Bioinformatics Specialist Maria Lehtivaara teaches people how to speak the language of data processing.
Sharpening data processing tools
CSC's five-day Bioweek course in February attracted a crowd of bioscientists to Keilaranta, Espoo. The programme included the basics of R and Unix, and an introduction to data processing and CSC's Taito supercluster computing environment. Towards the end of the week, participants were able to harness RNA-seq data analysis.
The course was divided into three modules that participants could pick and choose from at will. About 15 people took part in each module. The R and Bioconductor section was particularly popular.
– R is an environment that you'll encounter when you follow publications in the field. I came here to update my knowledge of it. The Bioconductor section in particular is something you encounter in our field, that is, NGS analytics, says Head of Laboratory Pekka Ellonen from the Institute for Molecular Medicine Finland (FIMM).
– It would be good to know how to use tools that can churn data. We've both studied some basic things at some point, but had to come here for a bit of an update, says his coursemate Senior Laboratory Technician Maija Lepistö from FIMM.
As soon as they get back to work, they'll be putting what they learnt in this two-day section into practice – but during the course, there's time to stop and think.
– I could, of course, do this alongside my regular work, but it's so hectic there. This course has really given me the time to revise and learn more about the subject. And, of course, the good instructors and examples help, says Ellonen.
Doctoral student Tapio Nevalainen from the University of Tampere took part in the full week of courses. His research team is continually working with large datasets (RNA-seq and DNA methylation) and traditional 'wet lab work' has transformed into computer analyses.
– Our team has one completely overworked bioinformatician. We decided that the other researchers should also delve deeper into bioinformatics, so that all the work doesn't fall on one person's shoulders. I'm also very interested in enhancing my own expertise in bioinformatics, as it's in ever increasing demand, says Nevalainen.
He'll be able to apply what he's learnt directly to his own data.
– The most useful thing for me was the RNA-seq section, which gave me a good understanding of how raw data is processed into results. It was also interesting to learn how to use the Taito cluster, as it initially felt so challenging.
According to course leader Maria Lehtivaara, participants naturally asked the most questions about issues relating to their own data.
"They'll first need to understand the language, and only then will they be able to take care of practical issues relating to data processing or the various stages of analysis and its tools."
– A bioscientist will, for example, receive analysed data and associated commands or R scripts from a colleague, collaborator or predecessor. They'll need some knowledge of the topic to interpret results, edit scripts for their own use, or deal with questions arising from analyses.
– They'll first need to understand the language, and only then will they be able to take care of practical issues relating to data processing (using Taito) or the various stages of analysis and its tools (RNA-seq), says Lehtivaara.
In addition to revision, the knowledge gained during the week also helps participants gain confidence.
– The course lived up to my expectations and I got more out of it than I expected. I would recommend the RNA-seq training to anyone who has anything to do with the data in question. Even if you don't have to analyse results yourself, it's important to understand how the analyses are performed, says Nevalainen.
– I'd also recommend the Taito cluster training to anyone who works with large datasets. Taking advantage of the Taito cluster would make many research teams' analyses both easier and quicker.
Also Lepistö believes that the course is still of great benefit even if you already have some sort of feeling for the programmes.
– Even if you're already familiar with it, you'll gain the kind of confidence that will enable you to start using it as soon as you go to work. If I hadn't come here, I wouldn't have – I'd have used those older, less effective ways of working, says Lepistö.
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