref_name_colors[g3d_particle.get_ref_name()]
except KeyError:
continue
elif color_mode == "l":
try:
color = float(g3d_particle.get_ref_locus()) / ref_lens[
g3d_particle.get_ref_name()]
except KeyError:
continue
elif color_mode == "L":
try:
arm_locus = g3d_particle.get_ref_locus() - ref_cens[
g3d_particle.get_ref_name()]
if arm_locus > 0:
arm_len = ref_lens[g3d_particle.get_ref_name()] - ref_cens[
g3d_particle.get_ref_name()]
else:
arm_len = ref_cens[g3d_particle.get_ref_name()]
color = float(abs(arm_locus)) / arm_len
except KeyError:
continue
elif color_mode == "i":
color = intra_hom_fraction(
g3d_particle,
g3d_data.get_g3d_particles_near(g3d_particle.get_position(),
max_distance), max_separation)
if color is None:
continue
elif color_mode == "I":
color = intra_hom_count(
g3d_particle,
g3d_data.get_g3d_particles_near(g3d_particle.get_position(),
max_distance), max_separation)
elif color_mode == "h":
homologous_g3d_particle = g3d_data.get_g3d_particle_from_hom_name_ref_locus(
homologous_hom_name(g3d_particle.get_hom_name()),
g3d_particle.get_ref_locus())
if homologous_g3d_particle is None:
continue
color = math.sqrt(
(g3d_particle.get_x() - homologous_g3d_particle.get_x())**2 +
(g3d_particle.get_y() - homologous_g3d_particle.get_y())**2 +
(g3d_particle.get_z() - homologous_g3d_particle.get_z())**2)
elif color_mode == "d":
color = hom_diversity(
g3d_data.get_g3d_particles_near(g3d_particle.get_position(),
max_distance))
elif color_mode == "r":
color = hom_richness(
g3d_data.get_g3d_particles_near(g3d_particle.get_position(),
max_distance))
elif color_mode == "C" or color_mode == "D":
color = math.sqrt((g3d_particle.get_x() - ref_pos[0])**2 +
(g3d_particle.get_y() - ref_pos[1])**2 +
(g3d_particle.get_z() - ref_pos[2])**2)
#sys.stderr.write(str(color) + "\n")
color_data[g3d_particle.get_hom_name(),
g3d_particle.get_ref_locus()] = color
# smoothing
if not smooth_distance is None:
g3d_data.prepare_nearby()
smooth_color_data = {}
atom_id = 0
for g3d_particle in g3d_data.get_g3d_particles():
atom_id += 1
if atom_id % disp_num_particles == 0:
sys.stderr.write(
"[M::" + __name__ + "] smoothed " + str(atom_id) +
" particles (" + str(
round(100.0 * atom_id /
g3d_data.num_g3d_particles(), 2)) + "%)\n")
color = smooth_color(
g3d_particle,
g3d_data.get_g3d_particles_near(g3d_particle.get_position(),
smooth_distance), color_data)
if not color is None:
smooth_color_data[g3d_particle.get_hom_name(),
g3d_particle.get_ref_locus()] = color
color_data = smooth_color_data
# radial
if radial_mode:
num_radial_bins = int(radial_max_r / radial_bin_r) + 1
radial_color_sums = [0.0] * num_radial_bins
radial_color_nums = [0] * num_radial_bins
# calculate center of mass, and normalization factor
hom_names, loci_np_array, position_np_array = g3d_data.to_np_arrays()
ref_pos = np.mean(position_np_array, axis=0)
mean_radial = np.mean(np.sum((position_np_array - ref_pos)**2,
axis=-1)**0.5,
axis=0)
sys.stderr.write("[M::" + __name__ +
"] radial mode: average radial distance = " +
str(mean_radial) +
", which will be normalize to 1.0\n")
# examine each particle
for g3d_particle in g3d_data.get_g3d_particles():
atom_id += 1
