If you were trying to convince a biologist to learn R, what types of R-generated figures would you show them to illustrate the power / flexibility / niftiness of R?
Really? You don't think they are capable of learning the assumptions? This seems kind of sad to me. I feel like with the amount of data being generated now, everyone could use some basic data analysis skills.
I would show them that with a few lines of code they can read in affy CEL files and get a scatter plot (MA plot) with DE genes highlighted in color and labeled (a demo with about 10 lines of code can do this within 10 seconds). I would show them that they can copy and paste that figure directly from R into a Microsoft Word or PowerPoint document (since most of them use those tools daily), or create a pdf. I would show them that they can turn a table of numbers into a heat map with pretty colors. I would show them that they can easily visualize plate based assays (96 well plates) with color, and that they can easily process data from those assays (i.e. fit 96 growth curves, or enzyme kinetic data). I would probably show them that it’s easy to generate and fit a scatter plot first, then show that it’s easy to fit 96 or 9600 scatter plots. Maybe play with some histograms.
Non-visually I would make the following points: R is a language for asking questions. It is the most efficient way to reduce the time between having questions and answering them. This means you can ask more questions, explore your data more, understand your data more. I would talk to them about reproducible analysis, and show them the beauty of how a few lines of code pasted into a buffer makes for (changeable) recipes and documentable and sharable analysis.
The most effective strategy would be to get to know this group's needs then solve a few of their problems thus demonstrating the utility of R. Some tasks that currently are tedious, perhaps require a lot of clicks with Excel could be streamlined and automated and thus become a gateway to R.
Going out there and demonstrating a few neat techniques might work too - the danger there is that after the presentation, once the initial buzz fades everyone will just go back to their familiar approaches since they don't have time to investigate more.
Here's an intro I saw that I thought was pretty gentle. And although the example was a plant breeding case, I think most biologists would grasp what it could do.
It was an hour long webinar, but was chunked into some YouTube pieces: http://blog.openhelix.eu/?p=9763
I think the enticement part is easier than actually teaching R, especially when the students are just getting used to imperative programming.
A live interactive session is a good idea, as is sticking to one facet of R, like plotting.
I tried to do this at PFB last year but I'm not sure I was very successful.
http://gorgonzola.cshl.edu/pfb/2010/LectureNotes/R/R.pdf
Good luck!
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@peri4n That's a pretty weird sentiment. I'm a biologists who can tinker a little in a couple of languages, and that's immensely helpful. Not just because it saves me from doing tedious things over and over, but because it means when I do have to talk to an expert in a given analysis/problem it's much easier to communicate what I want to do and what data I'm going to have etc.
Opposing views of the brain: "...of course they're capable of learning..." vs. "...I don't think they can learn...", or different outlooks on humanity (specifically biologists)? One says don't bother learning a foreign language unless you're a linguist, the other says watch me thrive in a foreign country with a few verbs and a handful of nouns. I know plenty of biologists who have learned and utilize R effectively. A few people misusing a function doesn't justify shielding a population from a tool set. Education always tops ignorance.
I would say it is just as likely that a programmer will make incorrect assumptions about data coming from a biologist. I don't think building a higher wall is the answer.
To be honest. I dont want to convince biologists to use computer programs. There is a simple reason for this:
Most programs do some assumptions biologists dont understand or dont know. So even the program works fine the output is garbage. This can result in horrible problems. I already had such problems.
@mmarchin, of course they're capable of learning R, it's just a question of whether it is the best use of their time or not. Most of the biologists I know have plenty on their plate keeping up with biology and wet lab technology. If you can show them that learning R will be a net savings of time for them, they'll probably be happy to learn it.
@mmmarchin Yes I dont think they can learn the assumptions. As it occured several times in this platform: Wrong statements about statistical models has been proclaimed. There is a reason why bioinformatics is a seperate science. @david_w Sure. Parsing some data is always useful and a technical vocabulary always helps in communication but you have to put a lot of time to get some insights and this is only done by cs enthusiats (less then 1% of the biologists).