R

This blogpost is about applying a mental-wellbeing coping to constant “data analysis worrying”. From https://xkcd.com/1222/. Let’s say you get a new project handed over; some kind of data analysis. What do you feel: excitement of getting your hands onto new data, or anxiety that this project may fail, stumbling upon all the data science mistakes that one can possibly make? I feel both of these things. I am always delighted about a.

I attended the last rOpenSci call on data repositories1 (recording) and below are my two cents on why storing on, and using data from the web may still be such a headache. The hour-long community call was - as always - inspiring and presented itself in a relaxed setting; with a set of experts voicing their experiences and challenges around data repositories from different angles, and a Q&A session towards the end.

Listening to a podcast keeps me focussed like nothing else, hence perfect for reflection and learning. Usually, I do some unsophisticated knitting next to it or I plug in my earphones while walking to work. Here is a list of my preferred podcasts. R & stats & data science Podcasts that touch on R, statistics or data science: Not So Standard Deviations: Entertaining chit chat - uplifting and enlightening. See below why this is my favorite.

Course material for R introduction workshop held at [Open science in practice](http://osip2019.epfl.ch/) summer school.

The 3+ days at useR!2019 in Toulouse were packed with great talks1 and good food - hence the amuse-bouches word play. Here are some R code bits from the conference. Hopefully convincing enough to start using a new package or change a workflow. Not everything was brand-new, but it was helpful to have someone talking through their inspiration and examples. Check out the speakers’ materials - soon there will be recordings too.

ggplot2 extension for visualising GWAS summary statistics.

Helper functions when working with GWAS (summary) data.

Goal Two approaches Our toy data 1A. A solution that works: ldlink from NIH LDproxy LDmatrix 1B. A solution that almost works: ensembl.org What reference panels/population can we choose from? Access LD between a SNP and its region Access LD matrix Access LD between a SNP and many other SNPs Coloured locuszoom plot 2. Solutions that work half-through SNPsnap API provided by sph.umich 3. A solution that does not work rsnps::ld_search Conclusion Session Info R-packages used: