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golobor/hela-pairing.ipynb

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hela-pairing.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import types\n",
"import pathlib\n",
"import re\n",
"import io\n",
"\n",
"\n",
"import numpy as np\n",
"import pandas as pd\n",
"\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib as mpl\n",
"\n",
"plt.style.use('seaborn-talk')\n",
"\n",
"import numba\n",
"\n",
"import pairlib\n",
"import pairlib.scalings\n",
"\n",
"import bioframe\n",
"\n",
"import cooler\n",
"import cooltools\n",
"# import cooltools.expected\n",
"# import cooltools.lib.plotting\n",
"\n",
"\n",
"\n",
"import polychrom\n",
"# import polychrom.polymerutils\n",
"# import polychrom.polymer_analyses\n",
"\n",
"import wiggin\n",
"import wiggin.polychrom_contrib\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"# fig, subplots =plt.subplot_mosaic('''\n",
"# A\n",
"# A\n",
"# A\n",
"# A\n",
"# A\n",
"# .\n",
"# B\n",
"# .\n",
"# C\n",
"# C\n",
"# .\n",
"# D\n",
"# D\n",
"# ''',\n",
"# figsize=(4,12))\n",
"# for label, sc in scs.items():\n",
"\n",
"# xs, ys = sc\n",
"# norm = pairlib.scalings.norm_scaling_factor(*scs[(label[0],'cis')], anchor= 3e3)\n",
" \n",
"# plt.subplot(subplots['A'])\n",
"# plt.loglog(\n",
"# xs, ys / norm,\n",
"# label='_'.join(label)\n",
"# )\n",
" \n",
"# plt.subplot(subplots['B'])\n",
"# plt.semilogx(np.sqrt(xs[:-1]*xs[1:]), \n",
"# np.diff(np.log10(ys))/np.diff(np.log10(xs)))\n",
" \n",
"\n",
"# plt.subplot(subplots['A']) \n",
"# plt.gca().set(\n",
"# aspect=1.0,\n",
"# title='P(s)'\n",
"# )\n",
"# plt.grid(lw=0.5, color='gray')\n",
"# plt.legend()\n",
"\n",
"# plt.subplot(subplots['B']) \n",
"# plt.gca().set(\n",
"# ylim=(-2,0),\n",
"# title='P(s) slopes'\n",
"# )\n",
"# plt.grid(lw=0.5, color='gray')\n",
"\n",
"\n",
" \n",
"# plt.subplot(subplots['C'])\n",
"# for sample in ['WT', 'Nipbl', 'Sororin']:\n",
"# xs = scs[(sample, 'cis')][0]\n",
"# ys_trans = scs[(sample, 'trans')][1]\n",
"# ys_cis = scs[(sample, 'cis')][1]\n",
"# plt.loglog(\n",
"# scs[(sample, 'cis')][0], \n",
"# ys_trans / ys_cis,\n",
"# label=sample\n",
"# )\n",
"# plt.legend(loc='lower right')\n",
"\n",
"# plt.gca().set(\n",
"# ylim=(3e-3,1.2),\n",
"# title='trans/cis ratio'\n",
"# )\n",
"# plt.grid(lw=0.5, color='gray')\n",
"\n",
"\n",
" \n",
"# plt.subplot(subplots['D'])\n",
"# for sample in ['WT', 'Nipbl', 'Sororin']:\n",
"# xs = scs[(sample, 'cis')][0]\n",
"# ys_trans = scs[(sample, 'trans')][1]\n",
"# ys_cis = scs[(sample, 'cis')][1]\n",
"# plt.semilogx(\n",
"# np.sqrt(xs[:-1]*xs[1:]), \n",
"# np.diff(np.log10(ys_trans))/np.diff(np.log10(xs))\n",
"# - np.diff(np.log10(ys_cis))/np.diff(np.log10(xs)),\n",
"# label=sample\n",
"# )\n",
"# # plt.legend()\n",
"# plt.grid(lw=0.5, color='gray')\n",
"# plt.gca().set(\n",
"# title='trans/cis ratio slope'\n",
"# )\n",
"# plt.axhline(1.0, lw=0.5, color='gray')\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Data vs Simulations"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"dfolder = '/groups/goloborodko/projects/lab/sisterChromatids2020/static_loops_translinks/phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp20000m_sigma0m_loopSize500m_gapSize166m_modif/0'"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"ename": "AttributeError",
"evalue": "module 'wiggin' has no attribute 'polychrom_contrib'",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)",
"Input \u001b[0;32mIn [3]\u001b[0m, in \u001b[0;36m<cell line: 2>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mimportlib\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m importlib\u001b[38;5;241m.\u001b[39mreload(\u001b[43mwiggin\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpolychrom_contrib\u001b[49m)\n",
"\u001b[0;31mAttributeError\u001b[0m: module 'wiggin' has no attribute 'polychrom_contrib'"
]
}
],
"source": [
"import importlib\n",
"importlib.reload(wiggin.polychrom_contrib)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"dfolders = [ \n",
" #'/groups/goloborodko/projects/lab/sisterChromatids2020/static_loops_translinks/phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp20000m_sigma0m_loopSize500m_gapSize166m_modif/',\n",
" # '/groups/goloborodko/projects/lab/sisterChromatids2020/static_loops_translinks/phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp20000m_sigma0m_loopSize500m_gapSize300m_modif/',\n",
" # '/groups/goloborodko/projects/lab/sisterChromatids2020/static_loops_translinks/phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp20000m_sigma0m_loopSize500m_gapSize500m_modif/',\n",
" \n",
" \n",
" #'/groups/goloborodko/projects/lab/sisterChromatids2020/trajectory_sisterChrom_spiral_N200000_d0.1_f0.002_delta0_sigma0_colRate0.003_blocks5000_ts100000_err0.01_harmonic_bonds_bondLength1.0_bondWiggleDistance0.05_angle_force_k1.5_quartic_repulsive_trunc1.0' ,\n",
" #'/groups/goloborodko/projects/lab/sisterChromatids2020/trajectory_sisterChrom_spiral_N200000_d0.1_f0.0004_delta0_sigma0_colRate0.003_blocks5000_ts100000_err0.01_harmonic_bonds_bondLength1.0_bondWiggleDistance0.05_angle_force_k1.5_quartic_repulsive_trunc1.0' , \n",
" #'/groups/goloborodko/projects/lab/sisterChromatids2020/trajectory_sisterChrom_spiral_N200000_d0.1_f0.004_delta0_sigma0_colRate0.003_blocks5000_ts100000_err0.01_harmonic_bonds_bondLength1.0_bondWiggleDistance0.05_angle_force_k1.5_quartic_repulsive_trunc1.0' ,\n",
"\n",
" '/groups/goloborodko/projects/lab/sisterChromatids2020/static_loops_translinks/phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize0m_gapSize0m_modif',\n",
" # '/groups/goloborodko/projects/lab/sisterChromatids2020/static_loops_translinks/phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp250m_sigma0m_loopSize0m_gapSize0m_modif',\n",
" \n",
" # '/groups/goloborodko/projects/lab/sisterChromatids2020/static_loops_translinks/phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma500m_loopSize0m_gapSize0m_modif',\n",
" \n",
" '/groups/goloborodko/projects/lab/sisterChromatids2020/static_loops_translinks/phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize500m_gapSize500m_modif',\n",
" \n",
" \n",
" # '/groups/goloborodko/projects/lab/sisterChromatids2020/static_loops_translinks/phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp20000m_sigma0m_loopSize500m_gapSize250m_modif',\n",
"\n",
