The second iteration of our bioinformatics summer course, Analyzing Next-Generation Sequencing Data, just finished. It was a great success, at least judging from the comments that people made to us personally; the evaluations aren't yet complete.

The what: a two week course on analyzing next-gen sequencing data, using the Amazon cloud, for biologists with no prior computational experience.

The who: 2 instructors (myself and Ian Dworkin), 4 TAs (Jason, Likit, Rose, and Chris), and two visiting faculty (Istvan Albert and Erich Schwarz). 24 students, from 5 of the seven continents (Australia, South America, Europe, Asia, and the US).

The where: two weeks out at the lush Kellogg Biological Station, a research station in west mid-Michigan (just north of Kalamazoo).

As with last year's course, we taught students to use Amazon AWS for all their computing needs, including compute and data storage. We had an education grant from Amazon this year, which let us play with more and niftier services: I used less (well, no) S3 and more/bigger EC2 machines with EBS volumes and snapshots. This worked fantastically well, with the main problem being the lousy connection between our room and the rest of the campus, which led to occasional bottlenecks as 24 students tried to bring up their machines. I don't know how many people are taking even partial advantage of AWS for their classes, but the sheer awesomeness of the cloud for teaching computer science and scientific computation is something that needs to be broadcast.

The students this year were more motivated, if possible, than last year's. If I had more than two points on the graph, I'd suggest that there was a trend here: everyone is getting this data, and nobody has the least #!%!@^@#% idea what to do with it. (Oh, heck, it's an obvious trend ;). One fallout from this is that we challenged the students with more scripting, and were rewarded -- most people seemed to think it was a good intro, although we'll have to see what happens down the road with that. (Also see this great Nat. Methods technology feature, replete with quotes from yours truly, about programming in biology.)

The students this year were also more diverse. Last year we had 33 applicants for 24 slots, and I accepted 24 and 23 came. This year we had 133 applicants (!!) for 24 slots, and all 24 were taken (although I had to fill a slot from one student who simply didn't show up. Bad person. No cookie for you.). This led to more diversity in backgrounds, skill sets, and training. We even let a bioinformatician slip in to the course by accident ;')

Very interestingly, the range of critters under study were more diverse. This was partly due to selection criteria -- Ian and I did most of the selecting, and as we are both evolution-curious, we tried to pick a diverse group of critters. Notables included: two cnidarian researchers, one dinoflagellate researcher (their critter had a freaking' 64 GB genome... that's 21 times human!), a last-minute lophotrochozoan person, someone working with 20-odd microbial genomes, a mouse/human xenografter, someone studying a symbiont of a symbiont, and someone working on strange, edible sea critters, as well as many others that I'm forgetting about. I think another trend that is probably completely obvious to those of working in evolution studies is that literally everything on this planet is getting blended up and thrown into sequencers -- and there ain't no reference genomes for these critters...

As with last year, we tried to pass on the message that this was a very immature and fast moving field, and you had to worry a lot about the quality of your sequence, on top of all the other issues. Interestingly, this was a strong message from Istvan Albert's talk, too; I know that Ian and I both tend to be very skeptical of next-gen sequence quality, but people are sometimes skeptical of the strength of our skepticism, so it was nice to hear the same message from someone completely different!

Less of my hair follicles were lost this year due to Ian's participation as co-instructor as well as the awesome guest lecturers. That was nice. Sleep was still hard to find, but I had more fun and less moments of sheer terror.

All of our tutorials are copy-paste and freely available under a Creative Commons/Attribution license. Please use and abuse! There are tutorials on basic mapping and assembly, transcriptome analysis, ChIP-seq, and resequencing analysis available, among others.

One piece of good news for students that want to take this course: it looks like the 2012 course will be happening! Were it to happen, it would be around June 4 - June 15. Same bat place. I will announce it here and everywhere & link to it from the old course page.

A few other courses have sprung up. The three that I think look the best are: the UC Davis course, in September; the NESCent course; and the Ft. Collins workshop on Comparative Genomics, happening in July (next week!). CSHL is running a few different courses (programming for biologists, advanced sequencing technologies, and computational/comparative genomics). The Davis course is the only one that uses the cloud much, which is a shame; the cloud usage is something that a lot of people seem to like about our course, and it's really convenient for people from institutions without significant compute resources. (Note that I know the NESCent course, at least, was just as oversubscribed as ours. There's room out there for more courses!)

BTW, we'd love to find someone interested in writing up our course (and maybe these others?) for a news piece in some journal. Drop me a note at ctb@msu.edu if you are interested!

--titus