Commit 3509620e by Mustafa Tekpinar

Updated the documentation.

parent 7298ac7d
...@@ -85,10 +85,27 @@ if ((normWeightMode=="max")){ ...@@ -85,10 +85,27 @@ if ((normWeightMode=="max")){
} }
} }
}else if (normWeightMode=="tjetormax"){
print("Using tjetormax")
for (row in 1:nrow(jet)) {
if(sum(colnames(jet)=="traceMax")==1){
if((jet[row, "traceMax"]>jet[row, "pc"]) & (jet[row, "traceMax"]>jet[row, "cv"])){
trace<-append(trace, jet[row, "traceMax"])
}else{
trace<-append(trace, max((jet[row, "traceMax"]+jet[row, "pc"])/2.0, max((jet[row, "traceMax"]+jet[row, "cv"])/2.0, (jet[row, "pc"]+jet[row, "cv"])/2.0 )))
}
}else{
if((jet[row, "trace"]>jet[row, "pc"]) & (jet[row, "trace"]>jet[row, "cv"])){
trace<-append(trace, jet[row, "trace"])
}else{
trace<-append(trace, max((jet[row, "trace"]+jet[row, "pc"])/2.0, max((jet[row, "trace"]+jet[row, "cv"])/2.0, (jet[row, "pc"]+jet[row, "cv"])/2.0 )))
}
}
}
}else{ }else{
print("ERROR: Unknown --normWeightMode selected!") print("ERROR: Unknown --normWeightMode selected!")
print("It can only be 'tjet', 'pc', 'cv',") print("It can only be 'tjet', 'pc', 'cv',")
print("'max' or 'sstjetormax'!") print("'max', 'tjetormax' or 'sstjetormax'!")
} }
print(trace) print(trace)
##################################################################################################################### #####################################################################################################################
......
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\ No newline at end of file
Using ESGEMME via Docker
========================
Requirements
------------
You need to have docker installed on your machine. You can consult the
following page for this: https://docs.docker.com/get-docker/
I am assuming some basic familiarity with Linux/Unix/MacOS terminal
commands.
Let’s start our favorite terminal app.
You must to create a folder called docker-tutorial and go to that empty
folder:
.. code:: bash
mkdir docker-tutorial
cd docker-tutorial
Getting the input data
----------------------
Let’s download the sample data provided in the ESGEMME repository for
this exercise. First, we will download the multiple sequence alignment
file in fasta format:
.. code:: bash
wget http://gitlab.lcqb.upmc.fr/tekpinar/ESGEMME/blob/master/data/aliBLAT.fasta
If you don’t have wget, you can try the same command with curl:
.. code:: bash
curl http://gitlab.lcqb.upmc.fr/tekpinar/ESGEMME/blob/master/data/aliBLAT.fasta
Please verify that the aliBLAT.fasta file is in the folder.
Now, we will download the PDB (Protein Databank) file for BLAT:
.. code:: bash
wget http://gitlab.lcqb.upmc.fr/tekpinar/ESGEMME/blob/master/data/blat-af2.pdb
Single point mutation calculations
----------------------------------
In order to make sure that the docker is installed:
.. code:: bash
sudo docker -h
If it shows you a list of options, you are on a good track. On MacOS,
you may not need ‘sudo’ word before the docker command at all.
.. code:: bash
sudo docker run -ti --rm --mount type=bind,source=$PWD,target=/home/tekpinar/research/myexample \
tekpinar/esgemme-docker:v1.3.0
You are in the container (your virtual operating system) now. You
created a folder called myexample in your container with the previous
command. Let’s change to that folder.
.. code:: bash
cd ../myexample/
When you check the data in that folder with ‘ls’ command, you are
supposed to see aliBLAT.fasta and blat-af2.pdb files. Basically, your
docker-tutorial folder on the host system and myexample folder on the
docker container are pointing to the same place.
Obtaining the entire single point mutation landscape
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
In this step, we will use only evolutionary information from an MSA file:
.. code:: bash
python $ESGEMME_PATH/esgemme.py aliBLAT.fasta -r input -f aliBLAT.fasta
After a few minutes of calculation, you must see at least two files named
BLAT_normPred_evolCombi.txt and BLAT_normPred_evolCombi.png. You have
the entire single point mutational landscape of BLAT protein in these
files.
If you want to utilize structural information (highly recommended) as well as
evolutionary information:
.. code:: bash
python $ESGEMME_PATH/esgemme.py aliBLAT.fasta -r input -f aliBLAT.fasta \
--pdbfile blat-af2.pdb \
--normweightmode sstjetormax
Obtaining the effect of a subset of single point mutations
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
If you are interested in only a bunch of single point mutations,
you have to prepare a mut file. The format is a simple text file and
each line contains a single point mutation such as D26A....