" # '/groups/goloborodko/projects/lab/sisterChromatids2020/static_loops_translinks/phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize500m_gapSize500m_modif',\n",
" # '/groups/goloborodko/projects/lab/sisterChromatids2020/static_loops_translinks/phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma500m_loopSize500m_gapSize500m_modif',\n",
" # '/groups/goloborodko/projects/lab/sisterChromatids2020/static_loops_translinks/phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp20000m_sigma0m_loopSize500m_gapSize166m_modif',\n",
" \n",
" \n",
" \n",
"\n",
"# phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp10000m_sigma0m_loopSize500m_gapSize250m_modif\n",
"# phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp50000m_sigma0m_loopSize500m_gapSize250m_modif\n",
"# phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp5000m_sigma0m_loopSize500m_gapSize250m_modif\n",
"# phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp30000m_sigma0m_loopSize500m_gapSize250m_modif\n",
"# phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma1500m_loopSize500m_gapSize500m_modif\n",
"# phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma500m_loopSize500m_gapSize500m_modif\n",
"# phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma500m_loopSize0m_gapSize0m_modif\n",
"# phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma1500m_loopSize0m_gapSize0m_modif\n",
"# phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp10000m_sigma0m_loopSize500m_gapSize166m_modif\n",
"# phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp5000m_sigma0m_loopSize500m_gapSize166m_modif\n",
"# phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp50000m_sigma0m_loopSize500m_gapSize166m_modif\n",
"# phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp30000m_sigma0m_loopSize500m_gapSize166m_modif\n",
"# phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp20000m_sigma0m_loopSize0m_gapSize0m_modif\n",
"# phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp250m_sigma0m_loopSize0m_gapSize0m_modif\n",
"# phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize0m_gapSize0m_modif\n",
"\n",
"\n",
"]\n"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"logs\n",
"phantomChains_errTol0.003_colRate0.01_N200000_blocks1000_ts100000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp10000m_sigmaLaplace100m_loopSize0m_gapSize0m\n",
"phantomChains_errTol0.003_colRate0.01_N200000_blocks1000_ts100000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp10000m_sigmaLaplace500m_loopSize0m_gapSize0m\n",
"phantomChains_errTol0.003_colRate0.01_N200000_blocks1000_ts100000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp5000m_sigmaLaplace100m_loopSize0m_gapSize0m\n",
"phantomChains_errTol0.003_colRate0.01_N200000_blocks1000_ts100000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp5000m_sigmaLaplace500m_loopSize0m_gapSize0m\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp10000m_sigma0m_loopSize500m_gapSize166m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp10000m_sigma0m_loopSize500m_gapSize250m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp15000m_sigma0m_loopSize400m_gapSize300m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp15000m_sigma0m_loopSize500m_gapSize200m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp15000m_sigma0m_loopSize500m_gapSize250m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp15000m_sigma0m_loopSize500m_gapSize300m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp15000m_sigma0m_loopSize500m_gapSize400m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp15000m_sigma0m_loopSize600m_gapSize200m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp15000m_sigma0m_loopSize600m_gapSize250m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp15000m_sigma0m_loopSize600m_gapSize300m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp15000m_sigma0m_loopSize600m_gapSize400m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp15000m_sigma0m_loopSize600m_gapSize500m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp15000m_sigma0m_loopSize600m_gapSize600m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp1500m_sigma0m_loopSize400m_gapSize1000m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp1500m_sigma0m_loopSize400m_gapSize700m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp1500m_sigma0m_loopSize400m_gapSize800m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp1500m_sigma0m_loopSize500m_gapSize1000m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp1500m_sigma0m_loopSize500m_gapSize1500m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp1500m_sigma0m_loopSize500m_gapSize800m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp20000m_sigma0m_loopSize0m_gapSize0m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp20000m_sigma0m_loopSize400m_gapSize200m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp20000m_sigma0m_loopSize400m_gapSize300m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp20000m_sigma0m_loopSize400m_gapSize400m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp20000m_sigma0m_loopSize500m_gapSize166m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp20000m_sigma0m_loopSize500m_gapSize200m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp20000m_sigma0m_loopSize500m_gapSize250m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp20000m_sigma0m_loopSize500m_gapSize300m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp20000m_sigma0m_loopSize500m_gapSize400m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp20000m_sigma0m_loopSize500m_gapSize500m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp20000m_sigma0m_loopSize600m_gapSize200m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp20000m_sigma0m_loopSize600m_gapSize250m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp20000m_sigma0m_loopSize600m_gapSize300m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp20000m_sigma0m_loopSize600m_gapSize400m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp20000m_sigma0m_loopSize600m_gapSize500m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp20000m_sigma0m_loopSize600m_gapSize600m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2000m_sigma0m_loopSize400m_gapSize1000m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2000m_sigma0m_loopSize400m_gapSize700m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