aowen87 / vincepipeline Goto Github PK

Project contributors:
    Alister Maguire, Hiranmayi Duvvuri, Pat Johnson, Xi Zhang

contact: 
    [email protected] or [email protected]
    Specific question regarding individual pipelines
    can be sent to contacts found within their respective
    documenations (located in the doc folder). 


Installation:

    Currently supported OS:
              *Linux (Debian tested)
              *Mac
              *Windows 10
              No other systems have been tested. 

    Pre-reqs: 
              Make sure that you have python 3.x installed on your machine. You should also 
              install paramiko (a python package). The auto install is set up to try and
              install paramiko for you, but this doesn't always work because of permissions. 
              If you have pip installed, you can install paramiko by entering the following
              command in a terminal/powershell: sudo pip install paramiko
              If you are on Windows, make sure that you have powershell installed and are
              able to ssh into remote servers. 

    Auto-installation (recommended):
              For auto-installation, open a terminal (powershell if on Windows), and navigate
              to the Setup directory. Once here, you will run runInstall.py by launching 
              python. Make sure that you are launching with python 3 and not python 2. If python
              3 is your default, you will type the following command into your terminal and 
              press enter:
              
              python runInstall.py

              If python 2 is your default, use the following command:

              python3 runInstall.py

              If you don't know which version is you default, you can find out by typing the
              following command:
              
              python --version

              Once runInstall.py is invoked, you will see a window with several entry boxes. 
              Most are self explanitory. The genome is an optional reference genome that you 
              can transfer to ACISS during installation. You will see a progress report being 
              printed in the terminal. Once complete, you should see a message that says 
              "Successfully installed". If something happens to go wrong, and you aren't sure 
              why, you can contact us through the provided emails. If successfull, you should 
              have a shorcut icon on your desktop. Double click the shortcut to launch the 
              pipeline. 
    
    Auto-Uninstallation:
              If you wish to uninstall, invoke runInstall.py, enter your ACISS user name and
              password, enter the path to the ACISS repo, and click uninstall. The desktop 
              shortcut and ACISS repo will be removed, and the GitHub repository will revert
              back to its original state.  

    Manual installation:
              There may be instances in which you wish to install manually. If this is the case, 
              See the documentation within the doc folder for details on each pipeline and
              their requirements. 


Usage:
    
        With auto-installation, the directories are set up as follows:

                                  MainInstallDirectory
                                           |
                                           |
                    ---------------------------------------------
                    |         |            |                    |
                BRAT_BW    mapChip    MethylationPipe    TransferedGenome


        BRAT_BW, mapChip, and MethylationPipe are the three directories that 
    correspond to the three pipelines. When you run a pipeline, all computations 
    will take place from within its respective directory. For instance, if 
    you run the BRAT-BW pipeline, all computations will take place within 
    BRAT_BW. This means that, if you wish to use a transfered genome, you can
    either place this genome in the pipeline's directory and enter the genome
    name without a path, or you can have the genome located elsewhere and 
    include the entire path when you run the computation. 
        All Pipelines have an option to input an email address. If you choose to
    do so, you will recieve an email notification when the pipeline starts and 
    ends. The user name and password entries are for your ACISS account information. 

BRAT-BW pipeline:

    Input:

        BRAT genome directory: The genome you wish to map the fastq files to. 
                               If you wish to build a genome, check the build genome
                               box and enter the name you wish to give the genome
                               directory. If you already have a genome on ACISS
                               that you'd like to use, enter the path to this 
                               directory. 

        fastq directory:       A directory containing the fastq files that you 
                               wish perform the computations on. This directory
                               should be located on ACISS. 

        results directory:     This is the directory that the results will be stored in. 
                               NOTE: you do not need to include a path when naming this 
                               directory. By default, the results directory will be created
                               in your primary pipeline directory with the given name. 

        non-BS mismatches:     The number of allowed non-bisulfite mismatches. 

        quality score:         An integer value representing the quality score. 

        build genome:          Check this box if you wish to build a genome. 

        remove extra output:   Check this box if you wish to remove extraneous output
                               that results from this section of the pipeline. By default, 
                               this box is checked. 
        
    Output: 
        
        wigFiles:              Contains the resulting wig files and bedgraph files. 

        mergedFiles:           These files are used within the methylation pipeline. 

        5mCAverages:           Output from average calculations.  


Methylation Pipeline:
    
    Input:
       
        .meth Conversion:                This tab contains the information for 
                                         meth_convert.py

            converted files directory    This directory contains the files from 
                                         mergedFiles in the BRAT-BW pipeline.

            results directory            This directory will contain the results
                                         from meth_convert.py in the form of the
                                         .hmr and .meth files.
                                         Files are output in the following format:
                                         prefix_strand_suffix
                                         These files will be used in the rest of the
                                         methylation pipeline.

        methylome comparison:            This tab contains the information for 
                                         methylome_comp.py

            meth conversion directory    This directory contains the output from
                                         meth_convert.py, or the .hmr and .meth files
                                         for each sample.

            results directory            This directory will contain the results from
                                         methylome_comp.py outputting .methdiff files
                                         as well as files containing the scores from
                                         sample 1 and sample 2 with sample 1 being the
                                         wild type or given sample and sample 2 being the
                                         samples in the input directory.

            .meth WT sample              This is the .meth file of the sample all other
                                         samples will be compared to.

            .hmr WT sample               This is the .hmr file of the sample all other
                                         samples will be compared to.

Chip-Seq analysis:
    
    Input:
       
        ChiP Reads Directory:    This tab contains the information for chip_map_reads.py

        Genome:                  If you have a reference genome that you'd like to use, 
                                 you can enter this directory. Otherwise, enter a fasta 
                                 file, and the genome will be created from this. 

        Chip Output directory:   This directory will contain the resulting files. 

    Output:
        
        <your_results_directory>/results: .bam and .bai files.



For futher questions, see documentation within the doc folder, or contact one of the
contributors.