Finding appropriate bioinformatic problem sets for a beginner (R, Python)

Question

[sukhaniharish1234]

Hello,

I am interested in evaluating whether a career in bioinformatics is right for me. To that end, I have spoken to several colleagues, and they have recommended practice on real-world data sets from the life sciences. One colleague recommended a problem set created by Atul Butte, the Director of the Institute of Computational Health Sciences. He thought that it was linked to a course curriculum, but was unable to find it.

Since then, I have searched for problem sets in bioinformatics on my own using Google and also on this site. However, so far I have not found a good problem set for my skill level and goals.

Right now, I think that I am looking for the following (below), but I am open to suggestions as well.

• Problem sets appropriate for a beginning programmer in R and Python
• Problem sets that involved real world data
• Problem sets that help me familiarize myself with one or more type of high throughput data (e.g. RNA seq, whole genome data).

Any type of data fitting that description would be wonderful, but I am very interested in clinical trials and drug repurposing. Thanks.

Answer 1

[WouterDeCoster]

I can definitely recommend Rosalind, in which you get real bioinformatic problems of increasing difficulty.

[gandrescabrera]

Nice recomendation!

Answer 2

[gandrescabrera]

I would recommend you some manuals from R packages. You will find a lot in Bioconductor.

For example edgeR have real-world examples as case examples, which you can DL the datasets. https://bioconductor.org/packages/release/bioc/vignettes/edgeR/inst/doc/edgeRUsersGuide.pdf

This is nice because is being explained.

Im working/learning in an Institute of biomedicine for a bunch of months, and these case studies helped me a lot to get into the notion, and interpret correctly the results and parameters.

Cheers!