if atom_id % disp_num_particles == 0:
sys.stderr.write(
"[M::" + __name__ + "] radial mode for " + str(atom_id) +
" particles (" + str(
round(100.0 * atom_id /
g3d_data.num_g3d_particles(), 2)) + "%)\n")
if (g3d_particle.get_hom_name(),
g3d_particle.get_ref_locus()) not in color_data:
continue
color = color_data[g3d_particle.get_hom_name(),
g3d_particle.get_ref_locus()]
radial = math.sqrt(
(g3d_particle.get_x() - ref_pos[0])**2 +
(g3d_particle.get_y() - ref_pos[1])**2 +
(g3d_particle.get_z() - ref_pos[2])**2) / mean_radial
radial_bin_id = int(radial / radial_bin_r + 0.5)
#sys.stderr.write(str(radial)+", " + str(radial_bin_id) + "=" + str(radial_bin_id*radial_bin_r)+ ", "+ str(color)+"\n")
if radial_bin_id >= num_radial_bins:
continue # out of bound, skip
radial_color_sums[radial_bin_id] += color
radial_color_nums[radial_bin_id] += 1
# output
sys.stderr.write("[M::" + __name__ + "] writing radial mode output\n")
for radial_bin_id in range(num_radial_bins):
if radial_color_nums[radial_bin_id] < radial_min_num_particles:
output_value = radial_missing_value
else:
output_value = radial_color_sums[
radial_bin_id] / radial_color_nums[radial_bin_id]
sys.stdout.write("\t".join([
str(radial_bin_id * radial_bin_r),
str(output_value),
str(radial_color_nums[radial_bin_id])
]) + "\n")
return 0
# output
sys.stderr.write(
"[M::" + __name__ + "] writing " + str(len(color_data)) + " colors (" +
str(round(100.0 * len(color_data) / g3d_data.num_g3d_particles(), 2)) +
"%)\n")
for hom_name, ref_locus in sorted(color_data.keys()):
sys.stdout.write("\t".join(
[hom_name,
str(ref_locus),
str(color_data[(hom_name, ref_locus)])]) + "\n")
return 0
def con3(argv):
# default parameters
max_distance = 3.0
matrix_mode = False
chr_len_file_name = None
matrix_bin_size = 1000000
merge_haplotypes = False
info_mode = False
# read arguments
try:
opts, args = getopt.getopt(argv[1:], "d:m:b:Hi")
except getopt.GetoptError as err:
sys.stderr.write("[E::" + __name__ + "] unknown command\n")
return 1
if len(args) == 0:
sys.stderr.write("Usage: dip-c con3 [options] <in.3dg>\n")
sys.stderr.write("Options:\n")
sys.stderr.write(
" -d FLOAT max distance for generating a contact [" +
str(max_distance) + "]\n")
sys.stderr.write(
" -m <chr.len> output a matrix of binned counts based on chromosome lengths (tab-delimited: chr, len)\n"
)
sys.stderr.write(
" -b INT bin size (bp) for \"-m\" (bins are centered around multiples of bin size) ["
+ str(matrix_bin_size) + "]\n")
sys.stderr.write(
" -H merge the two haplotypes (for \"-m\")\n")
sys.stderr.write(
" -i output bin info (tab-delimited: homolog or chr if \"-H\", bin center) instead (for \"-m\")\n"
)
return 1
num_color_schemes = 0
for o, a in opts:
if o == "-d":
max_distance = float(a)
elif o == "-m":
matrix_mode = True
chr_len_file_name = a
elif o == "-b":
matrix_bin_size = int(a)
elif o == "-H":
merge_haplotypes = True
elif o == "-i":
info_mode = True
# read 3DG file
if not info_mode:
g3d_data = file_to_g3d_data(open(args[0], "rb"))
g3d_data.sort_g3d_particles()
g3d_resolution = g3d_data.resolution()
sys.stderr.write(
"[M::" + __name__ + "] read a 3D structure with " +
str(g3d_data.num_g3d_particles()) + " particles at " +
