luquelab · anuradha1901 · Oct 27, 2021 · Oct 27, 2021 · Oct 27, 2021 · Oct 27, 2021
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diff --git a/docs/courses/CSRC cluster/PBS_torque.md b/docs/courses/CSRC cluster/PBS_torque.md
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+---
+layout: default
+title: Job Submission on Cinci 
+nav_order: 1
+parent: CSRC cluster
+grand_parent: Lab Documentation
+---
+
+# Job Submission on Cinci 
+
+The Cinci server used at the Luque Lab uses PBS (Portable Batch System) Torque which is a resource management system for submitting and controlling jobs on supercomputers, clusters and grids. 
+
+The Cinci server has 20 compute nodes - node 1 through node 20 amongst which 4 are higher performance/memorgy compute nodes - node 17 through node 20. Nodes 1 through 16 have 16 processors each and nodes 17 through 20 have 24 processors each. 
+
+Job submission is accomplished using the qsub command. The PBS command file is specified as a filename on the qsub command line. Once we submit a script via qsub which is then sent to the scheduling system. The scheduler will then find free resources and run the script on an available node.
+
+The resource requests can be made using either the script or command line arguments.
+
+**Using command line**:
+
+
+```bash
+qsub -l nodes=16
+```
+ Specifies that we are requesting 16 nodes of any type. If the number of nodes are not specified 1 node is taken. 
+
+
+```bash
+qsub -l nodes=16:ppn=24
+```
+Specifies that we are requesting 24 processors on each of the 16 nodes
+
+```bash
+qsub -l nodes=1:ppn=1,pmem=100MB,walltime=5:00
+```
+Specifies that we are requestion one node, one processor on that node, 100 mega bytes per process and a walltime of five minutes. 
+
+**Using scripts**:
+
+```bash
+#PBS -N Name 
+#PBS -l nodes=1:ppn=1,walltime=01:00
+
+echo "Hello World"
+```
+Here we are giving a job name, specifying that we need one processor on 1 node for 1 minute. 
+
+
+A list of other arguments and commands can be found [here](https://www.cqu.edu.au/eresearch/high-performance-computing/hpc-user-guides-and-faqs/pbs-commands).
+
+**Monitoring Jobs**
+
+The qstat command is used to monitor submitted jobs. 
+
+```bash
+qstat -f 
+```
+Specifies that a full status display be written to standard out. The [time] value is the amount of walltime, in seconds, remaining for the job.
+
+More qstat options can be found [here](http://docs.adaptivecomputing.com/torque/3-0-5/commands/qstat.php).
+
+
+**Canceling Jobs**
+
+Submitted jobs can be cancelled using the qdel command. The only parameter is the ID of the job to be canceled. For example if we want to kill the job with an ID 314
+
+```bash
+qdel 314
+```
+
+To delete all the the jobs
+```bash
+qdel all
+```
+
+More qdel options can be found [here](http://docs.adaptivecomputing.com/torque/3-0-5/commands/qdel.php).
diff --git a/docs/courses/CSRC cluster/anaconda_environment.md b/docs/courses/CSRC cluster/anaconda_environment.md
@@ -0,0 +1,50 @@
+---
+layout: default
+title: Entering the conda environment on cinci cluster
+nav_order: 2
+parent: CSRC cluster
+grand_parent: Lab Documentation
+---
+
+# Entering the conda environment on cinci cluster
+
+~~~
+# .bashrc
+# User specific aliases and functions
+alias rm='rm -i'
+alias cp='cp -i'
+alias mv='mv -i'
+~~~
+
+.bashrc initializes an interactive shell session. The bottom three lines are to prompt the user before deletion, overwriting and moving the file.
+
+~~~
+# Source global definitions
+if [ -f /etc/bashrc ]; then
+    . /etc/bashrc
+fi
+
+# added by Anaconda3 5.3.0 installer
+# >>> conda init >>>
+# !! Contents within this block are managed by 'conda init' !!
