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 together in 2013. You should go browse the entire post for yourself, but I’ll highlight a few that I saved to my reading list:

• Yuwen Liu and colleagues published a paper on power for RNA-seq experiments comparing biological replicates and sequencing depth. This paper adds to previous work showing conclusively that adding more replicates is usually better than adding more sequencing depth.
• Thomas Lumley’s brief but insightful discussion of statins and the causal Markov property. Lumley also linked to a Labhacks post on a high-quality scrunchable cloth poster print for $25.
• Joe Blitzstein’s Data Science course at Harvard, which has an excellent reading list (many are IPython Notebooks, which can be read freely and downloaded to run locally.
• A link to Lior Pachter’s blog, which I also regularly read for all things related to RNA-seq and beyond.
• Tuuli Lappalainen’s paper on RNA-seq reproducibility. You can also follow Tuuli on Twitter (@tuuliel).
• On the metagenomics front, the metagenomeSeq R package for differential abundance in microbial communities from Mihai Pop’s group, and from Curtis Huttenhower’s group, a new method for predictive functional profiling of microbial communities using 16S rRNA marker gene sequences.
• Finally, because Jeff’s post was about awesome things other people did in 2013, he deliberately omitted some of the awesome things that his own group and others at Johns Hopkins did in 2013. Some of Jeff’s contributions that I found most useful in 2013 were several guides, available as GitHub repository READMEs:
• jtleek/rpackages: A guide to developing R packages using devtools, roxygen2, knitr, git, and GitHub.
• jtleek/datasharing: A guide to how to share data with a statistician. This is a great post to send to your collaborators who constantly send you inconsistently coded data without a metadata code book.
• jtleek/reviews: A guide to reviewing academic papers. We’ve all gotten back terrible, often times useless reviews. Follow the advice here to avoid being one of those awful reviewers we all despise.

This only a sample of what’s posted on Jeff’s blog. Go read the full post below.

Simply Statistics: A non-comprehensive list of awesome things other people did this year.