2000m_sigma0m_loopSize500m_gapSize1250m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2000m_sigma0m_loopSize500m_gapSize1500m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2000m_sigma10m_loopSize500m_gapSize1250m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2000m_sigma5m_loopSize500m_gapSize1250m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp25000m_sigma0m_loopSize500m_gapSize200m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp25000m_sigma0m_loopSize500m_gapSize250m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp25000m_sigma0m_loopSize500m_gapSize300m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp25000m_sigma0m_loopSize500m_gapSize400m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize0m_gapSize0m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize400m_gapSize1000m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize400m_gapSize1200m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize400m_gapSize400m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize400m_gapSize600m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize400m_gapSize700m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize400m_gapSize800m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize500m_gapSize1000m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize500m_gapSize1200m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize500m_gapSize1250m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize500m_gapSize1500m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize500m_gapSize500m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize500m_gapSize800m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize600m_gapSize1000m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize600m_gapSize1200m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize600m_gapSize1400m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize600m_gapSize800m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma10m_loopSize500m_gapSize1250m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma1500m_loopSize0m_gapSize0m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma1500m_loopSize500m_gapSize500m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma500m_loopSize0m_gapSize0m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma500m_loopSize500m_gapSize500m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma5m_loopSize500m_gapSize1250m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp250m_sigma0m_loopSize0m_gapSize0m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp30000m_sigma0m_loopSize500m_gapSize166m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp30000m_sigma0m_loopSize500m_gapSize250m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp3000m_sigma0m_loopSize400m_gapSize1000m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp3000m_sigma0m_loopSize400m_gapSize1200m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp3000m_sigma0m_loopSize400m_gapSize800m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp3000m_sigma0m_loopSize500m_gapSize1000m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp3000m_sigma0m_loopSize500m_gapSize1100m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp3000m_sigma0m_loopSize500m_gapSize1200m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp3000m_sigma0m_loopSize500m_gapSize800m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp3000m_sigma0m_loopSize600m_gapSize1000m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp3000m_sigma0m_loopSize600m_gapSize1200m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp3000m_sigma0m_loopSize600m_gapSize1400m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp3000m_sigma0m_loopSize600m_gapSize800m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp3500m_sigma0m_loopSize500m_gapSize1000m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp3500m_sigma0m_loopSize500m_gapSize1100m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp3500m_sigma0m_loopSize500m_gapSize600m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp3500m_sigma0m_loopSize500m_gapSize800m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp3500m_sigma0m_loopSize600m_gapSize1000m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp3500m_sigma0m_loopSize600m_gapSize1200m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp3500m_sigma0m_loopSize600m_gapSize1400m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp3500m_sigma0m_loopSize600m_gapSize800m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp50000m_sigma0m_loopSize500m_gapSize166m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp50000m_sigma0m_loopSize500m_gapSize250m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp5000m_sigma0m_loopSize500m_gapSize166m_modif\n",
"phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp5000m_sigma0m_loopSize500m_gapSize250m_modif\n"
]
}
],
"source": [
"!ls /groups/goloborodko/projects/lab/sisterChromatids2020/static_loops_translinks/"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"/groups/goloborodko/projects/lab/sisterChromatids2020/static_loops_translinks/phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize0m_gapSize0m_modif/1 ...\n",
"/groups/goloborodko/projects/lab/sisterChromatids2020/static_loops_translinks/phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize0m_gapSize0m_modif/0 ...\n",
"/groups/goloborodko/projects/lab/sisterChromatids2020/static_loops_translinks/phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize0m_gapSize0m_modif/5 ...\n",
"/groups/goloborodko/projects/lab/sisterChromatids2020/static_loops_translinks/phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize0m_gapSize0m_modif/4 ...\n",
"/groups/goloborodko/projects/lab/sisterChromatids2020/static_loops_translinks/phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize0m_gapSize0m_modif/3 ...\n",
"/groups/goloborodko/projects/lab/sisterChromatids2020/static_loops_translinks/phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize0m_gapSize0m_modif/2 ...\n",
"/groups/goloborodko/projects/lab/sisterChromatids2020/static_loops_translinks/phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize0m_gapSize0m_modif/8 ...\n",
"/groups/goloborodko/projects/lab/sisterChromatids2020/static_loops_translinks/phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize0m_gapSize0m_modif/7 ...\n",
