Here are some books, courses, and software you may find helpful on your bioinformatics journey
As a way to keep the OMGenomics blog and show free (and keep me alive while I try to make it better), some of the links here are affiliate links, which means that the companies pay me a small commission if you decide to buy their products through these links (*and fun fact: also if you buy anything else on Amazon after visiting the links). These are all things I would recommend anyway, so hopefully this will be a valuable list of resources as you are getting deeper into bioinformatics.
Books to change your perspective
For building a great career
Cal Newport is a theoretical computer science professor, and his passion project for many years has been figuring of what makes people happy in their careers. He wrote a book called Deep Work: Rules for Focused Success in a Distracted World, that I found really resonated with me. The idea of deep work is something that I have applied a lot in my own work, and it really drove me to set better boundaries and protect some time every week and every day to actually get better at what I do, and not just put out email fires constantly.
I also highly recommend reading Cal Newport’s first book on this topic, So Good They Can’t Ignore You: Why Skills Trump Passion in the Quest for Work You Love which describes how getting really damn good at what you do gives you a better life than just trying to “find your passion.” This then becomes the reason to pursue Deep Work for yourself because it’s the best way to build those skills that will buy you the power of control over your working life.
I just zoomed through both these books in one weekend, and I find it easy to relate to Cal Newport when he talks about trying to succeed at graduate school and figuring out how to build a great career. This is a huge contrast to the way most people online talk about “finding your passion.” I find that I become passionate about something after getting really good at it and understanding it on a deeper level. This certainly happened with bioinformatics, and it even happened on a smaller scale with multiple school projects. I gave a presentation to my climate change class in college about electric cars back in 2010, so I liked Tesla before it was cool 😉 #hipster. I’ve been crazy about electric cars ever since that project. I vowed that my next car would be electric, so since I’m still poor (no Tesla money yet!), I now drive a cute little nerdy-looking Nissan Leaf. Anyway, you can build passion by learning and getting really good at things, and if you want to learn more about why deep work is more important than finding that elusive passion, go read Cal Newport’s books!
These are some of the online courses I recommend you check out. Different people love and hate the same course, so feel free to skip around and just take a peak at what you find interesting. Bioinformatics is a huge field, so you don’t have to love all of its subfields, but this should give you a taste of a few different perspectives:
- Genomic Data Science Specialization from Johns Hopkins on Coursera. Within that specialization I especially recommend Ben Langmead’s course using Python for working with DNA sequences. Ben is the creator of Bowtie who first figured out that the Burrows Wheeler Transform could be used to create an index of the genome for fast, efficient genome alignments, which made a big difference in the field.
- For machine learning, Andrew Ng’s Machine Learning course on Coursera is a classic that I highly recommend.
I went through this and did all of the programming assignments in MatLab because I had just finished Linear Algebra. If you are not completely comfortable with linear algebra, skip the programming assignments and just watch the lectures.
- For learning hard-core algorithms in bioinformatics, check out UCSD’s specialization on Bioinformatics.
Link: Introduction to Bioinformatics
Please don’t read this textbook cover-to-cover! Use it to flip through different fields like it’s a magazine, and see what catches your interest.
A PhD thesis or an entire career can be built by deeply understanding only half a chapter’s worth of background information.
What this book is best for is getting the lay of the land, seeing what fields exist, and helping to understand the lingo of each field enough to find the less well-known frontiers where new research can be done.
Link: Learning the bash Shell: Unix Shell Programming (In a Nutshell (O’Reilly))
This book is a great place to get started with learning bash. It gives you a nice tour of what is possible while going deep enough that you can practice examples and apply them to your own work.
Bioinformatics Data Skills
Link: Bioinformatics Data Skills: Reproducible and Robust Research with Open Source Tools
Once you got the basics of bash and are comfortable around the command-line, this book will take your skills to the next level. It is all about being smart with how you manage big data and build pipelines for reproducible research.
This neat little program (for Mac) is an upgrade for your clipboard, allowing you to copy multiple things and paste them again. This is such a time-saver and lets you remember that piece of code you copied but accidentally copied over it with something else, not you can just go down the list and find it again.
iTerm is a replacement for the terminal on Mac. I switched to it after some frustration with creating multiple tabs and windows in the terminal, and I have never gone back (except to make the first bash tutorial video)
Circa software for making circos plots
(Sneaking this in here) I made this software myself to give people an easy way to create beautiful circos plots without writing any code. It came out of my own frustration with creating circos plots during my PhD, so this is the first software I just HAD to make now that I call the shots 🙂
My fiancé gave me this microphone for Christmas to help get me started on this crazy business experiment. It was a good motivating factor. I didn’t know what a difference it made until we tested it, and it was like the difference between hearing someone through a phone and in person. It makes a huge difference.
2. Camera: my iPhone 6
It turns out iPhones have pretty decent cameras. And I can plug the Blue Raspberry microphone straight into the iPhone.
3. Tripod with phone adapter
We actually brought this tripod back to CSHL to record my thesis defense. When compressed it is a few inches too long to fit in a backpack, and you can extend it to be as tall as a person. I use this for all of the videos where you see me talking. Which phone adapter you get is really important. I once ruined an old phone of mine with another adapter that squeezed it so much over time that the glass screen popped out the side (we were trying to film our tortoise Python while we were at work). This adapter is completely adjustable so it doesn’t squeeze the life out of my new phone, which was kind of my highest priority after the turtle-cam experience.
4. Screen recording: QuickTime Player (comes with Mac computers)
This works fantastically. There are paid screen recorders out there, but I haven’t had any problems just using QuickTime. It’s simple, high-quality, and makes circles whenever you click so viewers can see what you are doing.
5. Video editing: iMovie (comes with Mac computers)
Pretty easy to use, tons of tutorials out there. I only ran into one oddity to look out for: If you want a high-resolution video, the very first footage or photo you add to a movie must have that high resolution. For some reason it sets the maximum resolution by the first piece of media you add, even if you remove it later, and there is no way to change it without starting over. Now I just have to be careful to check that the resolution is high right after adding the first media to the project.
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