Difference between revisions of "Docking Analysis in DOCK3.8"

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# add the new python 3.8 executable to your path to use
 
# add the new python 3.8 executable to your path to use
export PATH=$PATH:$MY_SOFT/python-3.8-install/bin</nowiki>
+
export PATH=$PATH:$MY_SOFT/python-3.8-install/bin
  
 
# optional: clean up the configuration files
 
# optional: clean up the configuration files
 
# rm -r $MY_SOFT/Python-3.8.8.tgz
 
# rm -r $MY_SOFT/Python-3.8.8.tgz
# rm Python-3.8.8.tgz
+
# rm Python-3.8.8.tgz</nowiki>
  
 
== Scripts Description ==
 
== Scripts Description ==

Revision as of 00:48, 27 April 2021

Location of new scripts/Install Instructions

/wynton/home/btingle/bin/top_poses

All programs described are located on this directory for now. Copy the directory to your own $HOME or wherever you see fit. You can also retrieve these scripts from the DOCK 3.8 repository @ https://github.com/docking-org/DOCK/tree/dev

git clone https://github.com/docking-org/DOCK.git
cd DOCK
git checkout dev

The scripts are located @ analysis/top_poses in the DOCK repository.

Note the link to python3.8 in this directory. You need to include a link to a python3.8 executable in your personal bin directory. This needs to be a link, you cannot copy the executable- it expects to be installed in particular directory. There are no pip requirements, just a blank python 3.8 install. You can also just use mine @ /wynton/home/btingle/soft/python-3.8-install/bin/python3.8

If you want to install python3.8 to your own directory, you will want to follow these instructions:

wget https://www.python.org/ftp/python/3.8.8/Python-3.8.8.tgz

# MY_SOFT is the directory you want to install to
tar -C $MY_SOFT -xzf Python-3.8.8.tgz
pushd $MY_SOFT/Python-3.8.8
./configure --prefix=$MY_SOFT
popd

# add the new python 3.8 executable to your path to use
export PATH=$PATH:$MY_SOFT/python-3.8-install/bin

# optional: clean up the configuration files
# rm -r $MY_SOFT/Python-3.8.8.tgz
# rm Python-3.8.8.tgz

Scripts Description

top_poses.py

Description

Main pose retrieval algorithm, runs on multiple cores. 7 cores is recommended and also the default.

Input can be a directory or a file. If input is a directory, the script will use a recursive find command to locate all test.mol2.gz* files residing in the directory structure.

If input is a file, each line in the file should map to a valid pose file, e.g:

/wynton/group/bks/work/yingyang/5HT-1d/04_LSD/run_dock_es1.5_ld0.3/docked_chunks/chunk0000/test.mol2.gz
/wynton/group/bks/work/yingyang/5HT-1d/04_LSD/run_dock_es1.5_ld0.3/docked_chunks/chunk0001/test.mol2.gz
/wynton/group/bks/work/yingyang/5HT-1d/04_LSD/run_dock_es1.5_ld0.3/docked_chunks/chunk0002/test.mol2.gz
/wynton/group/bks/work/yingyang/5HT-1d/04_LSD/run_dock_es1.5_ld0.3/docked_chunks/chunk0003/test.mol2.gz
/wynton/group/bks/work/yingyang/5HT-1d/04_LSD/run_dock_es1.5_ld0.3/docked_chunks/chunk0004/test.mol2.gz
/wynton/group/bks/work/yingyang/5HT-1d/04_LSD/run_dock_es1.5_ld0.3/docked_chunks/chunk0005/test.mol2.gz
/wynton/group/bks/work/yingyang/5HT-1d/04_LSD/run_dock_es1.5_ld0.3/docked_chunks/chunk0006/test.mol2.gz
/wynton/group/bks/work/yingyang/5HT-1d/04_LSD/run_dock_es1.5_ld0.3/docked_chunks/chunk0007/test.mol2.gz
/wynton/group/bks/work/yingyang/5HT-1d/04_LSD/run_dock_es1.5_ld0.3/docked_chunks/chunk0008/test.mol2.gz
/wynton/group/bks/work/yingyang/5HT-1d/04_LSD/run_dock_es1.5_ld0.3/docked_chunks/chunk0009/test.mol2.gz

Output is where the top 300K poses will be written out when the script has finished. e.g /scratch/top_poses.mol2.gz

Usage

python3.8 top_poses.py <input> <output> <<ncores>>

run_top_poses.bash

Description

Wrapper script for top_poses.py, can be used to submit individual pose jobs. Will run with 7 cores allocated.

Usage

run_top_poses.bash <input> <output>

Typical qsub usage

qsub -wd $PWD run_top_poses.bash <input> <output>

run_top_poses_mr.bash

Description

Map-reduce script to submit a number of analysis jobs and combine their results. The preferred method of running large analysis workloads.

Input field is evaluated the same as in top_poses.py.

Staging directory should be an NFS directory writable by your user. This is where input/output will be stored by the script.

Final output will show up in <staging directory>/output_final.poses.mol2.gz

Batch size refers to how many poses files will be evaluated by each job, the default is 1000, though you may want to modify this depending on the properties of your poses files/how many there are.

Only works on sge for right now. Tested on Wynton.

Usage

run_top_poses_mr.bash <input> <staging directory> <<batch size>>

Checking Logs

After your jobs have finished, check the logs to see if anything went wrong.

<staging directory>/logs

If everything went smoothly, there should be an output file corresponding to each input file, there should be nothing in the .err logs, and each .out log should end with a string of text that looks like this:

received all input!
joining threads...
done processing! writing out...
299900 / 300000

If you find an output file that doesn't end like this, you may wish to re-attempt that particular job.

If you submitted with run_top_poses_mr.bash, all you need to do is to run it again with the same parameters as before. The script detects existing output and will only re-submit as necessary. This will also update the output_final.poses.mol2.gz file.

You may also see a message that looks like this:

short timeout reached while retrieving pose... trying again! curr=...

This just indicates slowness in the file reading, and is common to see at the beginning of a log or when the filesystem is under high load.