{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "## Store the data to HDF5 file for rapid analysis and calculation\n", "\n", "* This tutorial discuss the analyses that can be performed using the [dnaMD Python module](http://do-x3dna.readthedocs.io/en/latest/api_summary.html) included in the _do\\_x3dna_ package. The tutorial is prepared using [Jupyter Notebook](https://jupyter.org/) and this notebook tutorial file could be downloaded from this [link](http://rjdkmr.github.io/do_x3dna/tut_notebook/hdf5_tutorial.ipynb).\n", "\n", "\n", "* Download the input files that are used in the tutorial from this [link](http://rjdkmr.github.io/do_x3dna/tutorial_data.tar.gz).\n", "\n", "\n", "* Two following input files are required in this tutorial\n", " * ``L-BP_cdna.dat`` \n", " * ``L-BPS_cdna.dat``\n", " * ``L-BPH_cdna.dat``\n", " * ``HelAxis_cdna.dat``\n", " * ``MGroove_cdna.dat``\n", " * ``BackBoneCHiDihedrals_cdna.dat``\n", " \n", " These files **should be** present inside tutorial_data of the current/present working directory.\n", " \n", " \n", "* The Python APIs **should be** only used when ``do_x3dna`` is executed with ``-ref`` option.\n", "\n", "\n", "* Detailed documentation is provided [here](http://do-x3dna.readthedocs.io/en/latest/dna_class_api.html)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Importing Python Modules\n", "\n", "* [numpy](http://www.numpy.org/): Required for the calculations involving large arrays\n", "\n", "\n", "* [matplotlib](http://matplotlib.org/): Required to plot the results\n", "\n", "\n", "* [dnaMD](http://do-x3dna.readthedocs.io/en/latest/api_summary.html): Python module to analyze DNA/RNA structures from the do_x3dna output files.\n" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import os\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import dnaMD\n", "%matplotlib inline\n", "\n", "\n", "try:\n", " os.remove('cdna.h5')\n", "except:\n", " pass\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Initializing DNA object with HDF5 file\n", "\n", "* [DNA object](http://do-x3dna.readthedocs.io/en/latest/dna_class_api.html#dnaMD.dnaMD.DNA) is initialized by using the total number of base-pairs\n", "\n", "\n", "To store the data in HDF5 file, just initialize the class with the filename as shown below. Here, we named the HDF5 file as ``cdna.h5``.\n", "\n", "**NOTE**: Except initialization, all other methods and functions can be used in similar ways." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "# Initialization\n", "dna = dnaMD.DNA(60, filename='cdna.h5') #Initialization for 60 base-pairs DNA bound with the protein\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Store/Save data to HDF5 file\n", "\n", "**No extra step neccessary to store the data in HDF5 file**. Just read the parameters from do_x3dna output files as described in previous tutorials.\n", "\n", "\n", "* Local base-pair parameters as shown [preveiosly here](http://do-x3dna.readthedocs.io/en/latest/notebooks/base_pairs_tutorial.html#Initializing-DNA-object-and-storing-data-to-it).\n", "* Local base-step parameters as shown [preveiosly here](http://do-x3dna.readthedocs.io/en/latest/notebooks/base_steps_tutorial.html#Initializing-DNA-object-and-storing-data-to-it).\n", "* Local helical base-step parameters as shown [preveiosly here](http://do-x3dna.readthedocs.io/en/latest/notebooks/helical_steps_tutorial.html#Initializing-DNA-object-and-storing-data-to-it).\n", "* Helical axis as shown [preveiosly here](http://do-x3dna.readthedocs.io/en/latest/notebooks/helical_axis_tutorial.html#Initializing-DNA-object-and-storing-data-to-it).\n", "* Major and minor grooves as shown [preveiosly here](http://do-x3dna.readthedocs.io/en/latest/notebooks/major_minor_groove_tutorial.html#Initializing-DNA-object-and-storing-data-to-it).\n", "* Backbone dihedrals as shown [preveiosly here](http://do-x3dna.readthedocs.io/en/latest/notebooks/backbone_torsion_wheel_tutorial.html#Initializing-DNA-object-and-storing-data-to-it)." