HAPPY HOLIDAYS!!!🎉⛄🎆🍾❄ In the spirit of the coming new year and new beginnings, we created a tutorial for getting started or restarted with R. If you are new to R or have dabbled in R but haven’t used it much recently, then this post is for you. We will focus on data classes and types, as well as data wrangling, and we will provide basic statistics and basic plotting examples using real data.
By Amy Peterson
Studying genetic differential expression using postmortem human brain tissue requires an understanding of the effect brain tissue degradation has on genetic expression. Particularly when brain tissue degradation confounds1 the differences in gene expression levels between subject groups. This problem of confounding necessitates measures from a control dataset of postmortem tissue from individuals who do not have the outcome of interest. Doing so provides a comparative measure of the impact of tissue degradation on expression that can then be used in a case-control study to examine the impact of the outcome of interest on genetic expression.
Every six months the Bioconductor project releases it’s new version of packages. This allows developers a time window to try out new methods and test them rigorously before releasing them to the community at large. It also means that this is an exciting time 🎉. With every release there are dozens1 of new software packages. Bioconductor version 3.8 was just released on Halloween: October 31st, 2018. Thus, this is the perfect time to browse through their descriptions and find out what’s new that can be of use to your research.
To carry on our momentum from a few weeks ago from our useR!2018 remote notes blog post, this time we will be summarizing the Demystifying Data Sience 2018 conference for which you can register for free. We are just following David Robinson’s advice to blog all the time!
So what should you blog about? @drob says no matter what stage you're at in your career, you have a lot to share.
For our club meeting today we were going to summarize the Demystifying Data Science conference but we forgot that the videos are not released yet.
Oops, we'll have to postpone our blog post. We didn't read the fine print that talk recordings will be available sometime next week. Sorry about that!
— LIBD rstats club (@LIBDrstats) July 27, 2018 So we adjusted plans and decided to continue our work on the UpSetR (Gehlenborg, 2016) package by Nils Gehlenborg.
For our July 13th 2018 LIBD rstats club meeting we decided to check as much as we could the useR!2018 conference. Here’s what we were able to figure out about it in about an hour. Hopefully our quick notes will help other rstats enthusiasts, users and developers get a glimpse of the conference. Although there’s bound to me more videos and material about the conference coming out in the following days.
By Amy Peterson
Using Git Git is a version control system that allows you to track changes made to files while working on a project, either independently or in collaboration with others. It provides a way to save many different components of a project in progress, including the source code, but also the figures and data that the code produces. The importance of understanding and using Git lies in its ability to maintain an organized record of a project, also referred to as a repository or repo, as it evolves.
By Steve Semick.
What do you do when you want to use results from the literature to anchor your own analysis? When these results are in the form of an easily accessible table, such as a .csv file or .xlsx file, then it is simple enough to download them and incorporate them into your research. Often times, however, published findings are not so easy to handle. Today, we’ll go through a practical scenario on scraping an html table from a Nature Genetics article into R and wrangling the data into a useful format.
By L. Collado-Torres.
If you are working at LIBD or with large data, it’s very likely that it won’t fit in your laptop and that you’ll be using the terminal to interact with a high performance computing cluster (like JHPCE) or server. Some small edits to your bash configuration file can make your terminal experience much more enjoyable and hopefully boost your productivity. The edits described below work for any OS.
By L. Collado-Torres.
For the past 6-7 years I have been using TextMate 2 as my text editor which I’ve found useful for R code, bash, Markdown, etc. You could also look into Sublime Text or use RStudio (post about this setup coming soon).
Sometimes students are interested in this setup, which is what I’ll document here. Though I want to highlight that you can get a very similar setup using other tools.