"/groups/goloborodko/projects/lab/sisterChromatids2020/static_loops_translinks/phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize0m_gapSize0m_modif/6 ...\n",
"/groups/goloborodko/projects/lab/sisterChromatids2020/static_loops_translinks/phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize0m_gapSize0m_modif/9 ...\n",
"/groups/goloborodko/projects/lab/sisterChromatids2020/static_loops_translinks/phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize500m_gapSize500m_modif/1 ...\n",
"/groups/goloborodko/projects/lab/sisterChromatids2020/static_loops_translinks/phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize500m_gapSize500m_modif/0 ...\n",
"/groups/goloborodko/projects/lab/sisterChromatids2020/static_loops_translinks/phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize500m_gapSize500m_modif/2 ...\n",
"/groups/goloborodko/projects/lab/sisterChromatids2020/static_loops_translinks/phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize500m_gapSize500m_modif/9 ...\n",
"/groups/goloborodko/projects/lab/sisterChromatids2020/static_loops_translinks/phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize500m_gapSize500m_modif/8 ...\n",
"/groups/goloborodko/projects/lab/sisterChromatids2020/static_loops_translinks/phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize500m_gapSize500m_modif/7 ...\n",
"/groups/goloborodko/projects/lab/sisterChromatids2020/static_loops_translinks/phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize500m_gapSize500m_modif/5 ...\n",
"/groups/goloborodko/projects/lab/sisterChromatids2020/static_loops_translinks/phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize500m_gapSize500m_modif/3 ...\n",
"/groups/goloborodko/projects/lab/sisterChromatids2020/static_loops_translinks/phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize500m_gapSize500m_modif/4 ...\n",
"/groups/goloborodko/projects/lab/sisterChromatids2020/static_loops_translinks/phantomChains_errTol0.01_colRate0.003_N400000_blocks5000_ts10000_bondLen1.0_wiggleDist0.05_k1.5_translinksSepExp2500m_sigma0m_loopSize500m_gapSize500m_modif/6 ...\n"
]
}
],
"source": [
"\n",
"# SIGMA = 10\n",
"SIGMA = 2.1\n",
"\n",
"# SIGMA = 10\n",
"#SIGMA = 4.5\n",
"#SIGMA = 2.4\n",
"CR = 1.1\n",
"REPEATS = 10\n",
"\n",
"kwargs = dict(\n",
" chains=[(0,0.5), (0.5,1.0)],\n",
" trans=True,\n",
" bins_decade=None,\n",
" contact_radius=CR\n",
")\n",
"\n",
"\n",
"scs_sim = {}\n",
"for dfolder in dfolders:\n",
" scs_rep = []\n",
" #dfolder_reps = [p for p in pathlib.Path(dfolder).glob('*') if re.match('[\\d]+', p.name)]\n",
" dfolder_reps = [p for p in pathlib.Path(dfolder).glob('*') if re.match('[0-9]+', p.name)]\n",
" if not len(dfolder_reps):\n",
" dfolder_reps = [dfolder]\n",
" for dfolder_rep in dfolder_reps:\n",
" print(dfolder_rep, '...')\n",
" coords = wiggin.polychrom_contrib.fetch_block(dfolder_rep, ind = -1)\n",
"\n",
" sc = wiggin.polychrom_contrib.gaussian_contact_vs_dist(\n",
" coords=coords,\n",
" contact_vs_dist_func=wiggin.polychrom_contrib.contact_vs_dist_multichain,\n",
" random_sigma=SIGMA,\n",
" random_reps=REPEATS,\n",
" **kwargs\n",
" )\n",
" scs_rep.append(sc)\n",
" sc = pd.concat(scs_rep)\n",
"\n",
" key = pathlib.Path(dfolder).name\n",
" scs_sim[key] = sc\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"import matplotlib as mpl\n",
"mpl.rcParams['figure.dpi'] = 150"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/users/anton.goloborodko/src/wiggin/wiggin/polychrom_contrib.py:394: RuntimeWarning: divide by zero encountered in log\n",
" np.log(xs),\n",
"/users/anton.goloborodko/src/wiggin/wiggin/polychrom_contrib.py:395: RuntimeWarning: divide by zero encountered in log\n",
" np.log(xp),\n",
"/users/anton.goloborodko/src/wiggin/wiggin/polychrom_contrib.py:396: RuntimeWarning: divide by zero encountered in log\n",
" np.log(fp),\n",
"/users/anton.goloborodko/src/wiggin/wiggin/polychrom_contrib.py:394: RuntimeWarning: divide by zero encountered in log\n",
" np.log(xs),\n",
"/users/anton.goloborodko/src/wiggin/wiggin/polychrom_contrib.py:395: RuntimeWarning: divide by zero encountered in log\n",
" np.log(xp),\n",
"/users/anton.goloborodko/src/wiggin/wiggin/polychrom_contrib.py:396: RuntimeWarning: divide by zero encountered in log\n",
" np.log(fp),\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 375x900 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"BP_PARTICLE = 200\n",
"SIGMA_SMOOTHING_LOG10 = 0.1\n",
"PAIRING_DIST = 2500 * 200\n",
"XLIM = (3e3, 1e7)\n",
"\n",
"f, axs = plt.subplot_mosaic('''\n",
" A\n",
" A\n",
" A\n",
" A\n",
" A\n",
" A\n",
" .\n",
" B\n",
" B\n",
" ''',\n",
" figsize=(2.5,6))\n",
"\n",
"\n",
"for i, (key, sc) in enumerate(scs_sim.items()):\n",
"\n",
" sc_sim_cis = wiggin.polychrom_contrib.agg_smooth_cvd(sc.query('chain1 == chain2'), \n",
" sigma_log10=SIGMA_SMOOTHING_LOG10)\n",
" sc_sim_trans = wiggin.polychrom_contrib.agg_smooth_cvd(sc.query('chain1 != chain2'), \n",
" sigma_log10=SIGMA_SMOOTHING_LOG10)\n",
"\n",
" xs_sim = sc_sim_cis['dist'].values * BP_PARTICLE\n",
" ys_sim_cis = sc_sim_cis['contact_freq.smoothed'].values\n",
" ys_sim_trans = sc_sim_trans['contact_freq.smoothed'].values\n",
"\n",
" norm_factor_sim = pairlib.scalings.norm_scaling_factor(xs_sim, ys_sim_cis, 3e3)\n",
" ys_sim_cis = ys_sim_cis / norm_factor_sim\n",
" ys_sim_trans = ys_sim_trans / norm_factor_sim \n",
"\n",
"\n",
" ax = axs['A']\n",
" plot_ghost = (len(scs_sim) > 1) and (i==0)\n",
"\n",
" ax.loglog(xs_sim, ys_sim_cis, \n",
" color='gray' if plot_ghost else 'C0', \n",
" alpha=0.5 if plot_ghost else 1.0, \n",
" label=None if plot_ghost else 'cis'\n",
" )\n",
" ax.loglog(xs_sim, ys_sim_trans, \n",
" color='gray' if plot_ghost else 'C1', \n",
" alpha=0.5 if plot_ghost else 1.0, \n",
" label=None if plot_ghost else 'trans'\n",
" )\n",
"\n",
" \n",
" ax = axs['B']\n",
" ax.loglog(xs_sim, ys_sim_trans / ys_sim_cis, \n",
" color='gray' if plot_ghost else 'C1', \n",
" alpha=0.5 if plot_ghost else 1.0, )\n",
"\n",
"\n",
"ax = axs['A']\n",
"ax.set(\n",
" xlim = XLIM,\n",
" ylim = (1e-5, 1e0),\n",
" aspect=1.0,\n",
" ylabel='contact frequency',\n",
" xlabel='genomic distance, bp'\n",
"); \n",
"ax.legend(loc=(1.1,0.1))\n",
"\n",
"\n",
"ax = axs['B']\n",
"ax.set(\n",
" xlim = XLIM,\n",
" ylim = (1e-3, 1.5),\n",
" ylabel='trans / cis',\n",
" xlabel='genomic distance, bp'\n",
"); \n",
"ax.axhline(1, lw=0.5, color='gray')\n",
