Bioinformatics Zen

Deepak, Neil, and Cameron have set up life streams which aggregate the feeds from services from sites like Last.fm and Flickr into a single set of posts. I’m a bit wary of this doing this because I already get easily distracted by Ruby and bioinformatics blogs, but Neil gave me an idea when he wrote about using these technologies to track research. I currently use Subversion to back up my project files, and I noticed Twitter status updates are very similar in length to subversion log messages. I created a short script so that every time I do a subversion repository check in, the message is also sent to Twitter.

#!/bin/sh
#Inspired by tinyurl.com/yt4ssq
 
# Scrub weird characters
MSG=`echo $@|tr ' ' '+'`
 
# Send twitter request
curl --basic --user "username:password" --data-ascii "status=$MSG" "http://twitter.com/statuses/update.json"
 
# Send SVN request
svn ci -m $MSG

Combined with an RSS Wordpress plugin, my most recent research activity from Twitter is displayed as a stream on my blog. Taking this a step further I included feeds for my research tagged Figures on Flickr, my paper bibliography on CiteULike, and discussion of my research on my blog. This stream is available on www.michaelbarton.me.uk/research-stream/, and shows the general idea of what I’m trying to do. I like this because in bioinformatics its sometimes difficult to know what other people are doing, but, now I hope that other people in my group can have a quick glance to see what I’ve been up to. Furthermore this all works passively, where I’m already using these services in my research anyway, and the only thing I had to do, was use yahoo pipes to aggregate the already existing information.

Because bioinformatics work is amenable to being displayed, shared, and edited on the web I think that the field should be at the bleeding edge of using Web 2.0 services like this. Of course many other bloggers before me, in particular Deepak, are already discussing this. Compared to most mashups what I’ve created is a rather shoddy as I’m cobbling together various services and trying to use Wordpress plugins to create something not exactly what they were intended for. However I don’t have much time in my PhD to spend experimenting, and I think this would be true for most scientists. Therefore the more that existing services can be used, the better. As a further example, I think Flickr has a lot of potential, and I would like to create a group for my lab, so everyone can upload and tag their figures, as they are producing them. Then the group’s pictures can be browsed and organise by tag to visualise what everyone is working on. The only effort required is for people to upload and tag their photos as they are making them.

I think the title says it all. If you have two populations such as “Treatment” and “Control”, what type of graphs can you use to compare the two? Have a look at the examples, then pick the corresponding R code.

All of the charts come from either excellent the lattice package, or the superb ggplot2 package. The code should also work for multiple populations as well.

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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.

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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.

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A great post at creating passionate users, I think really applicable to science too.

I know this is horribly overgeneralized, but as a high-level rule, we believe:

If you’re using formal language in a lecture, learning book […], you’re worrying about how people perceive YOU. If you’re thinking only about the USERS, on the other hand, you’re probably using more conversational language.

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