Publications by Stephen Turner
Customize your .Rprofile and Keep Your Workspace Clean
Like your .bashrc, .vimrc, or many other dotfiles you may have in your home directory, your .Rprofile is sourced every time you start an R session. On Mac and Linux, this file is usually located in ~/.Rprofile. On Windows it’s buried somewhere in the R program files. Over the years I’ve grown and pruned my .Rprofile to set various...
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Course Materials from useR! 2013 R/Bioconductor for Analyzing High-Throughput Genomic Data
At last week’s 2013 useR! conference in Albacete, Spain, Martin Morgan and Marc Carlson led a course on using R/Bioconductor for analyzing next-gen sequencing data, covering alignment, RNA-seq, ChIP-seq, and sequence annotation using R. The course materials are online here, including R code for running the examples, the PDF vignette...
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Archival, Analysis, and Visualization of #ISMBECCB 2013 Tweets
As the 2013 ISMB/ECCB meeting is winding down, I archived and analyzed the 2000+ tweets from the meeting using a set of bash and R scripts I previously blogged about.The archive of all the tweets tagged #ISMBECCB from July 19-24, 2013 is and will forever remain here on Github. You’ll find some R code to parse through this text and...
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Analysis of #ASHG2013 Tweets
I archived and anlayzed all Tweets with the hashtag #ASHG2013 using my previously mentioned code.Number of Tweets by date shows Wednesday was the most Tweeted day:The top used hashtags other than #ASHG2013:The most prolific users:And what Twitter analysis would be complete without the widely loved, and more widely hated word cloud:Edi...
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Real-time streaming differential RNA-seq analysis with eXpress
RNA-seq has been performed routinely for at least 5+ years, yet there is no consensus on the best methodology for analyzing this data. For example, Eduardo Eyras’s group recently posted a pre-print on methods to study splicing from RNA-seq, where this great figure was shown:This illustrates the problem clearly: ignoring alternative ...
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Archival and analysis of #GI2013 Tweets
I archived and analyzed all Tweets containing #GI2013 from the recent Cold Spring Harbor Genome Informatics meeting, using my previously described code.Friday was the most Tweeted day. Perhaps this was due to Lior Pachter’s excellent keynote, “Stories from the Supplement.”There was clearly a bimodal distribution in the Tweets by...
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Jeff Leek’s non-comprehensive list of awesome things other people did in 2013
Jeff Leek, biostats professor at Johns Hopkins and instructor of the Coursera Data Analysis course, recently posted on Simly Statistics this list of awesome things other people accomplished in 2013 in genomics, statistics, and data science.At risk of sounding too meta, I’ll say that this list itself is one of the awesome things that was put tog...
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Coursera Specializations: Data Science, Systems Biology, Python Programming
I first mentioned Coursera about a year ago, when I hired a new analyst in my core. This new hire came in as a very competent Python programmer with a molecular biology and microbial ecology background, but with very little experience in statistics. I got him to take Roger Peng’s Computing for Data Analysis course and Jeff Leek’s ...
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Data Analysis for Genomics MOOC
Last month I told you about Coursera’s specializations in data science, systems biology, and computing. Today I was reading Jeff Leek’s blog post defending p-values and found a link to HarvardX’s Data Analysis for Genomics course, taught by Rafael Irizarry and Mike Love. Here’s the course description:Data Analysis for Genomics...
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Software Carpentry at UVA, Redux
Software Carpentry is an international collaboration backed by Mozilla and the Sloan Foundation comprising a team of volunteers that teach computational competence and basic programming skills to scientists. In addition to a suite of online lessons, Software Carpentry also runs two-day on-site bootcamps to teach researchers skills such as using t...
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