Fortunately, we have an example mut in data folder of ESGEMME repository.
.. code:: bash
wget http://gitlab.lcqb.upmc.fr/tekpinar/ESGEMME/raw/master/data/Stiffler_2015_BLAT_ECOLX.mut
Similar to the previous step, there are two possible ways to do the calculations: with or without
structural information. First, without structural information:
.. code:: bash
python $ESGEMME_PATH/esgemme.py aliBLAT.fasta -r input -f aliBLAT.fasta \
-m Stiffler_2015_BLAT_ECOLX.mut
You can include structural information in the following way:
.. code:: bash
python $ESGEMME_PATH/esgemme.py aliBLAT.fasta -r input -f aliBLAT.fasta \
--pdbfile blat-af2.pdb \
--normweightmode sstjetormax \
-m Stiffler_2015_BLAT_ECOLX.mut
You will have BLAT_normPred_evolCombi.txt file in your folder. However, the output
format is completely different from the entire mutational landscape scanning file.
Each line of this file is a mutation and its predicted effect separated by a space.
In addition, you won't have a png file like in the previous case.
Multiple point mutation calculations
------------------------------------
Sometimes, we need to see effects of double or triple mutations. ESGEMME can
perform calculations if you provide a mut file. In this case, the mut file must
have the following format:
.. code:: bash
E26D:Y44R
E56N:A77F:H94V
The first line of the text file is impact of a double mutations and the second
line is the impact of the triple mutations. As you can see, the mutations are
separated by a colon(:) character.
The output file will be in a similar format. Each line will contain the multiple
mutation and its predicted effect, separated by a space.
Running several jobs using docker
---------------------------------
.. esgemme documentation master file, created by
sphinx-quickstart on Fri May 5 13:52:13 2023.
You can adapt this file completely to your liking, but it should at least
contain the root `toctree` directive.
Welcome to esgemme's documentation!
===================================
.. toctree::
:maxdepth: 2
:caption: Contents:
docker.rst
analysis.rst
installation.rst
Indices and tables
==================
* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`
/* This file intentionally left blank. */
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This source diff could not be displayed because it is too large. You can view the blob instead.
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\FNH@H@@footnotetext{\unvbox\FNH@notes}%
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}%
\def\FNH@footnote@envname {footnote}%
\def\FNH@footnotetext@envname{footnotetext}%
\def\FNH@footnote{%
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\FNH@startfntext
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# Sphinx build info version 1 # Sphinx build info version 1
# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done. # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
config: 2b63f8059aa2ad903c52bf6ea56d7c9d config: 1d56d17901c6f429146d20c07a73dc21
tags: 645f666f9bcd5a90fca523b33c5a78b7 tags: 645f666f9bcd5a90fca523b33c5a78b7
...@@ -12,7 +12,7 @@ commands. ...@@ -12,7 +12,7 @@ commands.
Let’s start our favorite terminal app. Let’s start our favorite terminal app.
You must to create a folder called docker-tutorial and go to that empty You must create a folder called docker-tutorial and go to that empty
folder: folder:
.. code:: bash .. code:: bash
...@@ -20,8 +20,8 @@ folder: ...@@ -20,8 +20,8 @@ folder:
mkdir docker-tutorial mkdir docker-tutorial
cd docker-tutorial cd docker-tutorial
Getting the input data Getting the example input data
---------------------- ------------------------------
Let’s download the sample data provided in the ESGEMME repository for Let’s download the sample data provided in the ESGEMME repository for
this exercise. First, we will download the multiple sequence alignment this exercise. First, we will download the multiple sequence alignment
...@@ -45,21 +45,22 @@ Now, we will download the PDB (Protein Databank) file for BLAT: ...@@ -45,21 +45,22 @@ Now, we will download the PDB (Protein Databank) file for BLAT:
wget http://gitlab.lcqb.upmc.fr/tekpinar/ESGEMME/blob/master/data/blat-af2.pdb wget http://gitlab.lcqb.upmc.fr/tekpinar/ESGEMME/blob/master/data/blat-af2.pdb
Running a calculation for a single sequence/protein Single point mutation calculations
--------------------------------------------------- ----------------------------------
In order to make sure that the docker is installed: In order to make sure that the docker is installed:
.. code:: bash .. code:: bash
docker -h sudo docker -h
If it shows you a list of options, you are on a good track. On MacOS, If it shows you a list of options, you are on a good track. On MacOS,
you may not need ‘sudo’ word before the docker command at all. you may not need ‘sudo’ word before the docker command at all.
