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Analysis

A typical analysis tasks reads the trajectory (XTC) or energy (EDR) file, computes quantities, and produces datafiles that can be plotted or processed further, e.g. using Python scripts. A strength of Gromacs_ is that it comes with a wide range of tools that each do one particular analysis task well (see the `Gromacs manual`_ and the `Gromacs documentation`_).

Basic analysis

As examples, we perform a number of common analysis tasks.

.. toctree::
   :maxdepth: 1

   analysis/rmsd
   analysis/rmsf
   analysis/distances
   analysis/rgyr

More Gromacs tools

A number of interesting quantities and observables [1] can be calculated with Gromacs tools. A selection is shown below but you are encouraged to read the `Gromacs manual`_ and the `Gromacs documentation`_ to find out what else is available.

Selection of Gromacs analysis tools

The full `list of Gromacs commands`_ contains 98 different tools. A small selection of commonly used ones are shown here:

:ref:`gmx energy`
basic thermodynamic properties of the system
:ref:`gmx rms`
calculate the root mean square deviation from a reference structure
:ref:`gmx rmsf`
calculate the per-residue root mean square fluctuations
:ref:`gmx gyrate`
calculate the radius of gyration
:ref:`gmx mindist` and :ref:`gmx distance`
calculate the distance between atoms or groups of atoms (make a index file with :ref:`gmx make_ndx` to define the groups of interest). :program:`gmx mindist` is especially useful to find water molecules close to a region of interest.
:ref:`gmx do_dssp`
Use the DSSP_ algorithm [Kabsch1983]_ to analyze the secondary structure (helices, sheets, ...).
.. seealso::

   * For analysis coupled with visualization look at VMD_.
   * For analyzing MD trajectories in many common formats (including
     the XTC, TRR, etc. used by Gromacs) using Python_, have a look at
     the `MDAnalysis`_ Python library (the `MDAnalysis Tutorial`_ is a
     good place to start... and it also uses AdK as an example).

Footnotes

[1]"Observable" is used in the widest sense in that we know an estimator function of all or a subset of the system's phase space coordinates that is averaged to provide a quantity of interest. In many cases it requires considerable more work to connect such an "observable" to a true experimental observable that is measured in an experiment.