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Validation pipeline for integrative and hybrid models

Project objective

  • 1. Develop a validation pipeline (including data validation, model validation, fit of input to model, fit of data not used for modeling and uncertainty of the model) for assessing IHM structures deposited to PDB-Dev

List of files and directories:

  • docs documentation for all classes and functions (sphinx)

  • src relevant source code for execution

  • static relevant css, js files for static and dynamic HTML reports along with output files from validation [htmls,images,pdfs,json,results,supplementary]

  • templates all HTML templates for static HTML reports, PDF files and supplementary table

  • tests tests for classes

  • example_sas example script to create validation reports for SAS data

  • example_imp_models example script to create validation reports for IMP models

  • example_summary_table example script to create validation reports for summary table

List of classes:

  • WriteReport class to write dictionary for jinja2, HTML and PDF outputs

  • plots quality at glance plots from all different analysis

  • get_excluded_volume class to calculate excluded volume and other relevant statistics

  • get_molprobity_information class to get data from molprobity, used only for atomistic models

  • sas_validation class to perform validation of models built using SAS datasets

  • sas_validation_plots plots based on SAS validation analysis

  • cx_validation class to perform validation of models built using CX-MS datasets

  • cx_validation_plots plots based on CX-MS validation analysis

  • em_validation class to perform validation of models built using EM datasets

Test site

Docker image

Rather than installing and configuring all dependencies (below), you can build a Docker (or podman) container by

  1. Downloading the ATSAS CentOS 7 RPM and placing it in the docker subdirectory (this cannot be redistributed by us; you must sign up at their web site for an academic license).
  2. Building the image with docker build -t ihm-validation docker

The resulting image has all dependencies in the default PATH and this repository available in the /IHMValidation directory; no further configuration should be necessary.

Initial setup

This initial setup is performed once.

Create and activate a Python3.8 virtual environment.

$ python3 -m venv .venv
$ source .venv/bin/activate


$ pip3 install -r dependencies.txt

Install the following packages based on your OS.

Create a local environment file and add the relevant variables.

$ touch .env
$ nano/vi .env

The variables to add to the .env file can be seen below (fill in the quotations with paths to the relevant values).

ATSAS="" 
Molprobity_ramalyze=""
Molprobity_molprobity=""
Molprobity_clashscore=""
Molprobity_rotalyze=""
wkhtmltopdf=""

Few pointers:

  1. ATSAS variable should contain the path to datcmp functionality, example : ATSAS-3.0.3-1/bin/datcmp

  2. Molprobity variables should point to respective functionalities, example : build/bin/molprobity.ramalyze

  3. wkhtmltopdf variable should point to the binary

Common errors in the installation process

  1. One common error, depending on your OS and webdriver is from bokeh/selenium. This error is usually displayed as:
  • RuntimeError: Neither firefox and geckodriver nor a variant of chromium browser and chromedriver are available on system PATH. You can install the former with 'conda install -c conda-forge firefox geckodriver'.

This error originates from converting htmls to svgs. Please install/update your webdriver. You can do this by adding pre-installed binaries to path variable or install packages using the suggested conda command.

To add pre-installed binaries (firefox and geckodriver), find the path of the binaries. Please try using conda first, add paths to binaries only if you are unable to use conda. You can do that in two steps:

  • You can use the command which firefox or which geckodriver to get path to respective binaries. If you don't have the pre-installed binaries, install fireforx/geckodriver using brew and then locate binaries. You can also download geckodriver from the mozilla github page.

  • You should then open the webdriver.py file in bokeh and add the path to appropriate functions. Open the webdriver.py file using the following path .venv/lib/python3.8/site-packages/bokeh/io/webdriver.py. Edit create_firefox_webdriver function by changing the variables for firefox to the binary path (delete which firefox) and change geckodriver to it's pre-installed binary path (delete which geckodriver).

  1. Another potential error could arise from having another env variable file or not having the file in the same directory. This error is displayed as:
  • ValueError: UndefinedValueError('{} not found. Declare it as envvar or define a default value.'.format(option)).

A solution to this error is using Autoconfig of decouple library to add the path to your .env file. See this stackoverflow post for specific details.

  1. An error could arise from not being able to access the executable, even though the path is found. This error can occur with the ATSAS package and is displayed as:
  • PermissionError: [Errno 13] Permission denied: '/ATSAS-3.0.3-1'

A solution to this is to open your .venv/bin/activate file and add in the above six variables at the top as 6 lines of code using the format export KEY=VALUE. See this stackoverflow post for specific details.

Running an example

After the initial setup, you can start executing the scripts to generate validation reports. Here are the steps:

  • Go to the example directory.
  • Command to execute: python Execute.py -f PDBDEV_00000009.cif
  • If new software was used to build the structure, update reference.csv, located in the templates directory with appropriate software name, PubMed link, and citation.

The input to the Execute.py script is a PDBDEV file in cif format. The output includes directories and files that are listed below:

  • Directory ../Validation/PDBDEV_00000009
  • Directory ../Validation/PDBDEV_00000009/images
  • Directory ../Validation/PDBDEV_00000009/pdf
  • Directory ../Validation/PDBDEV_00000009/json
  • Directory ../Validation/PDBDEV_00000009/supplementary
  • Directory ../Validation/PDBDEV_00000009/htmls
  • Directory ../Validation/PDBDEV_00000009/csv

Here's the description of all the directories:

  • Validation is the main head directory and is located one step above the example directory [you can see that in the way this repo is structured]
  • PDBDEV_00000009 is the entry directory with relevant files
  • PDBDEV_00000009/images contains all the images generated for this entry
  • PDBDEV_00000009/pdf contains all the pdf files generated for this entry, including pdf version of the validation report
  • PDBDEV_00000009/json contains the validation report in a json format as key-value pairs
  • PDBDEV_00000009/supplementary contains the summary table in a PDF format
  • PDBDEV_00000009/htmls contains corresponding html pages
  • PDBDEV_00000009/csv contains detailed molprobity tables for download

Transferring files to the server

The Validation folder that is generated needs to be transferred to the server. If individual entries are being evaluated, move/copy the entry directory from the local validation directory into the server's validation directory.

Information

Author(s): Sai J. Ganesan