.. code:: bash .. code:: bash
sudo docker run -ti --rm --mount type=bind,source=$PWD,target=/home/tekpinar/research/myexample tekpinar/esgemme-docker:v1.3.0 sudo docker run -ti --rm --mount type=bind,source=$PWD,target=/home/tekpinar/research/myexample \
tekpinar/esgemme-docker:v1.3.0
You are in the container (your virtual operating system) now. You You are in the container (your virtual operating system) now. You
created a folder called myexample in your container with the previous created a folder called myexample in your container with the previous
...@@ -74,16 +75,77 @@ supposed to see aliBLAT.fasta and blat-af2.pdb files. Basically, your ...@@ -74,16 +75,77 @@ supposed to see aliBLAT.fasta and blat-af2.pdb files. Basically, your
docker-tutorial folder on the host system and myexample folder on the docker-tutorial folder on the host system and myexample folder on the
docker container are pointing to the same place. docker container are pointing to the same place.
One last step and we are done: Obtaining the entire single point mutation landscape
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
In this step, we will use only evolutionary information from an MSA file:
.. code:: bash .. code:: bash
python $ESGEMME_PATH/esgemme.py aliBLAT.fasta -r input -f aliBLAT.fasta --pdbfile blat-af2.pdb python $ESGEMME_PATH/esgemme.py aliBLAT.fasta -r input -f aliBLAT.fasta
After a few minutes of calculation, you must see two files named After a few minutes of calculation, you must see at least two files named
BLAT_normPred_evolCombi.txt and BLAT_normPred_evolCombi.png. You have BLAT_normPred_evolCombi.txt and BLAT_normPred_evolCombi.png. You have
the entire single point mutational landscape of BLAT protein in these the entire single point mutational landscape of BLAT protein in these
files. files.
If you want to utilize structural information (highly recommended) as well as
evolutionary information:
.. code:: bash
python $ESGEMME_PATH/esgemme.py aliBLAT.fasta -r input -f aliBLAT.fasta \
--pdbfile blat-af2.pdb \
--normweightmode sstjetormax
Predicting the effect of a subset of single point mutations
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
If you are interested in only a bunch of single point mutations,
you have to prepare a mut file. The format is a simple text file and
each line contains a single point mutation such as D26A....
Fortunately, we have an example mut in data folder of ESGEMME repository.
.. code:: bash
wget http://gitlab.lcqb.upmc.fr/tekpinar/ESGEMME/raw/master/data/Stiffler_2015_BLAT_ECOLX.mut
Similar to the previous step, there are two possible ways to do the calculations: with or without
structural information. First, let's do it without structural information:
.. code:: bash
python $ESGEMME_PATH/esgemme.py aliBLAT.fasta -r input -f aliBLAT.fasta \
-m Stiffler_2015_BLAT_ECOLX.mut
You can include structural information in the following way:
.. code:: bash
python $ESGEMME_PATH/esgemme.py aliBLAT.fasta -r input -f aliBLAT.fasta \
--pdbfile blat-af2.pdb \
--normweightmode sstjetormax \
-m Stiffler_2015_BLAT_ECOLX.mut
You will have BLAT_normPred_evolCombi.txt file in your folder. However, the output
format is completely different from the entire mutational landscape scanning file.
Each line of this file is a mutation and its predicted effect separated by a space.
In addition, you won't have a png file like in the previous case.
Multiple point mutation calculations
------------------------------------
Sometimes, we need to see effects of double or triple mutations. ESGEMME can
perform calculations if you provide a mut file. In this case, the mut file must
have the following format:
.. code:: bash
E26D:Y44R
E56N:A77F:H94V
The first line of the text file is impact of a double mutation and the second
line is the impact of the triple mutations. As you can see, the mutations are
separated by a colon(:) character.
The output file will be in a similar format. Each line will contain the multiple
mutation and its predicted effect, separated by a space.
Running several jobs using docker Running several jobs using docker
--------------------------------- ---------------------------------
...@@ -11,6 +11,9 @@ Welcome to esgemme's documentation! ...@@ -11,6 +11,9 @@ Welcome to esgemme's documentation!
:caption: Contents: :caption: Contents:
docker.rst docker.rst
analysis.rst
input-preparation.rst
installation.rst
Indices and tables Indices and tables
================== ==================
......
Preparing Your Own Input
========================
Preparing Your Input MSA and PDB with Colabfold
-----------------------------------------------
You have a fasta file for your protein of interest and you want to understand
impact of (certain) mutations.
Before starting, please make sure that your fasta file does not contain a gap.
The quickest method to obtain both multiple sequence alignment and a protein
structure is to use Colabfold. Let's do this step by step:
1. Let's go the Colabfold web site:
https://colab.research.google.com/github/sokrypton/ColabFold/blob/main/AlphaFold2.ipynb
Sign in using your gmail account.