"\n",
"for ax in axs.values():\n",
" ax.axvline(PAIRING_DIST, lw=1.0, color='gray', ls='--')\n",
" ax.grid(lw=0.5, color='gray')\n",
"\n",
" locmaj = mpl.ticker.LogLocator(base=10.0, subs=(1.0, ), numticks=100)\n",
" locmin = mpl.ticker.LogLocator(base=10.0, subs=np.arange(2, 10) * .1,\n",
" numticks=100)\n",
"\n",
" ax.xaxis.set_major_locator(locmaj)\n",
" ax.xaxis.set_minor_locator(locmin)\n"
]
},
{
"cell_type": "code",
"execution_count": 241,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Data"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"\n",
"RES = 1000\n",
"\n",
"clrs = dict(\n",
"# wt_all = cooler.Cooler('/groups/goloborodko/seqdata/mitterGerlich2020/hg19/scsHic_mcool/G2.WT.all.1000.mcool::/resolutions/' + str(RES)),\n",
" # wt_cis = cooler.Cooler('/groups/goloborodko/seqdata/mitterGerlich2020/hg19/scsHic_mcool/G2.WT.cis.1000.mcool::/resolutions/' + str(RES)),\n",
" wt_trans = cooler.Cooler('/groups/goloborodko/seqdata/mitterGerlich2020/hg19/scsHic_mcool/G2.WT.trans.1000.mcool::/resolutions/' + str(RES)),\n",
" wt_cis = cooler.Cooler('/groups/goloborodko/seqdata/mitterGerlich2020/hg19/scsHic_mcool/G2.WT.cis.1000.mcool::/resolutions/' + str(RES)),\n",
" #wt_trans = cooler.Cooler('/groups/goloborodko/seqdata/mitterGerlich2020/hg19/scsHic_mcool/G2.WT.trans.1000.mcool::/resolutions/' + str(RES)),\n",
"# nipbl_all = cooler.Cooler('/groups/goloborodko/seqdata/mitterGerlich2020/hg19/scsHic_mcool/G2.Nipbl-AID.wAuxin.all.1000.mcool::/resolutions/' + str(RES)),\n",
" # nipbl_cis = cooler.Cooler('/groups/goloborodko/seqdata/mitterGerlich2020/hg19/scsHic_mcool/G2.Nipbl-AID.wAuxin.cis.1000.mcool::/resolutions/' + str(RES)),\n",
" # nipbl_trans = cooler.Cooler('/groups/goloborodko/seqdata/mitterGerlich2020/hg19/scsHic_mcool/G2.Nipbl-AID.wAuxin.trans.1000.mcool::/resolutions/' + str(RES))\n",
")\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"regs = pd.read_table(\n",
" io.StringIO(\n",
"'''\n",
"#chr1\t40000000\t60000000\tchr1\t48974884\t50833910\trandom 20Mb, paired\n",
"#chr1\t48962523\t50809784\tchr1\t48974884\t50833910\tbig tad, no pairing #1\n",
"#chr1\t50815108\t52506689\tchr1\t50833708\t52506175\tmany tads, little pairing\n",
"#chr1\t51326405\t51885487\tchr1\t51330670\t51942315\thighly paired TAD\n",
"#chr1\t60390000\t61340000\tchr1\t61340000\t60390000\thighly paired TAD #2\n",
"#chr1\t63290000\t64090000\tchr1\t61340000\t60390000\thighly paired TAD #3\n",
"#chr1\t57500957\t60640681\tchr1\t59053677\t62083620\tmany TADs, paired\n",
"#chr1\t161700000\t162700000\tchr1\t161700000\t162700000\tbig unpaired TAD\n",
"#chr1\t163349157\t165050295\tchr1\t163375715\t165062518\thuge unpaired TAD\n",
"#chr1\t163301372\t165145864\tchr1\t163265810\t165110302\thuge unpaired TAD, expanded\n",
"#chr1\t174943050\t186271682\tchr1\t174894647\t186305221\tmany TADs #2\n",
"#chr1\t202209609\t205774134\tchr1\t202181691\t205684759\ta bunch of small TADs\n",
"\n",
"\n",
"chr1\t36957679\t37880572\tchr1\t36983439\t37875906\tSA 1, paired\n",
"#chr1\t37895783\t38575276\tchr1\t37886047\t38524973\tSA 2, unpaired\n",
"chr1\t50065779\t50765555\tchr1\t50066184\t50745677\tSA 5, paired\n",
"chr1\t51688445\t52367937\tchr1\t51638142\t52287209\tSA 7, unpaired\n",
"chr1\t55594320\t56378287\tchr1\t55561750\t56361089\tSA 8, unpaired\n",
"chr1\t56387947\t57224500\tchr1\t56382293\t57168902\tSA 9, paired\n",
"chr1\t57187041\t58622915\tchr1\t57193873\t58592289\tSA 10, paired\n",
"chr1\t59184777\t60296019\tchr1\t59166638\t60265394\tSA 11, unpaired\n",
"chr1\t60208617\t60495793\tchr1\t60215449\t60477653\tSA 12, paired\n",
"chr1\t60395905\t61494661\tchr1\t60377765\t61464035\tSA 13, paired\n",
"chr1\t61494660\t62555958\tchr1\t61476520\t62525333\tSA 14, unpaired\n",
"chr1\t63205222\t64141662\tchr1\t63149624\t64098550\tSA 15, paired\n",
"chr1\t64141661\t64678553\tchr1\t64136007\t64660413\tSA 16, unpaired\n",
"chr1\t64641095\t65377761\tchr1\t64635441\t65322163\tSA 17, paired\n",
"chr1\t70221390\t70713291\tchr1\t70194470\t70594140\tSA 18, unpaired\n",
"chr1\t70862422\t71611574\tchr1\t70881618\t71555855\tSA 19, paired\n",
"chr1\t71974665\t74188218\tchr1\t72016950\t74122899\tSA 20, unpaired\n",
"chr1\t75141274\t75786894\tchr1\t75122071\t75736947\tSA 21, paired\n",
"chr1\t76217306\t77646893\tchr1\t76182731\t77658433\tSA 22, paired\n",
"chr1\t77585404\t78353999\tchr1\t77612316\t78334796\tSA 23, unpaired\n",
"chr1\t79364690\t80613742\tchr1\t79280371\t80567273\tSA 24, unpaired\n",
"chr1\t80575891\t82657643\tchr1\t80586197\t82649024\tSA 25, unpaired\n",
"'''\n",
" ),\n",
" names=['chrom1','start1','end1','chrom2','start2','end2', 'name']\n",
")\n",
"\n",
"regs1d = regs[['chrom1','start1','end1', 'name']].rename({'chrom1':'chrom', 'start1':'start', 'end1':'end'}, axis='columns')\n",
"regs1d = regs1d[~regs1d['chrom'].str.strip().str.startswith('#')]\n",
"regs1d['length'] = regs1d['end'] - regs1d['start']"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"paired_mask = regs1d.name.str.endswith(', paired')\n",
"unpaired_mask = regs1d.name.str.endswith(', unpaired')"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"15 679492\n",
"16 783967\n",
"19 1111242\n",
"22 1061298\n",
"24 536892\n",
"26 491901\n",
"28 2213553\n",
"31 768595\n",
"32 1249052\n",
"33 2081752\n",
"Name: length, dtype: int64"
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"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"regs1d[unpaired_mask].length"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/users/anton.goloborodko/src/wiggin/wiggin/polychrom_contrib.py:396: RuntimeWarning: divide by zero encountered in log\n",
" np.log(xs),\n",
"/users/anton.goloborodko/src/wiggin/wiggin/polychrom_contrib.py:397: RuntimeWarning: divide by zero encountered in log\n",
" np.log(xp),\n",
"/users/anton.goloborodko/src/wiggin/wiggin/polychrom_contrib.py:398: RuntimeWarning: divide by zero encountered in log\n",
" np.log(fp),\n"
]
}
],
"source": [
"SIGMA_SMOOTHING_LOG10 = 0.15\n",
"\n",
"scs_exp = {}\n",
"\n",
"\n",
"for _, reg in regs1d.iterrows():\n",
" for k, clr in clrs.items():\n",
" mat = clr.matrix().fetch(\n",
" (reg['chrom'], reg['start'], reg['end']),\n",
"# (reg['chrom2'], reg['start2'], reg['end2']),\n",
"# (reg['chrom2'], reg['start2'], reg['end2']),\n",
" )\n",
" \n",
" weights = clr.bins().fetch((reg['chrom'], reg['start'], reg['end']))['weight']\n",
