R Tutorial : The Bioconductor Project

Hi, I'm Paula Martinez. I'll be your instructor. I'm a data scientist and I train people on how to analyze their data more efficiently. Also, I'm a bioinformatician interested in genomic variation that leads to diversity for these kinds of analysis. I love using R&Bioconductor, particularly because of the possibilities to work with different datasets and to collaborate within the community. During this introduction you will discover the most commonly bioconductor packages. We will start with installation and at the end of this chapter you will be able to retrieve whole genome sequences using bioconductor. The bioconductor project is an open source software. It's a repository for R packages, datasets and workflows that are specific for analyzing biological data. The bioconductor project is a useful extension on cran, the R archive because it provides us with the software tools to explore, understand and solve simple and complex molecular biology questions. Hence, bioconductor's tagline is open source software for bioinformatics. Molecular biology questions are usually about either the structure or the function of each of the building blocks on an organism and very often how they interconnect to one another. In this course you will learn commonly used packages that will help you understand the structure of biological data. That is, you will find out more about the elements, their regions, their size and order, and how they relate to other data. Other bioconductor courses on Datacam will teach you more about the functions of the building blocks such as gene expression and regulation, and how these affect phenotypes such as health, disease, evolution, and much more. The bioconductor package collection forms its own repository and has a release schedule different from the R archive. Because bioconductor has its own base functions and updates, packages are installed differently. To install bioconductor packages you need two lines of code as shown on the slide. First, use the function source on the script Bioclight R from the bioconductor.org this script will install the biocinstaller package. Then use the function Biaseelight with the name of the package you want to install. Once you source the BioC Lite, you will be informed if any new versions of BioConductor are available and will also show you a prompt to update your R version if needed. Updating packages regularly it's important to get the new features in case there are upgrades on packages or dependencies. You will be asked to update all, some or none of the packages. Bioconductor is in constant development. You can check the version of BioCore using the syntax bioc installer bioc version or if you already loaded the bioc installer package, you can call the function bioc version directly. To load a package, use the function library. Like with gran packages, it's important for reproducibility to always check the versions of your packages. You can use the function session info, which gives you a list of all the loaded packages and their versions. Or you can enquire the version of each package using package version and the package name. Finally, if you are interested to know if you have out of date packages, use the function bioc valid. Now it's your turn to use bio.