2. Click on the 'Connect' button on the top right hand side.
3. Clean 'query_sequence' box and paste your sequence to the 'query_sequence' box.
For me, I selected adenylate kinase (AKE) as my example fasta sequence
(https://www.rcsb.org/fasta/entry/4AKE/display).
4. Change the 'jobname' to something that makes more sense to you.
5. Go to the menu bar of your 'AlphaFold2.ipynb' notebook, where 'File, Edit,
View, Insert, Runtime, Tools, Help' are listed. Click on the Runtime and
select 'Run all'.
6. This process make take from a few minutes to a few hours depending on your
protein size. It will give you an a3m file and up to 5 PDB models. Put these
files in a clean folder and change the directory to that folder in your
terminal.
7. Unfortunately, a3m file is not in fasta format and it contains gap columns.
We have to clean those gaps. We can do that with a GUI program like Ugene
or Jalview. However, it is a labor intensive procedure. Here, I will use a
small tool that I developed and added to the ESGEMME docker image that I created.
8. Start the docker image with the following command:
.. code:: bash
sudo docker run -ti --rm --mount type=bind,source=$PWD,target=/home/tekpinar/research/myexample \
tekpinar/esgemme-docker:v1.3.0
9. Now, change the directory to myexample folder.
.. code:: bash
cd ../myexample/
ls -l
We are supposed to see our a3m and pdb files in this folder.
10. Let's use a small script from hhsuite to convert a3m file to fasta format.
.. code:: bash
reformat.pl a3m fas AKE.a3m AKE.fasta
11. Final step and we are there:
.. code:: bash
demust removegaps -i AKE.fasta -o AKE_nogaps.fasta
Congratulations! Now, you have all the input files required for ESGEMME:
I. An input MSA: AKE_nogaps.fasta
II. An input PDB: myprotein.pdb
...@@ -9,12 +9,16 @@ steps required to install it from the source. ...@@ -9,12 +9,16 @@ steps required to install it from the source.
Installing the dependencies: Installing the dependencies:
^^^^^^^^^^^^^^^^^^^^^^^^^^^^ ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ESGEMME has the following external dependencies: \* Joint Evolutionary ESGEMME has the following external dependencies:
Trees: http://www.lcqb.upmc.fr/JET2/ and its dependencies: - naccess:
http://www.bioinf.manchester.ac.uk/naccess/ - muscle: * Joint Evolutionary Trees: http://www.lcqb.upmc.fr/JET2/ and its dependencies:
https://www.drive5.com/muscle/ \*\* \* seqinr R package:
https://cran.r-project.org/web/packages/seqinr/index.html \* dssp for * java
secondary structure prediction. * naccess: http://www.bioinf.manchester.ac.uk/naccess/
* muscle: https://www.drive5.com/muscle/
* seqinr R package: https://cran.r-project.org/web/packages/seqinr/index.html
* dssp for secondary structure prediction.
These tools should be installed to be able to use ESGEMME. These tools should be installed to be able to use ESGEMME.
......
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var stopwords = ["a","and","are","as","at","be","but","by","for","if","in","into","is","it","near","no","not","of","on","or","such","that","the","their","then","there","these","they","this","to","was","will","with"]; var stopwords = ["a", "and", "are", "as", "at", "be", "but", "by", "for", "if", "in", "into", "is", "it", "near", "no", "not", "of", "on", "or", "such", "that", "the", "their", "then", "there", "these", "they", "this", "to", "was", "will", "with"];
/* Non-minified version JS is _stemmer.js if file is provided */ /* Non-minified version is copied as a separate JS file, is available */
/** /**
* Porter Stemmer * Porter Stemmer
*/ */
...@@ -196,102 +197,3 @@ var Stemmer = function() { ...@@ -196,102 +197,3 @@ var Stemmer = function() {
} }
} }
var splitChars = (function() {
var result = {};
var singles = [96, 180, 187, 191, 215, 247, 749, 885, 903, 907, 909, 930, 1014, 1648,
1748, 1809, 2416, 2473, 2481, 2526, 2601, 2609, 2612, 2615, 2653, 2702,
2706, 2729, 2737, 2740, 2857, 2865, 2868, 2910, 2928, 2948, 2961, 2971,
2973, 3085, 3089, 3113, 3124, 3213, 3217, 3241, 3252, 3295, 3341, 3345,
