days = ['B','D2','D4','D6','D8','ES']
struc_times = [ 0, 4, 8, 12, 16, 20]
struc_map = {}
real_map = {}
real_o_e = {}
struc_o_e = {}
real_pearson = {}
struc_pearson = {}
real_vec = {}
struc_vec = {}
for chro in chros:
for day in days:
print(str(chro),str(day))
real_map[day] = ut.loadConstraintAsMat("../Real_Data/iPluripotent/day_"+str(day)+"_rep_1_chro_"+str(chro))
real_map_torch = torch.from_numpy(real_map[day])
real_map_torch = real_map_torch.unsqueeze(0).unsqueeze(0)
resized_real_map = torch.nn.functional.avg_pool2d(real_map_torch, kernel_size=2)
resized_real_map = resized_real_map.squeeze()
real_map[day] = resized_real_map.numpy()
struc = np.load("../Generated_Structures/ipsc_full_rep_1_eta_1000_alpha_0.6_lr_0.0001_epoch_400_res_50000_step_21_chro_"+str(chro)+".npy")
for struc_time in struc_times:
print(str(chro), str(struc_time))
struc_map[struc_time] = ut.struc2contacts(struc[struc_time])
struc_map_torch = torch.from_numpy(struc_map[struc_time])
struc_map_torch = struc_map_torch.unsqueeze(0).unsqueeze(0)
resized_struc_map = torch.nn.functional.avg_pool2d(struc_map_torch, kernel_size=2)
resized_struc_map = resized_struc_map.squeeze()
from sklearn.decomposition import PCA
import sys
import numpy as np
import numpy.ma as ma
import matplotlib.pyplot as plt
import pdb
sys.path.insert(0, "../")
from Utils import util as ut
chro = "13"
struc = np.load(
"../Generated_Structures/ipsc_missing_2_rep_1_eta_1000_alpha_0.6_lr_0.0001_epoch_400_res_50000_step_21_chro_"
+ str(chro) + ".npy")
real_map = ut.loadConstraintAsMat(
"../Real_Data/iPluripotent/day_D2_rep_1_chro_" + str(chro))
struc_map = ut.struc2contacts(struc[4])
struc_map = np.clip(struc_map, 0, 10)
real_map = np.clip(real_map, 0, 30)
real_pear = ma.corrcoef(ma.masked_invalid(real_map))
struc_pear = ma.corrcoef(ma.masked_invalid(struc_map))
pca_real = PCA(n_components=1)
pca_struc = PCA(n_components=1)
ab_real = pca_real.fit_transform(real_pear)
ab_struc = pca_struc.fit_transform(struc_pear)
real_vec = np.squeeze(ab_real)
struc_vec = np.squeeze(ab_struc)
fig, ax = plt.subplots(3, 2)
ax[0, 0].imshow(np.clip(struc_map, 0, 10), cmap="Reds")
fig, ax = plt.subplots(ncols=3, nrows=2)
fig.suptitle("Chro " + str(chro))
for r, rep in enumerate(reps):
FULL_STRUC_STRING = "Generated_Structures/cardio_full_rep_" + str(
rep
) + "_eta_1000_alpha_0.6_lr_0.0001_epoch_400_res_1_step_15_chro_" + str(
chro) + ".npy"
MIS_STRUC_STRING = "Generated_Structures/cardio_missing_2_rep_" + str(
rep
) + "_eta_1000_alpha_0.6_lr_0.0001_epoch_400_res_1_step_15_chro_" + str(
chro) + ".npy"
CONTACT_STRING = "Real_Data/Cardiomyocyte/RUES2/By_Chros/*_MES_Rep" + str(
rep) + "_500KB_" + str(chro)
CONTACT_STRING = glob.glob(CONTACT_STRING)[0]
mat_contacts[r] = ut.loadConstraintAsMat(CONTACT_STRING, res=1)
mat_mis_struc[r] = ut.loadStrucAtTimeAsMat(MIS_STRUC_STRING, time)
mat_full_struc[r] = ut.loadStrucAtTimeAsMat(FULL_STRUC_STRING, time)
for r, rep in enumerate(reps):
ax[r, 0].set_ylabel("Rep " + str(rep))
ax[r, 0].imshow(np.clip(mat_contacts[r], 0, 30), cmap="Reds")
ax[r, 1].imshow(np.clip(mat_mis_struc[r], 0, 10), cmap="Reds")
ax[r, 2].imshow(np.clip(mat_full_struc[r], 0, 10), cmap="Reds")
ax[1, 0].set_xlabel("Hi-C")
ax[1, 1].set_xlabel("Recon")
ax[1, 2].set_xlabel("Interp")
print("CHRO" + str(chro))
print(spearmanr(mat_contacts[0], mat_contacts[0], axis=None))
print(spearmanr(mat_contacts[0], mat_full_struc[0], axis=None))
print(spearmanr(mat_contacts[0], mat_mis_struc[0], axis=None))
mat_contacts = {}
mat_mis_struc = {}
mat_full_struc = {}
rep = 1
FULL_STRUC_STRING = "Generated_Structures/ipsc_full_rep_" + str(
