
Introduction
============
What is PRESCOTT?
-----------------

PRESCOTT (PRESCOTT: Population awaRe Epistatic and StruCtural mOdel of muTational effecTs) is a package predicting mutational effects in a protein based
on population, evolutionary and structural information. It is made up of
two main programs: escott and prescott.

ESCOTT can calculate effects of single point mutations and multiple
point mutations. On the other hand, PRESCOTT incorporates population
frequencies into ESCOTT predictions. Therefore, you need to run ESCOTT
first to have predictions of mutational effects. We recommend using
PRESCOTT package via our web site or our docker image due to its
dependencies.

Input Data Requirements
-----------------------

Input Data Requirements for escott
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

escott requires two files:

* a multiple sequence alignment (MSA) file in fasta format (mandatory):

  * your query protein must be the first sequence in the fasta file. In addition, the query sequence should not contain any gaps. 


* a structure file in PDB format (optional but highly recommended).

One of the fastest ways to obtain both input MSA and a PDB file is to
run colabfold:
https://colab.research.google.com/github/sokrypton/ColabFold/blob/main/AlphaFold2.ipynb

Please note that the MSA file produced by colabfold (a3m file) can
contain gaps in the query sequence. You have to remove them before using
it in PRESCOTT. You can remove the gaps with programs that have a GUI,
such as ugene (http://ugene.net/) or jalview (https://www.jalview.org/).

For testing purpose, you can find some example input files for BLAT
protein in data/ folder of this repository. 

Input Data Requirements for prescott
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

prescott requires three files:

* output file of escott (the file ending with …normPredCombi.txt) 
* a fasta file containing only your query sequence 
* gnomad csv file containing to be downloaded from https://gnomad.broadinstitute.org/ for your protein.

Usage
-----

You can find example bash scripts for escott and prescott in examples
folder of this repository.

Below, you will find examples of the most basic usage. Consult to the
documentation for further details.

Running the escott program
~~~~~~~~~~~~~~~~~~~~~~~~~~

Let’s assume that our input MSA is inputAli.fasta and input.pdb is our
structure file in PDB format.

Run the program by issuing the following command in a bash terminal:

.. code:: bash

   escott inputAli.fasta --pdbfile input.pdb 

A quick help can be accessed by typing

.. code:: bash

   escott --help

By default, ESCOTT will predict the effect of all possible single
mutations at all positions in the query sequence. Alternatively, a set
of single or multiple mutations can be given with the option -m. Each
line of the file should contain a mutation (e.g. D136R) or combination
of mutations separated by colons and ordered according to their
positions in the sequence (e.g. D136R,V271A).

Running the prescott program
~~~~~~~~~~~~~~~~~~~~~~~~~~~~

A quick help can be accessed by typing

.. code:: bash

   prescott --help

Run the program by issuing the following command in a bash terminal:

.. code:: bash

   prescott -e ../data/MLH1_normPred_evolCombi.txt -g ../data/gnomAD_v4.0.0_MLH1_HUMAN_ENSG00000076242.csv -s ../data/MLH1.fasta

GnomAD v4.0.0 is the most comprehensive, publicly available human population dataset as far as we know. However,
if you would like to use GnomAD v2.1.1, you should specify the version with '--gnomadversion' parameter as below:

.. code:: bash

   prescott -e ../data/MLH1_normPred_evolCombi.txt -g ../data/gnomAD_v2.1.1_MLH1_HUMAN_ENSG00000076242.csv -s ../data/MLH1.fasta --gnomadversion 2

The most important output is prescott-scores.csv file, which produces entire single point mutational landscape for the protein. 

In addition, there is a file called prescott-scores-details.csv. The file contains all information about the points modulated by population 
information coming from gnomad file and non-modulated variants. 

Finally, if you have both pathogenic and benign labels in the gnomad file, there will be a 'clinvar-vs-position.png' file showing how these labeled 
variants are affected by population information. 

Please note that the example input files of MLH1 protein for prescott acalculations are in the data directory of this repository.

Installation
------------

PRESCOTT is implemented in Python 3 and R. It has been tested only on
Linux. Since PRESCOTT has many dependencies, we recommend using our web
site or our docker image. If you are a determined user, you can find the
steps required to install it from the source in the following link (or
in the docs folder of this repository):

Citation
--------

Mustafa Tekpinar, Laurent David, Thomas Henry, Alessandra Carbone. PRESCOTT: a population aware, epistatic and structural model accurately predicts missense effect. 

.. |License: MIT| image:: https://img.shields.io/badge/License-MIT-yellow.svg
   :target: https://opensource.org/licenses/MIT

