This post is intended to be shortened over time, eventually becoming an automated procedure… a wiki-post from dahlo’s magic until upstream patches settle down. All commands are issued on the cluster, unless otherwise stated.

Please report any issues via comments !

1. Firsly, follow my earlier post on how to setup your own python virtual environment on UPPMAX.
2. Once you have a prompt similar to: (devel) hostname ~$, you can continue, else, jump to 1.
3. pip install drmaa Mercurial PyYAML
4. Add the following env variables to your .bashrc:

   export DRMAA_LIBRARY_PATH=/bubo/sw/apps/build/slurm-drmaa/lib/libdrmaa.so
   export DRMAA_PATH=$DRMAA_LIBRARY_PATH
   

5. Create a file ~/.slurm_drmaa.conf with the contents:

   job_categories: {
         default: "-A <your project_account> -p devel"
   }
   

6. hg clone http://bitbucket.org/brainstorm/galaxy-central
7. Edit universe_wsgi.ini from the provided sample so that it contains:

   admin_users = <your_admin_user>@example.com
   enable_api = True
   start_job_runners = drmaa
   default_cluster_job_runner = drmaa://-A <your project_account> -p devel
   

8. On your local machine: ssh -f <your_user>@<uppmax> -L 8080:localhost:8080 -N
9. On your local machine: Fire up your browser and connect to http://localhost:8080

As a betatester you may expect some issues when running galaxy in that way. Firstly, keep in mind that it’ll not perform as fast as a production-quality setup, it’s just a developer instance. Furthermore the node you’re in might have time limit restrictions, meaning that your instance will be killed in 30 minutes if you don’t reserve a slot beforehand as Martin recommended on the section “Run galaxy on a node”.

It has been a while since the GCC2011 took place in Lunteren, in the Netherlands. As a result of my visit, I gained some more valuable insight about what I like to call the metasploit of computational biology, if such an analogy could be made between computer security and biology.

A few words about Galaxy

With a 15+ core team and a very active contributor base, Galaxy is trying hard to provide a fix for the biomedical Babel in which life scientists work nowadays.

From its modest origin as a single perl script, later on morphing into a python web framework, Galaxy evolved rapidly. In short, Galaxy can be thought as the glue code that wraps and uniformizes a considerable amount of bioinformatics programs into a more consistent web interface.

But there’s much more under the hood: cluster job management, data conversion, dataset access controls, security, web services, etc… to name a few components and features.

“Everything is possible in Galaxy, As long as you can run it on the command line, you can incorporate it into Galaxy.”
– Hans-Rudolf Hotz, Friedrich Miescher Institute for Biomedical Research

But not everything shines in the galaxy since NGS tool inclusion hogged its main site at some point. This fact only proves the point that single sites like Galaxy main, handling 130.000 cluster jobs/month and 1TiB uploads per week, face sustainability issues on the big datasets era we’re living in. As a result, other than imposing reasonable cluster quotas, interesting scaling strategies are being tested on real research projects. Therefore, federation and cloud computing are the next steps on this particular quest to the bio-universe.

One interesting realization on the conference is that not only labs are rolling their own Galaxy instances, there was a big sequencing industry player showing some interest on it too:

“Galaxy is an attractive workflow engine candidate”
– Kirt Haden, Illumina Inc

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Summarizing from their official page, iGEM is about:

Using standard biological parts to build biological systems and operate them in living cells.

I’ve been tracking them since before joining KTH’s Computational Biology Masters degree. Having a quick look at past editions is both surprising and enlightening to see what they archieve year after year.

Perhaps the most rewarding sensation is being able to incrementally be aware of what they are talking about on their projects as I progress on my studies. Indeed, before joining the Masters I could barely understand the general idea, and got absolutely lost in the biological details. Now I can follow it after stepping on some stones that the master provided me.

Last year, together with Hassan, we based our final Biomodelling presentation on one project that matched the models we were studying on the course: Reaction diffusion systems.

Just a few weeks ago, while learning again how to stand up on a snowboard table on Romme, I had the great opportunity to talk with one of last year’s Uppsala Team advisor, Daniel, who not only enjoyed the experience, but together with his team, managed to contribute back some biobrick.

Today I would even like to try (dare?) and join one of those groups, just for the fun of learning how this amazing world actually works and to struggle with a real world problem.

And you ? What are you doing this summer ?

Fa un temps vaig comentar que parlaria més o menys regularment de BioDAC… bé, el cert és que durant el curs ja he anat prou atabalat i no m’hi he pogut dedicar tot el que voldria, però ara sí

Un dels objectius bàsics que comentava en el post inicial de la beca era:

(…) optimitzar tècniques de pattern matching usant instruccions SIMD presents en els microprocessadors d’avui en dia

Doncs bé, això he fet aquests dies de sol i pluja d’estiu, tot alternant entre platja i tecles

Què és SIMD ?

En poques paraules: procesar amb una sola instrucció, múltiples dades, d’aqui Single Instruction Multiple Data. No explicaré més a fons els detalls d’aquesta tecnologia, trobo que wikipedia ja em substitueix prou bé Només volia comentar uns detalls que m’he trobat al treballar-hi i que està bé tenir en compte si decidiu traduïr el vostre flamant algorisme per a que usi registres vectorials…

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No s’ha de posar pas un sh-bang per automatitzar una sessió de debugging repetitiva amb gdb, però el títol m’ha semblat encertat Tot i això gdb s’ho empassa, si ho voleu posar, és totalment inofensiu

Simplement cal fer ús del paràmetre “-x” i passar-li un fitxer de text amb les comandes que vols executar, una per línea, així de fàcil:

~> cat uni/tests/vect_tests/exec_gdb
file shifts
b main
r
display /t *a
display /t c
n
n
n

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