rep) + "_eta_" + str(eta) + "_alpha_" + str(alpha) + "_lr_" + str(lr)
FULL_STRUC_STRING += "_epoch_" + str(epoch) + "_res_" + str(
res) + "_step_" + str(step) + "_chro_" + str(chro) + ".npy"
for t, (time, day) in enumerate(
zip([0, 4, 8, 12, 16, 20], ['B', 'D2', 'D4', 'D6', 'D8', 'ES'])):
mat_full_struc[t] = ut.loadStrucAtTimeAsMat(FULL_STRUC_STRING, time)
CONTACT_STRING = "Real_Data/iPluripotent/day_" + str(
day) + "_rep_" + str(rep) + "_chro_" + str(chro)
mat_contacts[t] = ut.loadConstraintAsMat(CONTACT_STRING)
for d, day in enumerate(['B', 'D2', 'D4', 'D6', 'D8', 'ES']):
for t, time in enumerate([0, 4, 8, 12, 16, 20]):
print(
str(day) + "/" + str(time) + ":" + str(
spearmanr(mat_full_struc[t], mat_contacts[d], axis=None)
[0]))
fig, ax = plt.subplots(2, 6, gridspec_kw={'wspace': 0.0, 'hspace': 0.0})
for t, time in enumerate([0, 4, 8, 12, 16, 20]):
ax[0, t].imshow(np.clip(mat_full_struc[t], 0, 10), cmap="PuBuGn")
ax[1, t].imshow(np.clip(mat_contacts[t], 0, 30), cmap="YlOrRd")
ax[0, t].set_xticks([])
ax[1, t].set_xticks([])
ax[0, t].set_yticks([])
#This script will provide the HiC_Tool Tads for the orignal Contact maps import pdb import numpy as np import sys import matplotlib.pyplot as plt sys.path.insert(0,"../") from Utils import util as ut TIME = 4 line=sys.argv[1] day=sys.argv[2] rep=sys.argv[3] chro=sys.argv[4] out_file=sys.argv[5] #CONTACT_STRING = "../Real_Data/iPluripotent/day_D2_rep_1_chro_15" CONTACT_STRING = "../Real_Data/"+str(line)+"/day_"+str(day)+"_rep_"+str(rep)+"_chro_"+str(chro) mat = ut.loadConstraintAsMat(CONTACT_STRING) np.savetxt(out_file, mat, fmt='%0.2f', delimiter=' ')
#This file contains code for extracting AB compartments from all time points in a structure import time import numpy as np import numpy.ma as ma import matplotlib.pyplot as plt import pdb from sklearn.decomposition import PCA import matplotlib.pyplot as plt import sys sys.path.insert(0, "../") from Utils import util as ut import sys hic_file = sys.argv[1] out_file = sys.argv[2] start_time = time.time() mat = ut.loadConstraintAsMat(hic_file) mat = np.clip(mat, 0, 30) pear = ma.corrcoef(ma.masked_invalid(mat)) pca = PCA(n_components=1) AB = pca.fit_transform(pear) AB_VEC = np.squeeze(AB) np.save(out_file, AB_VEC)
import pdb
from scipy.stats import pearsonr
from scipy.stats import spearmanr
import numpy as np
import matplotlib.pyplot as plt
from Utils import util as ut
fig, ax = plt.subplots(6, 6)
for day, time in zip([0, 1, 2, 3, 4, 5], [0, 4, 8, 12, 16, 20]):
real1 = 1 / ut.loadConstraintAsMat(
"Synthetic_Data/Synthetic_Contact_Maps/struc1_" + str(day) + ".txt",
res=100000)
real2 = 1 / ut.loadConstraintAsMat(
"Synthetic_Data/Synthetic_Contact_Maps/struc2_" + str(day) + ".txt",
res=100000)
full1 = 1 / ut.loadStrucAtTimeAsMat(
"Generated_Structures/synthetic_full_rep_1_eta_10_alpha_1.0_lr_0.01_epoch_1000_res_100000_step_21_chro_all.npy",
time)
full2 = 1 / ut.loadStrucAtTimeAsMat(
"Generated_Structures/synthetic_full_rep_2_eta_10_alpha_1.0_lr_0.01_epoch_1000_res_100000_step_21_chro_all.npy",
time)
if day == 0 or day == 5:
struc1 = 1 / ut.loadStrucAtTimeAsMat(
"Generated_Structures/synthetic_full_rep_1_eta_10_alpha_1.0_lr_0.01_epoch_1000_res_100000_step_21_chro_all.npy",
time)
struc2 = 1 / ut.loadStrucAtTimeAsMat(
"Generated_Structures/synthetic_full_rep_2_eta_10_alpha_1.0_lr_0.01_epoch_1000_res_100000_step_21_chro_all.npy",
time)
else:
struc1 = 1 / ut.loadStrucAtTimeAsMat(
"Generated_Structures/synthetic_missing_" + str(day) +
"_rep_1_eta_10_alpha_1.0_lr_0.01_epoch_1000_res_100000_step_21_chro_all.npy",