AMIVA-F 0.0.13

A FLNc mutation pathogenicity predictor algorithm

AMIVA-F-test package

AMIVA-F is a machine learning based algorithm, trained to correlate single point mutations with disease in FLNc.

General Information:

AMIVA-F requires additionally JAVA and PYMOL installed. A step by step tutorial on how to install AMIVA-F is given below for different operating systems Currently it is tested on Anaconda3(Windows 10) but more OS and outside of virtual environments (like anaconda) will be tested soon aswell.

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Anaconda is a distribution of python programming language that helps with package management and deployment. Its available for Windows, Linux and macOS. Package versions in Anaconda are managed by an internal package managment system which does not mess with your local computer package depository. It further simplifies Path dependency problems and is outlined below for a full installation of AMIVA-F tested on Windows in Anaconda3.

Example setup of Anaconda3 from Windows10:

If you already installed anaconda, you can skip the next step.

Installation of Anaconda

1. Download Anaconda from https://www.anaconda.com/products/individual
2. Click on the downloaded .exe data.
3. Close all other applications in the background and click Next>
4. Accept by clicking I Agree
5. Select Just Me (recommended) and then Next>
6. Accept the default destination folder and click Next>
7. Select Register Anaconda3 as my default Python 3.8 and click Install

Workflow inside Anaconda3

Setup of the virtual environment

1. Open the anaconda prompt (anaconda3) which you find by entering anaconda prompt into the windows search bar (Found at the left bottom of your screen).

2. This should open a black command line interface where you now need to enter the following command conda create -n amivaenv python=3.8

3. This creates a new virtual environment with python 3.8 named amivaenv which will be used to install AMIVA and its dependencies without polluting your local pythonspace.

4. You will get a message telling you what is going to be installed. Enter y and press enter.

5. After creation enter: conda activate amivaenv

6. Which will then activate the new environment.

Getting Java required dependencies

1. Download javabridge from https://www.lfd.uci.edu/~gohlke/pythonlibs/#javabridge
   The site will offer you different versions of javabridge but you need the correct version corresponding to your systems bitness.
   You can check the bitness of your PC by pressing windows key + i together, then navigate to System and then chose About.
   Under Device specifications you will find informations about your system type
   e.g 64 bit operating system, x64-based processor
   If you work on a 64-bit operating system you simply need to download
   javabridge‑1.0.19‑cp38‑cp38‑win_amd64.whl.
   If you work on a 32-bit operating system you simply need to download
   javabridge‑1.0.19‑cp38‑cp38‑win32.whl.
   
   Note: The cp38 part specified the cpython version we use
   (3.8 as we created a virtual environment with python 3.8 before, In case that you want to use another python version you need to select cp37 version for 3.7 and so on).
   
2. Open https://adoptopenjdk.net/
   Under Choose a Version select OpenJDK11 (LTS) and for Choose a JVM select HotSpot
   Click the blue button Latest Release and wait for the download to be completed.
   This will download a .msi file which you should open by left clicking on it (Left bottom of the screen, alternatively found in the Download directory).
   Click Next
   Check the I accept the terms in the License Agreement and click Next
   Attention! Click now the Set JAVA_HOME variable and select Will be installed on local hard drive This is the 3rd row in the directory structure.
   Click Next
   Click Install If everything proceeded normally you managed to install AdoptOpenJDK. Click Finish
   

Installing everything required for AMIVA-F

If you followed the previous steps, you should now have everything required to make a full installation of AMIVA-F.
Open the Anaconda3 prompt (enter anaconda3 prompt into the windows search bar, found in the lower left corner of the screen).
This will open again the black cmd line.
If you closed this window during the installation process before, you might need to activate again the virtual environment.
Take a look at the beginning of the command line.
If you find (base) at the beginning you need to reactivate your virtual environment.

conda activate amivaenv

Now you should either find (amivaenv) or it was already there because you did not close the terminal before.

