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1/Folks with mainly biology training sometimes ask me for resources that can help them learn bioinformatics. This short thread has my recommendations at various levels.
2/First, if you mainly want to know how to perform various sorts of analyses, highly recommend the @Bioinfodotca Canadian Bioinformatics Workshops. Individual workshops cover a number of different domains, some point-and-click, others w/ more command-line. https://bioinformatics.ca/workshops/
3/Many require no prior bioinformatics or command-line knowledge. Some may expect a little familiarity with Linux and R. (And if you have none, you can get it from the Introduction to R course.)
4/Of course they are usually once a year (sometimes @cshlmeetings will have an additional omnibus course that combines several workshops). And not everyone can easily find the fees (although there are scholarships). That's why all the materials are also online year-round, free!
5/Here are the 2018 workshops (more recent ones are supposed to be online too but the files seem missing right now). In the "Pathway and Network Analysis" workshop (which I teach part of) you can find slide decks and YouTube videos for each lecture. https://bioinformatics.ca/workshops/workshops-2018/
6/ @Bioinfodotca YouTube channel also collects all the videos in a central location. Some 2021 workshop videos already up. There's no substitute for the actual courses with instructor interaction & practical exercises but the videos should get you started. https://www.youtube.com/channel/UCKbkfKk65PZyRCzUwXOJung
7/Second, if you are going to be doing bioinformatics analysis on a regular basis you will be way more effective if you learn how to use your tools and organize your work better. I recommend @thecarpentries workshops and lessons. https://carpentries.org/
8/ @datacarpentry workshops teach you how to organize, manage, and analyze data, helpfully focused on applications to particular domains like genomics.
9/Software Carpentry workshops are focused more on tools for software development—including Python and R.
10/Third, to learn the details of computational biology algorithms and get ready to create your own, I recommend @PhillipCompeau and Pevzner's _Bioinformatics Algorithms: An Active Learning_ approach. Available as a book or interactive courses ($). https://www.bioinformaticsalgorithms.org/
11/First five chapters available online for free. https://www.bioinformaticsalgorithms.org/read-the-book
12/Lecture videos for the whole book available on YouTube. https://www.youtube.com/c/bioinfalgorithms/playlists
13/They also have Rosalind, an awesome and free bioinformatics and algorithm problem-solving platform that you can develop your skills on. http://rosalind.info
14/There is no fourth step. If you can master that book, you're ready to join your local computational biology research group. Have fun!