("N.A." if g3d_resolution is None else str(g3d_resolution)) +
" bp resolution\n")
# matrix mode
if matrix_mode:
# read chromosome lengths
hom_lens = {}
hom_bin_lens = {}
hom_offsets = {}
matrix_size = 0
chr_len_file = open(chr_len_file_name, "rb")
for chr_len_file_line in chr_len_file:
ref_name, ref_len = chr_len_file_line.strip().split("\t")
ref_len = int(ref_len)
for haplotype in ([Haplotypes.paternal] if merge_haplotypes else
[Haplotypes.paternal, Haplotypes.maternal]):
hom_name = ref_name_haplotype_to_hom_name(
(ref_name, haplotype))
hom_bin_len = int(round(float(ref_len) / matrix_bin_size)) + 1
hom_lens[hom_name] = ref_len
hom_bin_lens[hom_name] = hom_bin_len
hom_offsets[hom_name] = matrix_size
matrix_size += hom_bin_len
if info_mode:
for bin_id in range(hom_bin_len):
sys.stdout.write("\t".join(
[(ref_name if merge_haplotypes else hom_name),
str(bin_id * matrix_bin_size)]) + "\n")
# generate matrix
if not info_mode:
matrix_data = g3d_data_to_matrix(g3d_data, max_distance,
hom_offsets, matrix_bin_size,
matrix_size, merge_haplotypes)
np.savetxt(sys.stdout, matrix_data, fmt='%i', delimiter='\t')
else:
if not info_mode:
con_data = g3d_data_to_con_data(g3d_data, max_distance)
con_data.sort_cons()
sys.stderr.write("[M::" + __name__ + "] writing output for " +
str(con_data.num_cons()) + " contacts (" + str(
round(
100.0 * con_data.num_intra_chr() /
con_data.num_cons(), 2)) +
"% intra-chromosomal, " + str(
round(
100.0 * con_data.num_phased_legs() /
con_data.num_cons() / 2, 2)) +
"% legs phased)\n")
sys.stdout.write(con_data.to_string() + "\n")
return 0
def pd(argv):
# default parameters
leg_file_1_name = None
leg_file_2_name = None
# read arguments
try:
opts, args = getopt.getopt(argv[1:], "1:2:")
except getopt.GetoptError as err:
sys.stderr.write("[E::" + __name__ + "] unknown command\n")
return 1
if len(args) == 0:
sys.stderr.write(
"Usage: dip-c pd [options] -1 <in1.leg> [-2 <in2.leg>] <in.3dg>\n")
sys.stderr.write("Options:\n")
sys.stderr.write(" -1 <in1.leg> LEG file (required)\n")
sys.stderr.write(" -2 <in2.leg> LEG file [<in1.leg>]\n")
return 1
for o, a in opts:
if o == "-1":
leg_file_1_name = a
elif o == "-2":
leg_file_2_name = a
if leg_file_1_name is None:
sys.stderr.write("[E::" + __name__ + "] -1 is required\n")
return 1
if leg_file_2_name is None:
leg_file_2_name = leg_file_1_name
# read 3DG file
g3d_data = file_to_g3d_data(open(args[0], "rb"))
g3d_data.sort_g3d_particles()
g3d_resolution = g3d_data.resolution()
sys.stderr.write(
"[M::" + __name__ + "] read a 3D structure with " +
str(g3d_data.num_g3d_particles()) + " particles at " +
("N.A." if g3d_resolution is None else str(g3d_resolution)) +
" bp resolution\n")
g3d_data.prepare_interpolate()
# convert LEG file to 3DG particles
positions_1 = np.empty([0, 3])
for leg_file_1_line in open(leg_file_1_name, "rb"):
is_out, position = g3d_data.interpolate_leg(
string_to_leg(leg_file_1_line.strip()))
if position is None:
position = np.array([np.nan, np.nan, np.nan])
positions_1 = np.vstack([positions_1, position])
positions_2 = np.empty([0, 3])
for leg_file_2_line in open(leg_file_2_name, "rb"):
is_out, position = g3d_data.interpolate_leg(
