Bioinformatics Zen

Back from a weeks holiday in Hungary just in time for my, hopefully, last ever year as a student. Last month I had a flurry of work completing a report and poster for the end of my second year, but now I’m aiming to work hard and try and get at least two papers out in my final year: in time to write up my thesis.

But now, to coincide with the beginning of the academic year, and the time that new PhD and Masters students start, I thought I would share some the resources that I found useful through out the course of my own Masters degree, then first two years of PhD.

Read more »

Computers and the Internet have made things great for scientists, particularly for us, since our jobs are sitting in front of them analysing data all day. Imagine being a bioinformatician without a computer, multivariate statistics is more of a pain than usual, genome sequence alignments need large pieces of paper. There would however be an upside to this analog dystopia - no more powerpoint presentations. Computers have arguably had a detrimental effect on the presentation of research, they allow the easy creation of big, text heavy slide sets. The emphasis of a talk leans towards the slides, and not the speaker.

Being asked to give a talk is viewed as a dull task: time taken away from research plus the discomfort of public speaking. If you’ve already decided beforehand that it’s going to be a dull, pointless exercise then don’t bother, not only will you be wasting your own time but also the time of everyone watching. It’s true that this is a very critical attitude to express; boring presentations are symptom of our scientific culture rather than the fault of the individual, but how many times have you been sat in conference and thought that you could have been using your time much more usefully? Now imagine, for a second time, a world where we have both computers and great presentations. The chance to give a presentation is greeted with enthusiasm, as an opportunity to teach the world about what you commit most of your time to, and to get valuable feedback on it. But we don’t need to imagine this place, we’re the generation of scientists coming through: the professors and PI of the next 30 years, we can start this revolution now.

Read more »

I think simple is better. Statistics says so too. Statistics says that you’ll probably read the first two paragraphs of this post, look at the pictures then go elsewhere. So I’d simply better get to my point. In terms of attention spans, computer code and (statistical) explanations, and possibly everything in general, I think it’s always better to favour simplicity over complexity.

Read more »

A post at Presentation Zen discusses keeping the signal-to-noise ratio in presentations as low as possible. Definitely worth a look, the point is to keep your slides uncluttered (noise) so that the audience can focus on your message (signal).

As an example of this I recently gave a presentation to illustrate hierarchical regulation. I gave the talk to a non bioinformatics audience so therefore I was trying to present using a simple and straight forward manner. The slides included a couple of graphs, and since I’ve mentioned graphs in presentations previously I thought I’d include a few slides here. The presentation might appear minimal, but I was also speaking at the same time.

I think everyone would agree that the most important thing in science is results. The best scientists produce the most relevant and important results. Of course, the best results won’t matter if no one knows about them. Which is why we publish and give presentations.

Sometimes I see results in papers and presentations illustrated poorly. Graphs that don’t demostrate the point to the reader/audience in the best possible way. Here I give examples of how data can be presented in different contexts, based on two of my favorite resources. The first is the R language for statistics, the other is Garr Reynolds‘ Presentation Zen ideology.

A bad example
Here’s an extreme case, but not completely uncommon in presentations. Two continuous variables - the oxidation of ammonia to nitric acid, and air flow. The chart was produced, using default options, in NeoOffice.

My initial complaint, is the inappropriate x axis - the first half of the plot isn’t being used. The axis should begin around 40, where the data starts.

Next, the unattractive grey background and horizontal black lines. I personally find this style unpleasant, and would recommend that these always be removed.

Finally, the trend-line, the magenta color is not particularly nice, and why is it so thick? The wide line makes the chart look clunky and inelegant. If you’re making a chart, you want people to look at it, and appreciate the data. You’ve spent months slaving away to produce a set of results, so why not put the extra effort into presenting them well?

Producing a graph for a paper
Here is the same data produced using the default plot function in R.

What strikes me about R plots, is how clean they appear. You could argue that it looks rather spartan, but the chart shows the data and nothing else. There are no frills, but then you want to illustrate your results efficiently. If the results aren’t that good, then no amount of fluffing will make them better. On the other hand if the results are good, extra decoration distracts from the main point.

Producing a graph for a presentation
Controversial, but I say don’t. If you can use a simpler way to show the result, do it. When looking at a chart in a paper, the reader has time to read the legend and think about what point it illustrates. I look at all the figures in a paper at least twice.

On the other hand, when presenting, you’ve usually got a limited time to get your point across. When you show a chart in a presentation the audience has to look at many things, the axis, points, trend-lines. This could distract from you, and your message.

What do you want to do in the time you have? You want to show your work as exciting and interesting to as many people as possible. How many times have you been in a presentation where there has been slide after slide of graphs. You can imagine that audience attention drops dramatically with each new plot. Here’s an example slide to illustrate how I would show the above data.

This shows the point succinctly, no distractions. Remember that you’ll be talking at the same time as well. If the audience wants more information, they can find you afterwards. You can direct them to the great figures that you included in your paper!

Of course you’ll need to include a plot to demonstrate controversial and important results. The less plots you have prior to these, the more impact they and therefore your point, will have. Garr Reynolds has some tips (point 6) on producing graphs for presentations.

Finally
I’d like to end this post by quoting the R help page on the subject of pie charts

Pie charts are a very bad way of displaying information. The eye is good at judging linear measures and bad at judging relative areas. A bar chart or dot chart is a preferable way of displaying this type of data.

Cleveland (1985), page 264: “Data that can be shown by pie charts always can be shown by a dot chart. This means that judgements of position along a common scale can be made instead of the less accurate angle judgements.” This statement is based on the empirical investigations of Cleveland and McGill as well as investigations by perceptual psychologists.