1. Open the File explorer and navigate to the Download directory (default directory for downloads).
   Search for the downloaded javabridge-1.0.19 file
   Right click on the javabridge-1.0.19 file and select Properties
   You can now open an editor of your choice and do the following:
   Copy the path from the Location Point e.g in my case C:\Users\adm2\Downloads.
   Copy this into the editor and add ** and javabridge-1.0.19-cp38-cp38-win_amd64.whl(in my case it was this version) which can be found at the top of the window.
   In your editor, the line should now finally look like this:
   
   C:\Users\adm2\Downloads\javabridge-1.0.19-cp38-cp38-win_amd64.whl
   (again in your case the adm2 name is different)
   

2. In the anaconda prompt you now need to enter the following:
   you need to enter pip install and then copy the path you assembled before in the editor pip install C:\Users\adm2\Downloads\javabridge-1.0.19-cp38-cp38-win_amd64.whl
   If everything worked you will get a message telling you:
   Successfully installed javabridge-1.0.19 numpy-1.20.3
   

3. Now we install AMIVA-F: pip install AMIVA-F
   If everything worked you will get a message telling you:
   Successfully installed AMIVA-F-0.0.6 biopython-1.79 freesasa-2.1.0 python-weka-wrapper3-0.2.3
   

4. We require Pymol: conda install -c schrodinger pymol
   This will ask your permission to install a bunch of files which you accept by entering y and pressing enter.
   

5. Open AMIVA-F
   Open the File explorer and search for your location where you installed Anaconda3.
   Usually you will find this under your username
   e.g in my case this was adm2 , then select anaconda3, envs, amivaenv,Lib, site-packages, AMIVA-F.
   If everything worked well you should see a directory containing the AMIVA-F.py file.
   Right click on this file, select Properties and copy the location
   e.g C:\Users\adm2\anaconda3\envs\amivaenv\Lib\site-packages\AMIVA-F
   Now enter in the command line in anaconda:
   this will look slightly different in your case you need to change adm2 to your user name

    cd C:\Users\adm2\anaconda3\envs\amivaenv\Lib\site-packages\AMIVA-F	 	  	
   

and then enter: python AMIVA-F.py
This should open now a GUI and you can use AMIVA-F.
For instructions on how to use AMIVA-F scroll down below.

Usage of AMIVA-F

AMIVA-F works fully automated and is easy to use, even in the absence of knowledge about the underlying parameters which are used as input for the neural network.

1. AMIVA-F works at the protein annotation level, therefore if you have mutations of interest in the c notation (DNA), look up the corresponding p.notation. Once you have your mutation of interest in protein notation, enter it in the entry field location directly above the green button ("Calculate everything for me!"). The required input could look like this: _If you are interested in the mutation Methionine(M) at position 82 to Lysine(K)

   M82K

If you by any chance submit a wrong amino acid (the amino acid you specified for the wildtype position is in fact not what you submitted, e.g FLNc position 82 corresponds to methionine, but you wrote S82K, which would correspond to serine), then AMIVA-F automatically corrects you and offers you to proceed calculations with the correct amino acid in in place.

2. After you entered the mutation of interest e.g M82K into the entry field specified above, click the green button ("Calculate everything for me!") This button will then automatically grab the correct model structure where your amino acid is located and calculate all input parameters required to predict the pathogenicity of the mutation. Usually this process is really fast, you will see all entry fields filled and you should normally just check if there is anything left blank. The 2 last rows in the entryfield (Found posttranslational modification sites, and additional information) are there to inform you about potentially interesting sited in close proximity (8Angström cutoff) of the desired mutation spot.

If you are working by any chance on posttranslational modifications or you possess information about additional binding partners, feel free to add them to the library files ( Posttranslational_modifications_and_binding_partners\Binding_partners_list.txt and Posttranslational_modifications_and_binding_partners\Posttranslational_modification_list.txt) which will be taken into account when filling out the input parameters.

3. Check if every entry field in the form is filled and every radiobutton is selected. If everything seems fine, proceed by clicking the blue button ("Generate template file"). This will prepare a specific input parameter file which will then be placed into the correct directory and can be directly used for further prediction by AMIVA-F

4. Click the red button ("Prediction on pathogenicity") and wait a couple of seconds. In the background, AMIVA-F trains itself with 10x cross validation with additional stratification (details can be seen later in the Trainingset info section of the neighbouring button). This process takes a couple of seconds but afterwards you should see the following entries:

More information can be found at the full tutorial inside the package.