+__conda_setup="$(CONDA_REPORT_ERRORS=false '/usr/local/anaconda3/bin/conda' shell.bash hook 2> /dev/null)"
+if [ $? -eq 0 ]; then
+    \eval "$__conda_setup"
+else
+    if [ -f "/usr/local/anaconda3/etc/profile.d/conda.sh" ]; then
+        . "/usr/local/anaconda3/etc/profile.d/conda.sh"
+        CONDA_CHANGEPS1=false conda activate base
+    else
+        \export PATH="/usr/local/anaconda3/bin:$PATH"
+    fi
+fi
+unset __conda_setup
+# <<< conda init <<<
+~~~
+
+/etc/bashrc contains system wide funtions and aliases. Environment related files and programs are available in etc/profile. 
+The if .. fi statement is the fundamental control statement that allows shell to make decisions and execute statements conditionally.
+
+
+
+
diff --git a/docs/courses/CSRC cluster/bashrc-ana3.bashrc b/docs/courses/CSRC cluster/bashrc-ana3.bashrc
@@ -0,0 +1,28 @@
+# .bashrc
+
+# User specific aliases and functions
+
+alias rm='rm -i'
+alias cp='cp -i'
+alias mv='mv -i'
+
+# Source global definitions
+if [ -f /etc/bashrc ]; then
+	. /etc/bashrc
+fi
+# added by Anaconda3 5.3.0 installer
+# >>> conda init >>>
+# !! Contents within this block are managed by 'conda init' !!
+__conda_setup="$(CONDA_REPORT_ERRORS=false '/usr/local/anaconda3/bin/conda' shell.bash hook 2> /dev/null)"
+if [ $? -eq 0 ]; then
+    \eval "$__conda_setup"
+else
+    if [ -f "/usr/local/anaconda3/etc/profile.d/conda.sh" ]; then
+        . "/usr/local/anaconda3/etc/profile.d/conda.sh"
+        CONDA_CHANGEPS1=false conda activate base
+    else
+        \export PATH="/usr/local/anaconda3/bin:$PATH"
+    fi
+fi
+unset __conda_setup
+# <<< conda init <<<
diff --git a/docs/courses/CSRC cluster/checkv.md b/docs/courses/CSRC cluster/checkv.md
@@ -0,0 +1,52 @@
+---
+layout: default
+title: Submitting jobs on cinci cluster - CheckV 
+nav_order: 3
+parent: CSRC cluster
+grand_parent: Lab Documentation
+---
+
+# Using qsub to submit bash scripts to run CheckV
+
+The official README for CheckV can be found [here](https://bitbucket.org/berkeleylab/checkv/src/master/).
+
+For this code to run we are assuming that you have bashrc-ana3.bashrc in your home directory.
+
+~~~
+#!/bin/bash
+#PBS -l nodes=2:ppn=24
+#PBS -l walltime=02:00:00
+~~~
+
+The first line us the most common shell used as default shel for user login of the linux system. It is used to instruct the operating system to use bash as a command interpreter. The second ans third lines request resources for the job. This job requests two nodes with 24 ppn (processors per node). This combination would run the job using two of the 12 core 24 thread CPUs on the cinci cluster.
+
+~~~
+cat ${PBS_NODEFILE} 
+~~~
+The nodefile contains a list of all nodes the job has allocated with an entry for every CPU.
+
+~~~
+cd 
+source bashrc-ana3 
+checkv end_to_end input_file.fna output_directory -d location_of_the_databse
+~~~
+The first line is the command which is used to change the current working directory in Linux. The second line is to enter the anaconda environment. The third line is to run CheckV using a single command to run the fill pipeline
+
+Here is an example of how we can do it. 