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Reading file : tutorial_data/L-BP_cdna.dat\n", "Reading frame 1000\n", "Finished reading.... Total number of frame read = 1001\n", "\n", "Reading file : tutorial_data/L-BPS_cdna.dat\n", "Reading frame 1000\n", "Finished reading.... Total number of frame read = 1001\n", "\n", "Reading file : tutorial_data/L-BPH_cdna.dat\n", "Reading frame 1000\n", "Finished reading.... Total number of frame read = 1001\n", "\n", "Reading file : tutorial_data/HelAxis_cdna.dat\n", "Reading frame 1000\n", "Finished reading.... Total number of frame read = 1001\n", "|frame: 526| WARNING: Bending angle [-1-0-1] = 20.14 is more than cut-off angle 20;\n", " Four maximum distances between three adjacent axis positions = (16.4, 14.4, 13.9, 13.5);\n", " Deleting [np.int64(45), np.int64(46)] original helical axis positions to remove possible fitting artifact...\n", "|frame: 549| WARNING: Bending angle [-1-0-1] = 27.93 is more than cut-off angle 20;\n", " Four maximum distances between three adjacent axis positions = (21.0, 19.1, 15.9, 15.3);\n", " Deleting [np.int64(2), np.int64(3)] original helical axis positions to remove possible fitting artifact...\n", "Fitting spline curve on helical axis of frame 600 out of 1001 frames" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/home/raj/github/do_x3dna/dnaMD/dnaMD/dnaMD.py:2635: RuntimeWarning: Mean of empty slice.\n", " xsmooth.append(xnew[start:end].mean())\n", "/home/raj/github/do_x3dna/dnaMD/venv/lib/python3.11/site-packages/numpy/_core/_methods.py:145: RuntimeWarning: invalid value encountered in scalar divide\n", " ret = ret.dtype.type(ret / rcount)\n", "/home/raj/github/do_x3dna/dnaMD/dnaMD/dnaMD.py:2636: RuntimeWarning: Mean of empty slice.\n", " ysmooth.append(ynew[start:end].mean())\n", "/home/raj/github/do_x3dna/dnaMD/dnaMD/dnaMD.py:2637: RuntimeWarning: Mean of empty slice.\n", " zsmooth.append(znew[start:end].mean())\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "|frame: 636| WARNING: Bending angle [-1-0-1] = 33.38 is more than cut-off angle 20;\n", " Four maximum distances between three adjacent axis positions = (14.9, 14.6, 14.2, 13.8);\n", " Deleting [np.int64(5), np.int64(6)] original helical axis positions to remove possible fitting artifact...\n", "|frame: 640| WARNING: Bending angle [-1-0-1] = 28.03 is more than cut-off angle 20;\n", " Four maximum distances between three adjacent axis positions = (16.9, 14.0, 13.4, 13.4);\n", " Deleting [np.int64(2), np.int64(3)] original helical axis positions to remove possible fitting artifact...\n", "Fitting spline curve on helical axis of frame 1000 out of 1001 frames\n", "Finished spline curve fitting...\n", "\n", "Reading file : tutorial_data/MGroove_cdna.dat\n", "Reading frame 1000\n", "Finished reading.... Total number of frame read = 1001\n", "\n", "Reading file : tutorial_data/BackBoneCHiDihedrals_cdna.dat\n", "Reading frame 1000\n", "Finished reading.... Total number of frame read = 1001\n" ] } ], "source": [ "# Read Local base-pair parameters\n", "dna.set_base_pair_parameters('tutorial_data/L-BP_cdna.dat', bp=[1, 60], bp_range=True)\n", "\n", "# Read Local base-step parameters\n", "dna.set_base_step_parameters('tutorial_data/L-BPS_cdna.dat', bp_step=[1, 59], parameters='all', step_range=True)\n", "\n", "# Read Local helical base-step parameters\n", "dna.set_base_step_parameters('tutorial_data/L-BPH_cdna.dat', bp_step=[1, 59], parameters='all', step_range=True, helical=True)\n", "\n", "# Read Helical axis\n", "dna.set_helical_axis('tutorial_data/HelAxis_cdna.dat')\n", "\n", "# Generate global axis by interpolation (smoothening)\n", "dna.generate_smooth_axis(smooth=500, spline=3, fill_point=6)\n", "\n", "# Calculate curvature and tangent along global helical axis\n", "dna.calculate_curvature_tangent(store_tangent=True)\n", "\n", "# Major and minor grooves \n", "parameters = [ 'minor groove', 'minor groove refined', 'major groove', 'major groove refined' ]\n", "dna.set_major_minor_groove('tutorial_data/MGroove_cdna.dat', bp_step=[1, 59], parameters=parameters, step_range=True)\n", "\n", "#Backbone dihedrals\n", "dna.set_backbone_dihedrals('tutorial_data/BackBoneCHiDihedrals_cdna.dat', bp=[2, 59], parameters='all', bp_range=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Example to extract a parameter\n", "As shown [previously here](http://do-x3dna.readthedocs.io/en/latest/notebooks/base_pairs_tutorial.html#Local-base-pair-parameter-of-a-base-pair-directly-from-dictionary), data can be extracted from HDF5 by same way as shown in the following.