Online free courses/tutorials: there is plenty of material on line, which makes it sometimes difficult to filter what is really worthy. Here again, tips from blogs or colleagues from your network might serve as reference. Coursera is, in my opinion, one of the best platforms, due to the quality and versatility of its courses. There are several excellent courses related to Statistics and Data Analysis. Some of them are more general about R programming (e.g. Data Analysis,Computing for Data Analysis – both using R- ),but there are also more specific ones (e.g. Design and Interpretation of Clinical Trials, Statistical Analysis of fMRI Data,.. you can check the full list here.
I would like to mention here some other resources available for those with a math/statistics background who might be interested in getting some insight into genetics. As we mentioned previously in other posts, it is critical to understand the data you are dealing with and these websites will help you with that:
- Yourgenome, an excellent platform form the Wellcome Trust Sanger Institute
- Genetics course from the MITOpenCourseWare
- GeneEd resources from the NIH
- Introduction to Genetics and Evolution also from coursera
- Genetics from Scitable by Nature Education, where you can navigate through your areas of interest
An extensive list of additional Online Genetics Education Resources can be found at the NHGRI site
For those wanting to get an introduction to NGS, there is a Next Generation Sequencing Practical Course at EMB-EBI Train online. A more advanced tutorial, showing the use of R/Bioconductor packages for High-Throuput Sequence Analysis can be found here.
There are, obviously, countless courses and tutorials about R and specific packages. Besides, GitHub is becoming more and more popular.By creating Gist on GitHub you can share your code quickly and easily, see a quick example here.
Forums /discussion list: when you are stuck with something and you are not able to find a solution, specialized forums might come to the rescue. Either because your same question has been asked before, or because there is someone willing to help, you will most likely get your doubt solved. Two forums are particularly useful in my field, BioStar and SEQanswers. Talking about R programming, R-help from R Mailing List and Stack Overflow are two of the sites where you can found most of your doubts solved. Our life without them would be much more difficult for sure…
As I mentioned at the beginning of the previous post, it is sometimes difficult to find a balance between the time you spend learning and your more “productive” time. Besides for those of us whose work is also a passion, the line between work and personal interests becomes blurred quite often. And so we will spend much of our leisure time diving around new stuff that eventually will be useful in our work. Some might argue that the time spent in training or the amount of information you have access to might be overwhelming. Is it worth the effort? How much time should we invest in learning? Are we able to take advantage of what we learn? You can take a look at this video for more elaborate thoughts on the subject.
I hope the information contained in these posts might be useful… Your suggestions on additional resources will be more than welcome!