" is_bad_bin = np.isnan(weights).values\n",
" mat[is_bad_bin] = np.nan\n",
" mat[:, is_bad_bin] = np.nan\n",
"\n",
"# if k[-1] == 'nipbl_trans':\n",
"# mat /= 2\n",
"\n",
" cvd = cooltools.expected.diagsum_from_array(mat, ignore_diags=0)\n",
" cvd['region'] = reg['name']\n",
" \n",
" \n",
" lb_cvd = wiggin.polychrom_contrib.agg_smooth_cvd(\n",
" cvd, \n",
" sigma_log10=SIGMA_SMOOTHING_LOG10,\n",
" dist_col='diag',\n",
" n_pairs_col='n_valid',\n",
" n_contacts_col='balanced.sum',\n",
" contact_freq_col='balanced.avg',\n",
" )\n",
" \n",
"\n",
" scs_exp[(reg['name'], k)] = lb_cvd\n"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"scs_exp_agg = {}\n",
"\n",
"for clr_name in clrs:\n",
" for paired in ['paired', 'unpaired']:\n",
" scs2agg = [\n",
" sc for k, sc in scs_exp.items()\n",
" if k[1] == clr_name and k[0].endswith(', ' + paired)\n",
" ]\n",
"\n",
" if not len(scs2agg):\n",
" continue\n",
" \n",
" scs_exp_agg[(paired, clr_name)] = wiggin.polychrom_contrib.agg_smooth_cvd(\n",
" pd.concat(scs2agg), \n",
" sigma_log10=SIGMA_SMOOTHING_LOG10,\n",
" dist_col='diag',\n",
" n_pairs_col='n_valid',\n",
" n_contacts_col='balanced.sum',\n",
" contact_freq_col='balanced.avg',\n",
" )\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
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" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>diag</th>\n",
" <th>n_valid</th>\n",
" <th>balanced.sum</th>\n",
" <th>n_valid.smoothed</th>\n",
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" <td>1.0</td>\n",
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" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>0.009335</td>\n",
" <td>1.0</td>\n",
" <td>0.007889</td>\n",
" <td>0.009335</td>\n",
" <td>0.007889</td>\n",
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" <th>4</th>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
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" <td>0.486170</td>\n",
" <td>NaN</td>\n",
" <td>0.486170</td>\n",
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" <th>1433</th>\n",
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" <td>0.486201</td>\n",
" <td>NaN</td>\n",
" <td>0.486201</td>\n",
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" <tr>\n",
" <th>1434</th>\n",
" <td>1.0</td>\n",
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" <td>1.0</td>\n",
" <td>0.486232</td>\n",
" <td>NaN</td>\n",
" <td>0.486232</td>\n",
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" <tr>\n",
" <th>1435</th>\n",
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],
"text/plain": [
" diag n_valid balanced.sum n_valid.smoothed balanced.sum.smoothed \\\n",
"0 NaN 1.0 0.000224 NaN NaN \n",
"1 1.0 1.0 0.000324 1.0 0.000350 \n",
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"3 1.0 1.0 0.009335 1.0 0.007889 \n",
"4 1.0 1.0 0.011462 1.0 0.011715 \n",
"... ... ... ... ... ... \n",
"1431 1.0 1.0 NaN 1.0 0.486138 \n",
"1432 1.0 1.0 NaN 1.0 0.486170 \n",
"1433 1.0 1.0 NaN 1.0 0.486201 \n",
"1434 1.0 1.0 NaN 1.0 0.486232 \n",
"1435 1.0 1.0 NaN 1.0 0.486263 \n",
"\n",
" balanced.avg balanced.avg.smoothed \n",
"0 0.000224 NaN \n",
"1 0.000324 0.000350 \n",
"2 0.005214 0.001937 \n",
"3 0.009335 0.007889 \n",
"4 0.011462 0.011715 \n",
"... ... ... \n",
"1431 NaN 0.486138 \n",
"1432 NaN 0.486170 \n",
"1433 NaN 0.486201 \n",
"1434 NaN 0.486232 \n",
"1435 NaN 0.486263 \n",
"\n",
"[1436 rows x 7 columns]"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"scs_exp_agg[('paired','wt_trans')] / scs_exp_agg[('paired','wt_cis')]"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
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" <td>1.0</td>\n",
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" <td>0.003299</td>\n",
" <td>0.004026</td>\n",
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" <td>0.004741</td>\n",
" <td>0.006026</td>\n",
" <td>0.004741</td>\n",
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" <td>1.0</td>\n",
" <td>0.245837</td>\n",
" <td>NaN</td>\n",
" <td>0.245837</td>\n",
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" <td>1.0</td>\n",
" <td>0.245899</td>\n",
" <td>NaN</td>\n",
" <td>0.245899</td>\n",
" </tr>\n",
" <tr>\n",
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" <td>1.0</td>\n",
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" <td>1.0</td>\n",
" <td>0.245931</td>\n",
" <td>NaN</td>\n",
" <td>0.245931</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2214</th>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
" <td>0.245962</td>\n",
" <td>NaN</td>\n",
" <td>0.245962</td>\n",
" </tr>\n",
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"</table>\n",
"<p>2215 rows × 7 columns</p>\n",
"</div>"
],
"text/plain": [
" diag n_valid balanced.sum n_valid.smoothed balanced.sum.smoothed \\\n",
"0 NaN 1.0 0.000412 NaN NaN \n",
"1 1.0 1.0 0.000447 1.0 0.000470 \n",
"2 1.0 1.0 0.004627 1.0 0.001595 \n",
"3 1.0 1.0 0.003299 1.0 0.004026 \n",
"4 1.0 1.0 0.006026 1.0 0.004741 \n",
"... ... ... ... ... ... \n",
"2210 1.0 1.0 NaN 1.0 0.245837 \n",
"2211 1.0 1.0 NaN 1.0 0.245868 \n",
"2212 1.0 1.0 NaN 1.0 0.245899 \n",
"2213 1.0 1.0 NaN 1.0 0.245931 \n",
"2214 1.0 1.0 NaN 1.0 0.245962 \n",
"\n",
" balanced.avg balanced.avg.smoothed \n",
"0 0.000412 NaN \n",
"1 0.000447 0.000470 \n",
"2 0.004627 0.001595 \n",
"3 0.003299 0.004026 \n",
"4 0.006026 0.004741 \n",
"... ... ... \n",
"2210 NaN 0.245837 \n",
"2211 NaN 0.245868 \n",
"2212 NaN 0.245899 \n",
"2213 NaN 0.245931 \n",
"2214 NaN 0.245962 \n",
"\n",
"[2215 rows x 7 columns]"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"scs_exp_agg[('unpaired','wt_trans')] / scs_exp_agg[('unpaired','wt_cis')]"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"plt.rcParams['figure.dpi'] = 150"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 375x900 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"XLIM = (3e3, 1e7)\n",
"KEY2LABEL = lambda k: k[1].split('_')[-1]\n",
"EXP_NORM_FACTOR = 1e2\n",
"\n",
"scs2plot = scs_exp\n",
"scs2plot_agg = scs_exp_agg\n",
"\n",
"scs2plot = {k:v for k,v in scs_exp.items() if not k[0].endswith('unpaired')}\n",
"scs2plot_agg = {k:v for k,v in scs_exp_agg.items() if not k[0].endswith('unpaired')}\n",
"\n",
"f, axs =plt.subplot_mosaic('''\n",
" A\n",
" A\n",
" A\n",
" A\n",
" A\n",
" A\n",
" .\n",
" B\n",
" B\n",
" ''',\n",
" figsize=(2.5,6))\n",
"\n",
"\n",
"ax = axs['A']\n",