+~~~
+checkv end_to_end ~/Test_CheckV/Test_sequence.fna ~/Test_CheckV/result -d /usr/local/checkv-db-v1.1
+~~~
+
+Another way to run CheckV using individual commands for each step in the pipeline
+~~~
+checkv contamination input_file.fna output_directory 
+checkv completeness input_file.fna output_directory 
+checkv complete_genomes input_file.fna output_directory
+checkv quality_summary input_file.fna output_directory
+~~~
+
+You can now submit your script as a job using the command:
+~~~
+qsub checkv.sh
+~~~
+
diff --git a/docs/courses/CSRC cluster/checkv.sh b/docs/courses/CSRC cluster/checkv.sh
@@ -0,0 +1,15 @@
+#!/bin/bash
+#PBS -l nodes=2:ppn=24
+#PBS -l walltime=02:00:00
+
+echo "Running on: "
+cat ${PBS_NODEFILE}  # The nodefile contains a list of all nodes the job has allocated with an entry for every CPU
+
+echo
+echo "Program Output begins: "
+
+cd  # going into the home directory
+source bashrc-ana3  # entering the anaconda environment
+checkv end_to_end ~/Test_CheckV/Test_sequence.fna ~/Test_CheckV/result -d /usr/local/checkv-db-v1.1
+
+# checkv end_to_end input_file.fna output_directory -d location_of_the_databse
diff --git a/docs/courses/CSRC cluster/csrc_cluster.md b/docs/courses/CSRC cluster/csrc_cluster.md
@@ -0,0 +1,11 @@
+---
+layout: default
+title: CSRC cluster 
+nav_order: 4
+parent: Lab Documentation
+has_children: true
+---
+
+## CSRC cluster
+
+This website offers comprehensive tutorials on efficiently running programs on the CSRC Cinci Cluster, a powerful multicore CPU cluster. 
diff --git a/docs/courses/CSRC cluster/okular.md b/docs/courses/CSRC cluster/okular.md
@@ -0,0 +1,52 @@
+---
+layout: default
+title: Viewing PDF's on cinci
+nav_order: 5
+parent: CSRC cluster
+grand_parent: Lab Documentation
+---
+
+# Viewing PDF's on the cinci cluster
+
+The cinci cluster uses okular as the document viewer. Following are the steps that need to be followed to use ssh with x11 forwarding be able to access okular.
+
+
+## Accessing okular using Linux/ Mac 
+1. Download and install XQuartz on macOS
+    * XQuartz package can be found [here](https://www.xquartz.org/)
+    * Once this package is downloaded, install the server and follow the instructions provided on the dialogue box to complete the installation process
+    * XQuartz can also be downloaded using the brew command on the terminal
+
+    ``` brew install -cask xquartz```
+
+2. Reboot your mac 
+    * Click on the Apple icon and then restart or use the following command on the terminal 
+
+    ``` sudo reboot ```
+
+3. Log into cinci using the SSH command with -X or -Y  flages
+
+    ```ssh -X user@cinci.sdsu.edu``` or 
+
+    ```ssh -Y user@cinci.sdsu.edu```
+4. Open required file using the following command
+
+    ``` okular path/doc.pdf ```
+
+5. More command line options for okular can be found [here](https://docs.kde.org/stable5/en/okular/okular/command-line-options.html)
+
+
+
+## Accessing okular using Windows
+1. Download and install PuTTY from [here](https://www.chiark.greenend.org.uk/~sgtatham/putty/latest.html)
+2. Create a session under the 'Session' category. Enter 'cinci.sdsu.edu' under 'Host Name' and under 'Saved Sessions'
+3. Select SSH as the Connection type
+4. Click on the 'plus' of the SSH category, select X11, and check 'Enable X11 forwarding'
+5. Select the 'Session' category, and clieck on 'Save'.
+6. Conntect to cinci.sdsu.edu by clicking 'Open'.
+7. Log in using your username and password.
+8. Open required file using the following command
+
+    ``` okular path/doc.pdf ```
+
+9. More command line options for okular can be found [here](https://docs.kde.org/stable5/en/okular/okular/command-line-options.html).
diff --git a/docs/courses/CSRC cluster/pyCapsid.md b/docs/courses/CSRC cluster/pyCapsid.md
@@ -0,0 +1,30 @@
+---
+layout: default
+title: Job Submission on Cinci - pyCapsid
+nav_order: 6
+parent: CSRC cluster
+grand_parent: Lab Documentation
+---
+
+1. The first step to running pyCapsid on the cluster is installing pyCapsid in dedicated conda environment as described in 
+its [installation documentation.](https://luquelab.github.io/pyCapsid/installation/#via-conda) 
+2. Once you've done that, activate the environment using `conda activate` and note the path to the python interpreter of that environment using 
+`type python`. For example:
+![img.png](python_path_example.png)
+3. Create a folder in which you will store the results of pyCapsid. Note the path of the folder using `pwd`.
