If you have the time prior to the course, there are several things you can can do to get prepared. These items are mostly getting accounts with web services. There is also a full list of software we plan to use in the event you wish to use your own computer. ###Please get an account with following online services: * [GitHub](https://github.com) * [iPlant](http://www.iplantcollaborative.org) * [SQLShare](https://sqlshare.escience.washington.edu) _Google Account needed_ * [SageMath Cloud](https://cloud.sagemath.com) * [Galaxy](https://usegalaxy.org) ###Please review these webpages: * [Markdown](https://help.github.com/articles/markdown-basics/) * [Jupyter](https://jupyter.org/) - formerly IPython Notebook * [IGV](http://www.broadinstitute.org/igv/) --- ##Computing Environments and Software This course will be taught using lab computers or personal computers of students. This approach (as opposed to using virtual machines in the cloud) has its disadvantages and advantages. All lab computers should already have the below software installed. **If you are using your own computer here is a list of the software we will be using.** Any modern laptop should work fine. There will be some analysis that we will not complete during the course (given time constraints), however students should be able to clearly understand how to carryout the analysis. We will also be introducing students to cloud based options. Generally speaking, what we will be doing is more straightforward to do on Unix based machines, (Linux and MacOSx) though we will also show students Windows-centric solutions. --- ### Text Editors A good text editor will be very useful. Ther are several built in options with nano recommended by [Software Carpentry](https://software-carpentry.org/). For this course I suggest stand alone applications. **Windows** - [Notepad++](http://notepad-plus-plus.org/) - [Sublime Text](http://www.sublimetext.com/) **Mac OS X** - [Text Wrangler](http://www.barebones.com/products/textwrangler/) - [Sublime Text](http://www.sublimetext.com/) **Linux** - [Gedit](https://wiki.gnome.org/Apps/Gedit) - [Kate](http://kate-editor.org/) - [Sublime Text](http://www.sublimetext.com/) --- ### Markdown Editors We will use [Markdown](https://help.github.com/articles/markdown-basics/). Below are some recommended editors. Text editors above would also work. **Browser-based** - Jupyter will work - see below. **Windows** - [MarkdownPad](http://markdownpad.com/) **Mac OS X** - [Byword](http://bywordapp.com/) - [Mou](http://25.io/mou/) --- We will be using the "command-line", specifically the Bash shell. Below is information for this for different operating systems taken from the [Software Carpentry](https://software-carpentry.org/) website. ### The Bash Shell _Bash is a commonly-used shell that gives you the power to do simple tasks more quickly._ **Windows** Download the Git for Windows [installer](https://git-for-windows.github.io/). Run the installer. Important: on the 6th page of the installation wizard (the page titled `Configuring the terminal emulator...`) select `Use Windows' default console window`. This will provide you with both Git and Bash in the Git Bash program. **Mac OS X** The default shell in all versions of Mac OS X is bash, so no need to install anything. You access bash from the Terminal (found in `/Applications/Utilities`). You may want to keep Terminal in your dock for this workshop. **Linux** The default shell is usually Bash, but if your machine is set up differently you can run it by opening a terminal and typing `bash`. **Note you should be able to run bash shell on any platform within Jupyter, once installed** --- ### GitHub Local Clients We will be using GitHub, a Web-based Git repository hosting service. It offers distributed revision control of Git as well as adding its own features. - [GitHub Desktop](https://desktop.github.com/) is available for Mac and Windows --- ### Jupyter Formerly IPython Notebook Installation instructions are available [here](http://jupyter.readthedocs.org/en/latest/install.html). If you are new to Python and Jupyter, it is recommended you use [Anaconda](http://jupyter.readthedocs.org/en/latest/install.html#if-you-are-new-to-python-and-jupyter). On a Mac, there is a stand alone version of the notebook - [Pineapple](https://nwhitehead.github.io/pineapple/) --- ### BLAST The newest version of BLAST+ for all operating systems is available @ --- ### R _R is a programming language that is especially powerful for data exploration, visualization, and statistical analysis._ Below is information for this for different operating systems taken from the [Software Carpentry](https://software-carpentry.org/) website. **Windows** Install R by downloading and running [this .exe](http://cran.r-project.org/bin/windows/base/release.htm) file from [CRAN](http://cran.r-project.org/index.html). Also, please install the [RStudio IDE](http://www.rstudio.com/ide/download/desktop). **Mac OS X** Install R by downloading and running [this .pkg file](http://cran.r-project.org/bin/macosx/R-latest.pkg) from [CRAN](http://cran.r-project.org/index.html). Also, please install the [RStudio IDE](http://www.rstudio.com/ide/download/desktop). **Linux** You can download the binary files for your distribution from [CRAN](http://www.rstudio.com/ide/download/desktop). Or you can use your package manager (e.g. for Debian/Ubuntu run `sudo apt-get install r-base` and for Fedora run `sudo yum install R`). Also, please install the [RStudio IDE](http://www.rstudio.com/ide/download/desktop). --- ### Bedtools "Collectively, the bedtools utilities are a swiss-army knife of tools for a wide-range of genomics analysis tasks" Available for download @ _Likely only available for Linux and Mac OS_ --- ### IGV "high-performance visualization tool for interactive exploration of large, integrated genomic datasets" To download the software you will need to register. See . --- ### More Software **There are a number of programs that will be used that we might not actually run at full production level during the course given time and or processor constraints**. It would be fine to install these to get familar with parameters - [BSMAP](https://code.google.com/p/bsmap/) - [Trinity](https://github.com/trinityrnaseq/trinityrnaseq/wiki) - [Tophat](https://ccb.jhu.edu/software/tophat/index.shtml) - [FastQC](http://www.bioinformatics.babraham.ac.uk/projects/fastqc/) - [Trimmomatic](http://www.usadellab.org/cms/?page=trimmomatic) - [Trim Galore]() --- Here is a list of free web services we will likely use during the course - [DAVID](https://david.ncifcrf.gov/) - [Revigo](http://revigo.irb.hr/) --- ###Recommended Reading Material (not required for course) > [Bioinformatics Data Skills](http://shop.oreilly.com/product/0636920030157.do): > Reproducible and Robust Research with Open Source Tools > By Vince Buffalo > Publisher: O'Reilly Media > Final Release Date: July 2015 > Pages: 538 * [The Supplementary Material Repository for Bioinformatics Data Skills](https://github.com/vsbuffalo/bds-files) --- ###Other educational resources - [Sofware Carpentry Lessons](http://software-carpentry.org/lessons.html) - [RNA-Seq Methods and Algorithms](https://www.youtube.com/playlist?list=PL-0S9LiUi0vhjynujVZw34RKmUo6vPmVd) (2015 iPlant Workshop @ UC Davis)