3369, 3506, 3516, 3633, 3715, 3721, 3736, 3744, 3748, 3750, 3756, 3761,
3781, 3912, 4239, 4347, 4681, 4695, 4697, 4745, 4785, 4799, 4801, 4823,
4881, 5760, 5901, 5997, 6313, 7405, 8024, 8026, 8028, 8030, 8117, 8125,
8133, 8181, 8468, 8485, 8487, 8489, 8494, 8527, 11311, 11359, 11687, 11695,
11703, 11711, 11719, 11727, 11735, 12448, 12539, 43010, 43014, 43019, 43587,
43696, 43713, 64286, 64297, 64311, 64317, 64319, 64322, 64325, 65141];
var i, j, start, end;
for (i = 0; i < singles.length; i++) {
result[singles[i]] = true;
}
var ranges = [[0, 47], [58, 64], [91, 94], [123, 169], [171, 177], [182, 184], [706, 709],
[722, 735], [741, 747], [751, 879], [888, 889], [894, 901], [1154, 1161],
[1318, 1328], [1367, 1368], [1370, 1376], [1416, 1487], [1515, 1519], [1523, 1568],
[1611, 1631], [1642, 1645], [1750, 1764], [1767, 1773], [1789, 1790], [1792, 1807],
[1840, 1868], [1958, 1968], [1970, 1983], [2027, 2035], [2038, 2041], [2043, 2047],
[2070, 2073], [2075, 2083], [2085, 2087], [2089, 2307], [2362, 2364], [2366, 2383],
[2385, 2391], [2402, 2405], [2419, 2424], [2432, 2436], [2445, 2446], [2449, 2450],
[2483, 2485], [2490, 2492], [2494, 2509], [2511, 2523], [2530, 2533], [2546, 2547],
[2554, 2564], [2571, 2574], [2577, 2578], [2618, 2648], [2655, 2661], [2672, 2673],
[2677, 2692], [2746, 2748], [2750, 2767], [2769, 2783], [2786, 2789], [2800, 2820],
[2829, 2830], [2833, 2834], [2874, 2876], [2878, 2907], [2914, 2917], [2930, 2946],
[2955, 2957], [2966, 2968], [2976, 2978], [2981, 2983], [2987, 2989], [3002, 3023],
[3025, 3045], [3059, 3076], [3130, 3132], [3134, 3159], [3162, 3167], [3170, 3173],
[3184, 3191], [3199, 3204], [3258, 3260], [3262, 3293], [3298, 3301], [3312, 3332],
[3386, 3388], [3390, 3423], [3426, 3429], [3446, 3449], [3456, 3460], [3479, 3481],
[3518, 3519], [3527, 3584], [3636, 3647], [3655, 3663], [3674, 3712], [3717, 3718],
[3723, 3724], [3726, 3731], [3752, 3753], [3764, 3772], [3774, 3775], [3783, 3791],
[3802, 3803], [3806, 3839], [3841, 3871], [3892, 3903], [3949, 3975], [3980, 4095],
[4139, 4158], [4170, 4175], [4182, 4185], [4190, 4192], [4194, 4196], [4199, 4205],
[4209, 4212], [4226, 4237], [4250, 4255], [4294, 4303], [4349, 4351], [4686, 4687],
[4702, 4703], [4750, 4751], [4790, 4791], [4806, 4807], [4886, 4887], [4955, 4968],
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[6104, 6107], [6109, 6111], [6122, 6127], [6138, 6159], [6170, 6175], [6264, 6271],
[6315, 6319], [6390, 6399], [6429, 6469], [6510, 6511], [6517, 6527], [6572, 6592],
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[6824, 6916], [6964, 6980], [6988, 6991], [7002, 7042], [7073, 7085], [7098, 7167],
[7204, 7231], [7242, 7244], [7294, 7400], [7410, 7423], [7616, 7679], [7958, 7959],
[7966, 7967], [8006, 8007], [8014, 8015], [8062, 8063], [8127, 8129], [8141, 8143],
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[8330, 8335], [8341, 8449], [8451, 8454], [8456, 8457], [8470, 8472], [8478, 8483],
[8506, 8507], [8512, 8516], [8522, 8525], [8586, 9311], [9372, 9449], [9472, 10101],
[10132, 11263], [11493, 11498], [11503, 11516], [11518, 11519], [11558, 11567],
[11622, 11630], [11632, 11647], [11671, 11679], [11743, 11822], [11824, 12292],
[12296, 12320], [12330, 12336], [12342, 12343], [12349, 12352], [12439, 12444],
[12544, 12548], [12590, 12592], [12687, 12689], [12694, 12703], [12728, 12783],
[12800, 12831], [12842, 12880], [12896, 12927], [12938, 12976], [12992, 13311],
[19894, 19967], [40908, 40959], [42125, 42191], [42238, 42239], [42509, 42511],
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[42784, 42785], [42889, 42890], [42893, 43002], [43043, 43055], [43062, 43071],
[43124, 43137], [43188, 43215], [43226, 43249], [43256, 43258], [43260, 43263],
[43302, 43311], [43335, 43359], [43389, 43395], [43443, 43470], [43482, 43519],
[43561, 43583], [43596, 43599], [43610, 43615], [43639, 43641], [43643, 43647],
[43698, 43700], [43703, 43704], [43710, 43711], [43715, 43738], [43742, 43967],
[44003, 44015], [44026, 44031], [55204, 55215], [55239, 55242], [55292, 55295],