+4. Inside that folder create a file named `config.toml` or download an example config.toml from [here](https://github.com/luquelab/pyCapsid/blob/main/docs/tutorial/config_simple.toml).
+Adjust the contents of this config file to the desired set of parameters. A more detailed  config file with more of the available options can be found [here](https://github.com/luquelab/pyCapsid/blob/main/docs/tutorial/conf_example.toml).
+5. Next create a python file with your preferred name, i.e. `run_pycap.py`. The contents of that file should look like this:
+    ```python
+    #!/usr/dataB/luquelab/members/ctbrown/miniconda3/envs/pycapsid/bin/python # This is the path to your python interpreter noted in step 2
+    #PBS -l nodes=1:ppn=24 # This requests a single node with 24 processors per node. This corresponds to the 4 higher quality nodes on the CSRC cluster. Remove the ppn requirement to use any node.
+    #PBS -l walltime=18:00:00 # This specifies the maximum time the job will run before being terminated
+    #PBS -d "/usr/dataB/luquelab/members/ctbrown/pyCapsid/pyCapsid/run/" # This specifies the working directory, and should be the directory you created in step 3
+    #PBS -j oe # This combines the standard output and standard error logs
+
+    from pyCapsid import run_capsid_report
+    run_capsid_report('config.toml') # make sure the filename provided here is the same as the config file you created.
+    ```
+6. Check that you set the parameters in `config.toml` correctly and submit the job using `qsub run_pycap.py`.
+7. This will create a folder with the same name that was specified in the config file. You can copy this folder to your 
+local machine using the scp command.
diff --git a/docs/courses/CSRC cluster/python_path_example.png b/docs/courses/CSRC cluster/python_path_example.png
diff --git a/docs/courses/CSRC cluster/vibrant.md b/docs/courses/CSRC cluster/vibrant.md
@@ -0,0 +1,46 @@
+---
+layout: default
+title: Submitting jobs on cinci cluster - VIBRANT 
+nav_order: 4
+parent: CSRC cluster
+grand_parent: Lab Documentation
+---
+
+# Using qsub to submit bash scripts to run VIBRANT
+
+The official README for CheckV can be found [here](https://github.com/AnantharamanLab/VIBRANT).
+
+For this code to run we are assuming that you have bashrc-ana3.bashrc in your home directory.
+
+~~~
+#!/bin/bash
+#PBS -l nodes=2:ppn=24
+#PBS -l walltime=02:00:00
+~~~
+
+The first line us the most common shell used as default shel for user login of the linux system. It is used to instruct the operating system to use bash as a command interpreter. The second ans third lines request resources for the job. This job requests two nodes with 24 ppn (processors per node). This combination would run the job using two of the 12 core 24 thread CPUs on the cinci cluster.
+
+~~~
+cat ${PBS_NODEFILE} 
+~~~
+The nodefile contains a list of all nodes the job has allocated with an entry for every CPU.
+
+~~~
+cd 
+source bashrc-ana3
+cd ../../usr/local/VIBRANT-1.2.1/
+python3 VIBRANT_run.py -i input_file.fna -folder output_directory
+~~~
+The first line is the command which is used to change the current working directory in Linux. The second line is to enter the anaconda environment. The third line is to go to the directory where VIBRANT is installed. The fourth line is to run VIBRANT using python3.
+
+Here is an example
+~~~
+python3 VIBRANT_run.py -i ~/Test_VIBRANT/DTRs_ctgs_1-10.fna -folder ~/Test_VIBRANT/Test_results
+~~~
+
+you can now submit your script as a job using the command:
+
+~~~
+qsub vibrant.sh
+~~~
+