string_to_leg(leg_file_2_line.strip()))
if position is None:
position = np.array([np.nan, np.nan, np.nan])
positions_2 = np.vstack([positions_2, position])
# calculate pairwise distances
distances = distance.cdist(positions_1, positions_2)
np.savetxt(sys.stdout, distances, delimiter='\t')
return 0
def clean3(argv):
# default parameters
con_file_name = None
max_clean_distance = 500000
clean_quantile = 0.06
# display parameters
display_quantiles = np.arange(0.0, 1.01, 0.01)
# read arguments
try:
opts, args = getopt.getopt(argv[1:], "c:d:q:")
except getopt.GetoptError as err:
sys.stderr.write("[E::" + __name__ + "] unknown command\n")
return 1
if len(args) == 0:
sys.stderr.write(
"Usage: dip-c clean3 [options] -c <in.con> <in.3dg>\n")
sys.stderr.write("Options:\n")
sys.stderr.write(
" -c <in.con> contact file for cleaning (required)\n")
sys.stderr.write(
" -d INT max distance (bp) from a contact leg to a 3D genome particle ["
+ str(max_clean_distance) + "]\n")
sys.stderr.write(" -q FLOAT quantile of particles to remove [" +
str(clean_quantile) + "]\n")
return 1
for o, a in opts:
if o == "-c":
con_file_name = a
elif o == "-d":
max_clean_distance = int(a)
elif o == "-q":
clean_quantile = float(a)
if con_file_name is None:
sys.stderr.write("[E::" + __name__ + "] -c is required\n")
return 1
# read 3DG file
g3d_data = file_to_g3d_data(open(args[0], "rb"))
g3d_data.sort_g3d_particles()
g3d_resolution = g3d_data.resolution()
sys.stderr.write(
"[M::" + __name__ + "] read a 3D structure with " +
str(g3d_data.num_g3d_particles()) + " particles at " +
("N.A." if g3d_resolution is None else str(g3d_resolution)) +
" bp resolution\n")
# read legs from CON file
con_file = gzip.open(con_file_name,
"rb") if con_file_name.endswith(".gz") else open(
con_file_name, "rb")
con_data = file_to_con_data(con_file)
sys.stderr.write(
"[M::" + __name__ + "] read " + str(con_data.num_cons()) +
" contacts (" +
str(round(100.0 * con_data.num_intra_chr() / con_data.num_cons(), 2)) +
"% intra-chromosomal, " + str(
round(100.0 * con_data.num_phased_legs() / con_data.num_cons() /
2, 2)) + "% legs phased)\n")
leg_data = LegData()
leg_data.add_con_data(con_data)
leg_data.sort_phased_legs()
sys.stderr.write("[M::" + __name__ + "] sorted " +
str(leg_data.num_legs()) + " legs\n")
# find cut-off
leg_counts = g3d_data.leg_counts(leg_data, max_clean_distance)
sys.stderr.write("[M::" + __name__ + "] statistics:\n")
sys.stderr.write("quantile\t#legs\n")
for display_quantile in display_quantiles:
sys.stderr.write(
str(display_quantile) + "\t" + str(
int(
round(np.percentile(leg_counts, display_quantile *
100.0), 0))) + "\n")
min_leg_count = int(
math.ceil(np.percentile(leg_counts, clean_quantile * 100.0)))
sys.stderr.write("[M::" + __name__ + "] min leg count: " +
str(min_leg_count) + "\n")
# clean
g3d_data.clean_leg_poor(leg_data, max_clean_distance, min_leg_count)
leg_counts = g3d_data.leg_counts(leg_data, max_clean_distance)
g3d_data.sort_g3d_particles()
sys.stderr.write("[M::" + __name__ + "] writing output for " +
str(g3d_data.num_g3d_particles()) + " particles\n")
sys.stdout.write(g3d_data.to_string() + "\n")
return 0