[57344, 63743], [64046, 64047], [64110, 64111], [64218, 64255], [64263, 64274],
[64280, 64284], [64434, 64466], [64830, 64847], [64912, 64913], [64968, 65007],
[65020, 65135], [65277, 65295], [65306, 65312], [65339, 65344], [65371, 65381],
[65471, 65473], [65480, 65481], [65488, 65489], [65496, 65497]];
for (i = 0; i < ranges.length; i++) {
start = ranges[i][0];
end = ranges[i][1];
for (j = start; j <= end; j++) {
result[j] = true;
}
}
return result;
})();
function splitQuery(query) {
var result = [];
var start = -1;
for (var i = 0; i < query.length; i++) {
if (splitChars[query.charCodeAt(i)]) {
if (start !== -1) {
result.push(query.slice(start, i));
start = -1;
}
} else if (start === -1) {
start = i;
}
}
if (start !== -1) {
result.push(query.slice(start));
}
return result;
}
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...@@ -68,8 +74,8 @@ ...@@ -68,8 +74,8 @@
<div role="main" class="document" itemscope="itemscope" itemtype="http://schema.org/Article"> <div role="main" class="document" itemscope="itemscope" itemtype="http://schema.org/Article">
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<div class="section" id="analyzing-the-esgemme-output"> <section id="analyzing-the-esgemme-output">
<h1>Analyzing the ESGEMME output<a class="headerlink" href="#analyzing-the-esgemme-output" title="Permalink to this headline"></a></h1> <h1>Analyzing the ESGEMME output<a class="headerlink" href="#analyzing-the-esgemme-output" title="Permalink to this heading"></a></h1>
<p>By default, ESGEMME will output the following files: * <p>By default, ESGEMME will output the following files: *
myProt_normPred_evolEpi.txt * myProt_normPred_evolInd.txt * myProt_normPred_evolEpi.txt * myProt_normPred_evolInd.txt *
myProt_normPred_evolCombi.txt</p> myProt_normPred_evolCombi.txt</p>
...@@ -80,13 +86,14 @@ query sequence. If the user provides her/his own list of mutations, then ...@@ -80,13 +86,14 @@ query sequence. If the user provides her/his own list of mutations, then
only the global epistatic model will be run and the output file will only the global epistatic model will be run and the output file will
contain 2 columns, the first one with the mutations, the second one with contain 2 columns, the first one with the mutations, the second one with
the normalized predicted effects.</p> the normalized predicted effects.</p>
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<li class="toctree-l1 current"><a class="current reference internal" href="#">Preparing Your Own Input</a><ul>
<li class="toctree-l2"><a class="reference internal" href="#preparing-your-input-msa-and-pdb-with-colabfold">Preparing Your Input MSA and PDB with Colabfold</a></li>
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<section id="preparing-your-own-input">
<h1 id="index">Index</h1> <h1>Preparing Your Own Input<a class="headerlink" href="#preparing-your-own-input" title="Permalink to this heading"></a></h1>
<section id="preparing-your-input-msa-and-pdb-with-colabfold">
<div class="genindex-jumpbox"> <h2>Preparing Your Input MSA and PDB with Colabfold<a class="headerlink" href="#preparing-your-input-msa-and-pdb-with-colabfold" title="Permalink to this heading"></a></h2>
<p>You have a fasta file for your protein of interest and you want to understand
impact of (certain) mutations.
Before starting, please make sure that your fasta file does not contain a gap.
The quickest method to obtain both multiple sequence alignment and a protein
structure is to use Colabfold. Let’s do this step by step:</p>
<ol class="arabic">
<li><p>Let’s go the Colabfold web site:</p>
<p><a class="reference external" href="https://colab.research.google.com/github/sokrypton/ColabFold/blob/main/AlphaFold2.ipynb">https://colab.research.google.com/github/sokrypton/ColabFold/blob/main/AlphaFold2.ipynb</a></p>
<p>Sign in using your gmail account.</p>
</li>
<li><p>Click on the ‘Connect’ button on the top right hand side.</p></li>
<li><p>Clean ‘query_sequence’ box and paste your sequence to the ‘query_sequence’ box.
