A biologist playing the numbers game

A biologist playing the numbers game

Biologists generally dislike numbers, as a rule. Probably because numbers require you to do all the work before anything interesting happens. Numbers don’t metabolise, or synthesise, or secrete, or replicate. They don’t behave in different ways under the same conditions. They are, in a word, reliable. We like what they represent, but we don’t like that they are an abstraction of what actually interests us about biology.

But this is 2017. Gone are the days of Leidy, Manson and Darwin where a biologist could spend their life avoiding the numbers game and still rise to the top of their field. Biology means data, and data means statistics! At some point, every young biologist goes through the realisation that they have to bite the bullet and actually learn a bit of stats in R (or MatLab, if you would rather use something with a price tag), rather than subsist on the vague idea of statistical analysis all those modules you took furnished you with. After all, wouldn’t it be nice to be an author on one of those nice shiny papers with all that important looking multivariate analysis in it.

So what to do? Well go on a course of course. I did exactly that. I found myself an interesting and relevant looking course ran by PR Statistics, looking at analysis of population genomics data in R. The course took me through how to use various packages available in R, particularly Adegenet [1], to reveal structure in your data and was instructed by the developers behind Adegenet: Thibaut Jombart & Zhian N Kamvar, who were as knowledgeable and skilled instructors as you could encounter. If you perform statistical analysis on allelic frequencies in population data sets, then I would highly recommend this package, it contains everything that you could need to elucidate even the most subtle structure in data. Set in the almost idyllic location of Margam country park, east of Swansea, it was a week which did not leave me, or any of my course mates (many of whom had travelled from as far as the USA) wanting. I feel compelled to also mention the cake that the cooks set out for us every day, which resulted in me leaving Margam a few pounds heavier, as well as a week wiser. If this course is representative of all courses ran by PR Statistics, then I can highly recommend them.
So armed with my new, more informed view on statistical analysis in R, I can go forth and see what I can make of my own data sets and see if I can’t produce some of those oh so aesthetic graphs myself. As it happens, I quite like numbers now.

Many thanks to Oliver Hooker for organising the course, and to Thibaut and Zhian for their expert instruction.

By Arthur Morris

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[1] T. Jombart, “Adegenet: A R package for the multivariate analysis of genetic markers,” Bioinformatics, vol. 24, no. 11, pp. 1403–1405, 2008.

Social Media Scientific Collaborations?

My only foray into social media during my scientific career has been limited to one platform involving the use of 140 characters at a time. I use no other social media platforms. Since I joined in 2014 I have gradually engaged to greater extent. During this time I’ve found the small snippets of information displayed before my eyes to be a highly suitable source to binge on science news. Of course this has required me to be selective about the people or groups that I follow not to be swamped by general news from the masses. To this end, my news feed features all of those things I find exciting or interesting around science, with the occasional fun thing thrown in. On a daily basis I read new findings from the fields of biochemistry, protein science and, of course, parasitology. Admittedly, I confess the majority of my feeds are related to the later topic, with my screen regularly filled with amazing images and video snippets of parasitic worms and the cool things that they do.
As I have posted new research coming out of my research group around the biochemistry and molecular biology of parasitic worms it is highly addictive to see other social media users interacting with these instant updates of research. Whether it is an update on the role of a glutathione transferase (GST) or an insight into the fatty acid binding protein family I am continually excited to both promote our research and simultaneously interact with scientists across the world. One of the best aspects of this is that the scientists are from all stages of their careers from undergraduates through to established and highly respected Profs. A second confession of this blog is that a lot of scientists I follow are established collaborators and there may be the suggestion that we are self-promoting our work to one another. This aside, it is great bringing new science to the world (or at least the 400 followers I have) and seeing the progress of others – especially satisfying interacting with undergraduates succeeding with their first protein gels or postgraduates uploading SDS-PAGE ‘Gel-fies’.
However, I had never thought of social media as a platform to establish new connections and collaborations…until today. After being delighted with image after image of wriggling Parascaris parasites (worms of horses that are approximately 15-20 cm in length) I was compelled to contact the owner of these worms…a fellow wormer based across the pond in the USA. I have a particular passion to collect some Parascaris to provide one of my PhD students some samples to extract their GSTs and compare with related worms. This fellow worm guru was one of those people you follow in case something interesting pops up on their feed…and sure enough. It did! I have since established formal communications/collaborations and will be waiting on a shipment of worms to arrive in the post. What a nice gift for my PhD student! The wonders of establishing social media collaborations…

Post by Dr. Russ Morphew