"for k, sc in scs2plot.items():\n",
" ax.loglog(\n",
" sc['diag'] * RES,\n",
" sc['balanced.avg.smoothed'] * EXP_NORM_FACTOR,\n",
" markersize=5,\n",
" c='gray',\n",
" alpha=0.5\n",
" )\n",
"\n",
"ax = axs['A']\n",
"for k, sc in scs2plot_agg.items():\n",
" ax.loglog(\n",
" sc['diag'] * RES,\n",
" sc['balanced.avg.smoothed'] * EXP_NORM_FACTOR,\n",
" label=KEY2LABEL(k),\n",
" markersize=5,\n",
" c='C0' if k[1].endswith('cis') else 'C1'\n",
" )\n",
"\n",
"ax = axs['B']\n",
"for k, sc in scs2plot.items():\n",
" if k[-1].endswith('trans'):\n",
" sc_trans = scs2plot[k]\n",
" sc_cis = scs2plot[(k[0], k[-1].replace('trans','cis'))]\n",
" ax.loglog(\n",
" sc['diag'] * RES,\n",
" sc_trans['balanced.avg.smoothed'] / sc_cis['balanced.avg.smoothed'], \n",
" markersize=5,\n",
" c='gray',\n",
" alpha=0.5\n",
" )\n",
"\n",
"x = axs['B']\n",
"for k, sc in scs2plot_agg.items():\n",
" if k[-1].endswith('trans'):\n",
" sc_trans = scs2plot_agg[k]\n",
" sc_cis = scs2plot_agg[(k[0], k[-1].replace('trans','cis'))]\n",
" ax.loglog(\n",
" sc['diag'] * RES,\n",
" sc_trans['balanced.avg.smoothed'] / sc_cis['balanced.avg.smoothed'], \n",
" label=k,\n",
" markersize=5,\n",
" c='C0' if k[0].endswith('cis') else 'C1'\n",
"\n",
" )\n",
"\n",
"ax = axs['A']\n",
"ax.set(\n",
" xlim = XLIM,\n",
" ylim = (1e-5, 1e0),\n",
" aspect=1.0,\n",
" ylabel='contact frequency',\n",
" xlabel='genomic distance, bp'\n",
"); \n",
"ax.legend(loc=(1.1,0.1))\n",
"\n",
"\n",
"ax = axs['B']\n",
"ax.set(\n",
" xlim = XLIM,\n",
" ylim = (1e-3, 1.5),\n",
" ylabel='trans / cis',\n",
" xlabel='genomic distance, bp'\n",
"); \n",
"ax.axhline(1, lw=0.5, color='gray')\n",
"\n",
"for ax in axs.values():\n",
" ax.grid(lw=0.5, color='gray')\n",
"\n",
" locmaj = mpl.ticker.LogLocator(base=10.0, subs=(1.0, ), numticks=100)\n",
" locmin = mpl.ticker.LogLocator(base=10.0, subs=np.arange(2, 10) * .1,\n",
" numticks=100)\n",
"\n",
" ax.xaxis.set_major_locator(locmaj)\n",
" ax.xaxis.set_minor_locator(locmin)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Data vs simulations"
]
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/users/anton.goloborodko/src/wiggin/wiggin/polychrom_contrib.py:394: RuntimeWarning: divide by zero encountered in log\n",
" np.log(xs),\n",
"/users/anton.goloborodko/src/wiggin/wiggin/polychrom_contrib.py:395: RuntimeWarning: divide by zero encountered in log\n",
" np.log(xp),\n",
"/users/anton.goloborodko/src/wiggin/wiggin/polychrom_contrib.py:396: RuntimeWarning: divide by zero encountered in log\n",
" np.log(fp),\n",
"/users/anton.goloborodko/src/wiggin/wiggin/polychrom_contrib.py:394: RuntimeWarning: divide by zero encountered in log\n",
" np.log(xs),\n",
"/users/anton.goloborodko/src/wiggin/wiggin/polychrom_contrib.py:395: RuntimeWarning: divide by zero encountered in log\n",
" np.log(xp),\n",
"/users/anton.goloborodko/src/wiggin/wiggin/polychrom_contrib.py:396: RuntimeWarning: divide by zero encountered in log\n",
" np.log(fp),\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 375x900 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"XLIM = (3e3, 1e7)\n",
"KEY2LABEL = lambda k: k[1].split('_')[-1]\n",
"EXP_NORM_FACTOR = 2e2\n",
"\n",
"scs2plot = scs_exp\n",
"scs2plot_agg = scs_exp_agg\n",
"\n",
"scs2plot = {k:v for k,v in scs_exp.items() if k[0].endswith('unpaired')}\n",
"scs2plot_agg = {k:v for k,v in scs_exp_agg.items() if k[0].endswith('unpaired')}\n",
"\n",
"f, axs =plt.subplot_mosaic('''\n",
" A\n",
" A\n",
" A\n",
" A\n",
" A\n",
" A\n",
" .\n",
" B\n",
" B\n",
" ''',\n",
" figsize=(2.5,6))\n",
"\n",
"\n",
"# ax = axs['A']\n",
"# for k, sc in scs2plot.items():\n",
"# ax.loglog(\n",
"# sc['diag'] * RES,\n",
"# sc['balanced.avg.smoothed'] * EXP_NORM_FACTOR,\n",
"# markersize=5,\n",
"# c='gray',\n",
"# alpha=0.5\n",
"# )\n",
"\n",
"ax = axs['A']\n",
"for k, sc in scs2plot_agg.items():\n",
" ax.loglog(\n",
" sc['diag'] * RES,\n",
" sc['balanced.avg.smoothed'] * EXP_NORM_FACTOR,\n",
" label=KEY2LABEL(k),\n",
" markersize=5,\n",
" c='C0' if k[1].endswith('cis') else 'C1'\n",
" )\n",
"\n",
"# ax = axs['B']\n",
"# for k, sc in scs2plot.items():\n",
"# if k[-1].endswith('trans'):\n",
"# sc_trans = scs2plot[k]\n",
"# sc_cis = scs2plot[(k[0], k[-1].replace('trans','cis'))]\n",
"# ax.loglog(\n",
"# sc['diag'] * RES,\n",
"# sc_trans['balanced.avg.smoothed'] / sc_cis['balanced.avg.smoothed'], \n",
"# markersize=5,\n",
"# c='gray',\n",
"# alpha=0.5\n",
"# )\n",
"\n",
"ax = axs['B']\n",
"for k, sc in scs2plot_agg.items():\n",
" if k[-1].endswith('trans'):\n",
" sc_trans = scs2plot_agg[k]\n",
" sc_cis = scs2plot_agg[(k[0], k[-1].replace('trans','cis'))]\n",
" ax.loglog(\n",
" sc['diag'] * RES,\n",
" sc_trans['balanced.avg.smoothed'] / sc_cis['balanced.avg.smoothed'], \n",
" label=k,\n",
" markersize=5,\n",
" c='C0' if k[0].endswith('cis') else 'C1'\n",
"\n",
" )\n",
"\n",
"\n",
"for i, (key, sc) in enumerate(scs_sim.items()):\n",
"\n",
" sc_sim_cis = wiggin.polychrom_contrib.agg_smooth_cvd(sc.query('chain1 == chain2'), \n",
" sigma_log10=SIGMA_SMOOTHING_LOG10)\n",
" sc_sim_trans = wiggin.polychrom_contrib.agg_smooth_cvd(sc.query('chain1 != chain2'), \n",
" sigma_log10=SIGMA_SMOOTHING_LOG10)\n",
"\n",
" xs_sim = sc_sim_cis['dist'].values * BP_PARTICLE\n",
" ys_sim_cis = sc_sim_cis['contact_freq.smoothed'].values\n",
" ys_sim_trans = sc_sim_trans['contact_freq.smoothed'].values\n",
"\n",
" norm_factor_sim = pairlib.scalings.norm_scaling_factor(xs_sim, ys_sim_cis, 3e3)\n",
" ys_sim_cis = ys_sim_cis / norm_factor_sim\n",
" ys_sim_trans = ys_sim_trans / norm_factor_sim \n",
"\n",
"\n",
" ax = axs['A']\n",
" plot_ghost = True\n",
"\n",
" ax.loglog(xs_sim, ys_sim_cis, \n",
" color='gray' if plot_ghost else 'C0', \n",
" alpha=0.5 if plot_ghost else 1.0, \n",
" label=None if plot_ghost else 'cis'\n",
" )\n",
" ax.loglog(xs_sim, ys_sim_trans, \n",
" color='gray' if plot_ghost else 'C1', \n",
" alpha=0.5 if plot_ghost else 1.0, \n",
" label=None if plot_ghost else 'trans'\n",
" )\n",
"\n",
" \n",
" ax = axs['B']\n",
" ax.loglog(xs_sim, ys_sim_trans / ys_sim_cis, \n",
" color='gray' if plot_ghost else 'C1', \n",
" alpha=0.5 if plot_ghost else 1.0, )\n",
"\n",
"\n",
"\n",
"ax = axs['A']\n",
"ax.set(\n",
" xlim = XLIM,\n",
" ylim = (1e-5, 1e0),\n",
" aspect=1.0,\n",
" ylabel='contact frequency',\n",
" xlabel='genomic distance, bp'\n",
"); \n",
"ax.legend(loc=(1.1,0.1))\n",
"\n",