For me, I selected adenylate kinase (AKE) as my example fasta sequence
(<a class="reference external" href="https://www.rcsb.org/fasta/entry/4AKE/display">https://www.rcsb.org/fasta/entry/4AKE/display</a>).</p></li>
<li><p>Change the ‘jobname’ to something that makes more sense to you.</p></li>
<li><p>Go to the menu bar of your ‘AlphaFold2.ipynb’ notebook, where ‘File, Edit,
View, Insert, Runtime, Tools, Help’ are listed. Click on the Runtime and
select ‘Run all’.</p></li>
<li><p>This process make take from a few minutes to a few hours depending on your
protein size. It will give you an a3m file and up to 5 PDB models. Put these
files in a clean folder and change the directory to that folder in your
terminal.</p></li>
<li><p>Unfortunately, a3m file is not in fasta format and it contains gap columns.
We have to clean those gaps. We can do that with a GUI program like Ugene
or Jalview. However, it is a labor intensive procedure. Here, I will use a
small tool that I developed and added to the ESGEMME docker image that I created.</p></li>
<li><p>Start the docker image with the following command:</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>sudo<span class="w"> </span>docker<span class="w"> </span>run<span class="w"> </span>-ti<span class="w"> </span>--rm<span class="w"> </span>--mount<span class="w"> </span><span class="nv">type</span><span class="o">=</span>bind,source<span class="o">=</span><span class="nv">$PWD</span>,target<span class="o">=</span>/home/tekpinar/research/myexample<span class="w"> </span><span class="se">\</span>
tekpinar/esgemme-docker:v1.3.0
</pre></div>
</div>
</li>
<li><p>Now, change the directory to myexample folder.</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span><span class="nb">cd</span><span class="w"> </span>../myexample/
ls<span class="w"> </span>-l
</pre></div>
</div>
<p>We are supposed to see our a3m and pdb files in this folder.</p>
</li>
<li><p>Let’s use a small script from hhsuite to convert a3m file to fasta format.</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>reformat.pl<span class="w"> </span>a3m<span class="w"> </span>fas<span class="w"> </span>AKE.a3m<span class="w"> </span>AKE.fasta
</pre></div>
</div> </div>
</li>
<li><p>Final step and we are there:</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>demust<span class="w"> </span>removegaps<span class="w"> </span>-i<span class="w"> </span>AKE.fasta<span class="w"> </span>-o<span class="w"> </span>AKE_nogaps.fasta
</pre></div>
</div>
</li>
</ol>
<p>Congratulations! Now, you have all the input files required for ESGEMME:
I. An input MSA: AKE_nogaps.fasta
II. An input PDB: myprotein.pdb</p>
</section>
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<p class="caption"><span class="caption-text">Contents:</span></p> <p class="caption" role="heading"><span class="caption-text">Contents:</span></p>
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<li class="toctree-l1"><a class="reference internal" href="docker.html">Using ESGEMME via Docker</a></li> <li class="toctree-l1"><a class="reference internal" href="docker.html">Using ESGEMME via Docker</a></li>
<li class="toctree-l1"><a class="reference internal" href="analysis.html">Analyzing the ESGEMME output</a></li> <li class="toctree-l1"><a class="reference internal" href="analysis.html">Analyzing the ESGEMME output</a></li>
<li class="toctree-l1"><a class="reference internal" href="input-preparation.html">Preparing Your Own Input</a></li>
<li class="toctree-l1 current"><a class="current reference internal" href="#">Installation</a><ul> <li class="toctree-l1 current"><a class="current reference internal" href="#">Installation</a><ul>
<li class="toctree-l2"><a class="reference internal" href="#installing-the-dependencies">Installing the dependencies:</a></li> <li class="toctree-l2"><a class="reference internal" href="#installing-the-dependencies">Installing the dependencies:</a></li>
<li class="toctree-l2"><a class="reference internal" href="#getting-the-source-code-and-preparing-the-environment">Getting the source code and preparing the environment:</a></li> <li class="toctree-l2"><a class="reference internal" href="#getting-the-source-code-and-preparing-the-environment">Getting the source code and preparing the environment:</a></li>
...@@ -74,45 +78,51 @@ ...@@ -74,45 +78,51 @@
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<div class="section" id="installation"> <section id="installation">
<h1>Installation<a class="headerlink" href="#installation" title="Permalink to this headline"></a></h1> <h1>Installation<a class="headerlink" href="#installation" title="Permalink to this heading"></a></h1>
<p>ESGEMME is implemented in Python 3 and R. It has been tested only on <p>ESGEMME is implemented in Python 3 and R. It has been tested only on
