Project contributors: Alister Maguire, Hiranmayi Duvvuri, Pat Johnson, Xi Zhang contact: aom@uoregon.edu or alisterowen87@gmail.com 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.