"\n",
"ax = axs['B']\n",
"ax.set(\n",
" xlim = XLIM,\n",
" ylim = (1e-3, 1.5),\n",
" ylabel='trans / cis',\n",
" xlabel='genomic distance, bp'\n",
"); \n",
"ax.axhline(1, lw=0.5, color='gray')\n",
"\n",
"for ax in axs.values():\n",
" ax.grid(lw=0.5, color='gray')\n",
"\n",
" locmaj = mpl.ticker.LogLocator(base=10.0, subs=(1.0, ), numticks=100)\n",
" locmin = mpl.ticker.LogLocator(base=10.0, subs=np.arange(2, 10) * .1,\n",
" numticks=100)\n",
"\n",
" ax.xaxis.set_major_locator(locmaj)\n",
" ax.xaxis.set_minor_locator(locmin)\n"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"# Use bioframe to fetch the genomic features from the UCSC.\n",
"hg19_chromsizes = bioframe.fetch_chromsizes('hg19')\n",
"hg19_cens = bioframe.fetch_centromeres('hg19')\n",
"hg19_arms = bioframe.core.construction.add_ucsc_name_column(bioframe.make_chromarms(hg19_chromsizes, hg19_cens))\n",
"\n",
"hg19_arms = hg19_arms[hg19_arms.chrom.isin(clr.chromnames)].reset_index(drop=True)"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"scs_exp_gw = {k: cooltools.expected.diagsum(\n",
" clr=clr,\n",
" view_df=hg19_arms,\n",
" transforms={'balanced': lambda p: p['count']*p['weight1']*p['weight2']}\n",
")\n",
"for k, clr in clrs.items()}"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/users/anton.goloborodko/src/wiggin/wiggin/polychrom_contrib.py:394: RuntimeWarning: divide by zero encountered in log\n",
" np.log(xs),\n",
"/users/anton.goloborodko/src/wiggin/wiggin/polychrom_contrib.py:395: RuntimeWarning: divide by zero encountered in log\n",
" np.log(xp),\n",
"/users/anton.goloborodko/src/wiggin/wiggin/polychrom_contrib.py:396: RuntimeWarning: divide by zero encountered in log\n",
" np.log(fp),\n"
]
}
],
"source": [
"scs_exp_gw_agg = {}\n",
"\n",
"for k, sc_exp_gw in scs_exp_gw.items():\n",
" scs_exp_gw_agg[k] = wiggin.polychrom_contrib.agg_smooth_cvd(\n",
" sc_exp_gw, \n",
" sigma_log10=SIGMA_SMOOTHING_LOG10,\n",
" dist_col='diag',\n",
" n_pairs_col='n_valid',\n",
" n_contacts_col='balanced.sum',\n",
" contact_freq_col='balanced.avg',\n",
" )\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [],
"source": [
"import matplotlib as mpl\n",
"mpl.rcParams['figure.dpi'] = 150"
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/users/anton.goloborodko/src/wiggin/wiggin/polychrom_contrib.py:394: RuntimeWarning: divide by zero encountered in log\n",
" np.log(xs),\n",
"/users/anton.goloborodko/src/wiggin/wiggin/polychrom_contrib.py:395: RuntimeWarning: divide by zero encountered in log\n",
" np.log(xp),\n",
"/users/anton.goloborodko/src/wiggin/wiggin/polychrom_contrib.py:396: RuntimeWarning: divide by zero encountered in log\n",
" np.log(fp),\n"
]
},
{
"data": {
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",
"text/plain": [
"<Figure size 375x900 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"XLIM = (3e3, 1e7)\n",
"KEY2LABEL = lambda k: k.split('_')[-1]\n",
"EXP_NORM_FACTOR = 1.5e2\n",
"BP_PARTICLE = 200\n",
"\n",
"scs2plot_agg = scs_exp_gw_agg\n",
"\n",
"f, axs = plt.subplot_mosaic('''\n",
" A\n",
" A\n",
" A\n",
" A\n",
" A\n",
" A\n",
" .\n",
" B\n",
" B\n",
" ''',\n",
" figsize=(2.5,6))\n",
"\n",
"\n",
"\n",
"\n",
"ax = axs['A']\n",
"for k, sc in scs2plot_agg.items():\n",
" ax.loglog(\n",
" sc['diag'] * RES,\n",
" sc['balanced.avg.smoothed'] * EXP_NORM_FACTOR,\n",
" label=KEY2LABEL(k),\n",
" # label='WT experiment' if k.endswith('cis') else None,\n",
" markersize=5,\n",
" c='C0' if k.endswith('cis') else 'C1'\n",
" # alpha=0.5,\n",
" # c='gray'\n",
" )\n",
"\n",
"ax = axs['B']\n",
"for k, sc in scs2plot_agg.items():\n",
" if k.endswith('trans'):\n",
" sc_trans = scs2plot_agg[k]\n",
" sc_cis = scs2plot_agg[(k.replace('trans','cis'))]\n",
" ax.loglog(\n",
" sc_trans['diag'] * RES,\n",
" sc_trans['balanced.avg.smoothed'] / sc_cis['balanced.avg.smoothed'], \n",
" #label=k,\n",
" markersize=5,\n",
" c='C0' if k[0].endswith('cis') else 'C1'\n",
" # alpha=0.5,\n",
" # c='gray'\n",
"\n",
" )\n",
"\n",
"\n",
"\n",
"\n",
"for i, (key, sc) in enumerate(scs_sim.items()):\n",
"\n",
" sc_sim_cis = wiggin.polychrom_contrib.agg_smooth_cvd(sc.query('chain1 == chain2'), \n",
" sigma_log10=SIGMA_SMOOTHING_LOG10)\n",
" sc_sim_trans = wiggin.polychrom_contrib.agg_smooth_cvd(sc.query('chain1 != chain2'), \n",
" sigma_log10=SIGMA_SMOOTHING_LOG10)\n",
"\n",
" xs_sim = sc_sim_cis['dist'].values * BP_PARTICLE\n",
" ys_sim_cis = sc_sim_cis['contact_freq.smoothed'].values\n",
" ys_sim_trans = sc_sim_trans['contact_freq.smoothed'].values\n",
"\n",
" norm_factor_sim = pairlib.scalings.norm_scaling_factor(xs_sim, ys_sim_cis, 3e3)\n",
" ys_sim_cis = ys_sim_cis / norm_factor_sim\n",
" ys_sim_trans = ys_sim_trans / norm_factor_sim \n",
"\n",
"\n",
" ax = axs['A']\n",
" plot_ghost = True\n",
"\n",
" ax.loglog(xs_sim, ys_sim_cis, \n",
" color='gray' if plot_ghost else 'C0', \n",
" alpha=0.5 if plot_ghost else 1.0, \n",
" # label=None if plot_ghost else 'cis simulations'\n",
" label='simulations'\n",
" )\n",
" ax.loglog(xs_sim, ys_sim_trans, \n",
" color='gray' if plot_ghost else 'C1', \n",
" alpha=0.5 if plot_ghost else 1.0, \n",
" label=None if plot_ghost else 'trans simulations'\n",
" )\n",
"\n",
" \n",
" ax = axs['B']\n",
" ax.loglog(xs_sim, ys_sim_trans / ys_sim_cis, \n",
" color='gray' if plot_ghost else 'C1', \n",
" alpha=0.5 if plot_ghost else 1.0, )\n",
"\n",
"\n",
"\n",
"\n",
"ax = axs['A']\n",
"ax.set(\n",
" xlim = XLIM,\n",
" ylim = (1e-5, 1e0),\n",
" aspect=1.0,\n",
" ylabel='contact frequency',\n",
" xlabel='genomic distance, bp'\n",
"); \n",
"ax.legend(loc=(1.1,0.1))\n",
"\n",
"\n",
"ax = axs['B']\n",
"ax.set(\n",
" xlim = XLIM,\n",
" ylim = (1e-3, 1.5),\n",
" ylabel='trans / cis',\n",
" xlabel='genomic distance, bp'\n",
"); \n",
"ax.axhline(1, lw=0.5, color='gray')\n",
"\n",
"for ax in axs.values():\n",
" ax.grid(lw=0.5, color='gray')\n",
"\n",
" locmaj = mpl.ticker.LogLocator(base=10.0, subs=(1.0, ), numticks=100)\n",
" locmin = mpl.ticker.LogLocator(base=10.0, subs=np.arange(2, 10) * .1,\n",
" numticks=100)\n",
"\n",
" ax.xaxis.set_major_locator(locmaj)\n",
" ax.xaxis.set_minor_locator(locmin)\n"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "main",
"language": "python",
"name": "main"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.4"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
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