Linux. Since ESGEMME has many dependencies, we recommend using our web Linux. Since ESGEMME has many dependencies, we recommend using our web
site or our docker image. If you are a determined user, here comes the site or our docker image. If you are a determined user, here comes the
steps required to install it from the source.</p> steps required to install it from the source.</p>
<div class="section" id="installing-the-dependencies"> <section id="installing-the-dependencies">
<h2>Installing the dependencies:<a class="headerlink" href="#installing-the-dependencies" title="Permalink to this headline"></a></h2> <h2>Installing the dependencies:<a class="headerlink" href="#installing-the-dependencies" title="Permalink to this heading"></a></h2>
<p>ESGEMME has the following external dependencies: * Joint Evolutionary <p>ESGEMME has the following external dependencies:</p>
Trees: <a class="reference external" href="http://www.lcqb.upmc.fr/JET2/">http://www.lcqb.upmc.fr/JET2/</a> and its dependencies: - naccess: <ul class="simple">
<a class="reference external" href="http://www.bioinf.manchester.ac.uk/naccess/">http://www.bioinf.manchester.ac.uk/naccess/</a> - muscle: <li><p>Joint Evolutionary Trees: <a class="reference external" href="http://www.lcqb.upmc.fr/JET2/">http://www.lcqb.upmc.fr/JET2/</a> and its dependencies:</p>
<a class="reference external" href="https://www.drive5.com/muscle/">https://www.drive5.com/muscle/</a> ** * seqinr R package: <ul>
<a class="reference external" href="https://cran.r-project.org/web/packages/seqinr/index.html">https://cran.r-project.org/web/packages/seqinr/index.html</a> * dssp for <li><p>java</p></li>
secondary structure prediction.</p> <li><p>naccess: <a class="reference external" href="http://www.bioinf.manchester.ac.uk/naccess/">http://www.bioinf.manchester.ac.uk/naccess/</a></p></li>
<li><p>muscle: <a class="reference external" href="https://www.drive5.com/muscle/">https://www.drive5.com/muscle/</a></p></li>
</ul>
</li>
<li><p>seqinr R package: <a class="reference external" href="https://cran.r-project.org/web/packages/seqinr/index.html">https://cran.r-project.org/web/packages/seqinr/index.html</a></p></li>
<li><p>dssp for secondary structure prediction.</p></li>
</ul>
<p>These tools should be installed to be able to use ESGEMME.</p> <p>These tools should be installed to be able to use ESGEMME.</p>
</div> </section>
<div class="section" id="getting-the-source-code-and-preparing-the-environment"> <section id="getting-the-source-code-and-preparing-the-environment">
<h2>Getting the source code and preparing the environment:<a class="headerlink" href="#getting-the-source-code-and-preparing-the-environment" title="Permalink to this headline"></a></h2> <h2>Getting the source code and preparing the environment:<a class="headerlink" href="#getting-the-source-code-and-preparing-the-environment" title="Permalink to this heading"></a></h2>
<p>Download the ESGEMME source code from <p>Download the ESGEMME source code from
<a class="reference external" href="http://gitlab.lcqb.upmc.fr/tekpinar/ESGEMME">http://gitlab.lcqb.upmc.fr/tekpinar/ESGEMME</a>. Define and export the <a class="reference external" href="http://gitlab.lcqb.upmc.fr/tekpinar/ESGEMME">http://gitlab.lcqb.upmc.fr/tekpinar/ESGEMME</a>. Define and export the
environment variable ESGEMME_PATH=/path-to-ESGEMME-directory/</p> environment variable ESGEMME_PATH=/path-to-ESGEMME-directory/</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span><span class="nb">export</span> <span class="nv">ESGEMME_PATH</span><span class="o">=</span>/path-to-ESGEMME-directory/ <div class="highlight-bash notranslate"><div class="highlight"><pre><span></span><span class="nb">export</span><span class="w"> </span><span class="nv">ESGEMME_PATH</span><span class="o">=</span>/path-to-ESGEMME-directory/
</pre></div> </pre></div>
</div> </div>
</div> </section>
<div class="section" id="configuring-default-conf-file"> <section id="configuring-default-conf-file">
<h2>Configuring default.conf file<a class="headerlink" href="#configuring-default-conf-file" title="Permalink to this headline"></a></h2> <h2>Configuring default.conf file<a class="headerlink" href="#configuring-default-conf-file" title="Permalink to this heading"></a></h2>
<p>Inside ESGEMME folder, there is an important file called default.conf. <p>Inside ESGEMME folder, there is an important file called default.conf.
This file contains essential parameters of ESGEMME, such as paths of This file contains essential parameters of ESGEMME, such as paths of
external parts, default internal parameters. etc. You have to correct the Software section of this external parts, default internal parameters. etc. You have to correct the Software section of this
file according to your system.</p> file according to your system.</p>
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