\n", "\n", "Also, see that plot is similar.\n", "\n", "\n", "Note that in this case, data is read from the HDF5 file, while in the previous tutorial, data was stored in memory (RAM)." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Extracting \"Shear\" of 22nd bp\n", "shear_20bp = dna.data['bp']['22']['shear'][:]\n", "\n", "#Shear vs Time for 22nd bp\n", "plt.title('22nd bp')\n", "plt.plot(dna.time, shear_20bp)\n", "plt.xlabel('Time (ps)')\n", "plt.ylabel('Shear ($\\AA$)')\n", "plt.show()\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Example to extract parameter as a function of time\n", "\n", "As shown [previously here](hhttp://do-x3dna.readthedocs.io/en/latest/notebooks/base_steps_tutorial.html#Local-base-step-parameters-as-a-function-of-time-(using-provided-functions)), smae method ([dnaMD.DNA.time_vs_parameter(...)](http://do-x3dna.readthedocs.io/en/latest/dna_class_api.html#dnaMD.dnaMD.DNA.time_vs_parameter)) can be used to get parameter values as a function of time.\n", "\n", "Also, see that plot is similar.\n", "\n", "\n", "Note that in this case, data is read from the HDF5 file, while in the previous tutorial, data was stored in memory (RAM)." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Rise vs Time for 25-40 bp segment\n", "plt.title('Rise for 25-40 bp segment')\n", "\n", "# Rise is the distance between two base-pairs, so for a given segment it is sum over the base-steps\n", "time, value = dna.time_vs_parameter('rise', [25, 40], merge=True, merge_method='sum')\n", "plt.plot(time, value, label='bound DNA', c='k')\n", "\n", "plt.xlabel('Time (ps)')\n", "plt.ylabel('Rise ( $\\AA$)')\n", "plt.legend()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Reading file : tutorial_data/L-BP_odna.dat\n", "Reading frame 1000\n", "Finished reading.... Total number of frame read = 1001\n", "\n", "Reading file : tutorial_data/L-BPS_odna.dat\n", "Reading frame 1000\n", "Finished reading.... Total number of frame read = 1001\n", "\n", "Reading file : tutorial_data/L-BPH_odna.dat\n", "Reading frame 1000\n", "Finished reading.... Total number of frame read = 1001\n", "\n", "Reading file : tutorial_data/HelAxis_odna.dat\n", "Reading frame 1000\n", "Finished reading.... Total number of frame read = 1001\n", "Fitting spline curve on helical axis of frame 1000 out of 1001 frames\n", "Finished spline curve fitting...\n", "\n", "Reading file : tutorial_data/MGroove_odna.dat\n", "Reading frame 1000\n", "Finished reading.... Total number of frame read = 1001\n", "\n", "Reading file : tutorial_data/BackBoneCHiDihedrals_odna.dat\n", "Reading frame 1000\n", "Finished reading.... Total number of frame read = 1001\n" ] } ], "source": [ "odna = dnaMD.DNA(60, filename='odna.h5') #Initialization for 60 base-pairs DNA bound with the protein\n", "\n", "# Read Local base-pair parameters\n", "odna.set_base_pair_parameters('tutorial_data/L-BP_odna.dat', bp=[1, 60], bp_range=True)\n", "\n", "# Read Local base-step parameters\n", "odna.set_base_step_parameters('tutorial_data/L-BPS_odna.dat', bp_step=[1, 59], parameters='all', step_range=True)\n", "\n", "# Read Local helical base-step parameters\n", "odna.set_base_step_parameters('tutorial_data/L-BPH_odna.dat', bp_step=[1, 59], parameters='all', step_range=True, helical=True)\n", "\n", "# Read Helical axis\n", "odna.set_helical_axis('tutorial_data/HelAxis_odna.dat')\n", "\n", "# Generate global axis by interpolation (smoothening)\n", "odna.generate_smooth_axis(smooth=500, spline=3, fill_point=6)\n", "\n", "# Calculate curvature and tangent along global helical axis\n", "odna.calculate_curvature_tangent(store_tangent=True)\n", "\n", "# Major and minor grooves \n", "parameters = [ 'minor groove', 'minor groove refined', 'major groove', 'major groove refined' ]\n", "odna.set_major_minor_groove('tutorial_data/MGroove_odna.dat', bp_step=[1, 59], parameters=parameters, step_range=True)\n", "\n", "#Backbone dihedrals\n", "odna.set_backbone_dihedrals('tutorial_data/BackBoneCHiDihedrals_odna.dat', bp=[2, 59], parameters='all', bp_range=True)" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.11" } }, "nbformat": 4, "nbformat_minor": 4 }