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The word “microbiome” seems to appear everywhere these days: articles about how to eat for a healthy microbiome, research about how the gut microbiome impacts both your gut health AND your brain health, companies promising to improve your skin through skin-microbiome targeted products, news about how the microbiome can even affect your response to chemotherapy drugs. It’s certainly an exciting field to be in right now - but if you’re not already part of it, you might be wondering how to become a microbiome researcher. I’ve outlined some tips below on how to break into this exciting and fascinating field of research.

Get a degree in a related field

As with many career paths, you can start with getting a Bachelor’s degree in a discipline related to microbiome research. While my degree was in Biological Sciences, you could also major in Microbiology, Biochemistry, Biological Engineering, Molecular and Cell Biology, or even Computer Science or Bioinformatics (more on that later.)

Regardless of your degree program, you’ll probably want to take classes about microbiology, immunology, cell biology, biochemistry, organic chemistry, coding, and statistics. These courses will provide a great foundation for the topics and skills that come with more advanced microbiome research.

What about an advanced degree? While you don’t strictly need a master's or PhD to pursue a career in microbiome research, they will certainly help, especially if you want to be leading and designing projects yourself. Getting a graduate degree can also be a great way to meet more people in the microbiome research field and develop the skills needed to carry out microbiome research. 

Get involved in a research lab

While you are getting your degree, check out the research opportunities at your university. It doesn’t have to be in a lab studying the microbiome (though if it is, that’s awesome!) Even just getting any research experience at all will help you understand the process of critical thinking, problem solving, hypothesis generation, and results interpretation. Many universities offer scholarships or fellowships to students wanting to get involved in research, and some may allow you to get credit hours for the research you perform.

The process of getting involved in research will differ a little depending on school, but often, you can email the professor of the lab and ask about openings or opportunities to get involved.

Learn some coding skills

No, really. A lot of microbiome research these days relies on using software programs to analyze huge sets of data, and it’s really important to be able to parse through that data, process it using the appropriate tools, and visualize or statistically compare experimental groups. Experience in R, Python, and/or Bash/Unix shell will go a long way towards a career in microbiome research.

As a side note, this route is a great way to break into the field if you already have a degree and don’t want to go back for another, or if you are looking to make a career switch. Taking online coding classes through Coursera, Datacamp, or any of the numerous other platforms for learning coding will give you valuable skills that can be applied to microbiome research positions. Especially hot right now are machine learning and artificial intelligence models, if you want to get real intense.

Learn how to read the literature

With all of the buzz about microbiomes out there, there is bound to be a lot of psuedoscience mixed in with the real research. Learn how to read appropriate sources for information: get familiar with how to read and evaluate a scientific paper, what sources are actually reputable, and what information is true versus what is overhyped and misunderstood by the press. This will help you critically evaluate new information when it comes out. Some good places to search for new journal articles include PubMed and GoogleScholar. I also really like Dr. Elisabeth Bik's MicrobiomeDigest, which compiles new and interesting microbiome research weekly. You could also follow microbiome researchers on Twitter - they are often sharing their latest papers and research insights!

I hope this information is helpful for anyone considering a career in microbiome research. It’s a fun and interesting area to be in right now, and I think the future of microbiome research holds a lot of promise!

ggplot2 is a system for creating graphics in R, and is popular among data scientists for its powerful data visualization capabilities. The program is based on The Grammar of Graphics, a foundational syntax for creating graphics for scientific journals, news outlets, and anything else that relies on quantitative data viz. I've been using ggplot for around 6 years now, and still learn new things all the time - I've decided to gather some of my favorite tips and approaches and write about them here to share with you.

In this series I will outline some of my favorite tips and tricks for utilizing ggplot2 to its fullest, in order to create beautiful, colorful plots with your own data! Today's post is all about color.

Tips for coloring your ggplot graphs

One of the first things a reader will notice when they look at your plots is the colors. You want your chosen palette to quickly and easily convey the different variables in your data, in a way that is colorblind friendly and, if you're like me, aesthetically pleasing. You'll want to make sure that the palette you choose has enough colors to assign to your variables so each has a distinct color. 

You can set a color scheme in a few different ways:

1. Install and load an existing color palette package in R. The wonderful thing about R is that since it's open source, many brilliant folks around the world have developed packages that you can install easily. Some of my favorites are wesanderson,  ghibli, ggsci (a collection of palettes inspired by journals and sci fi movies/TV shows), MetBrewer (palettes inspired by works at the Metropolitan Museum of Art in New York), and nationalparkcolors (inspired by the colors in retro National Park posters and images.) Installing and playing around with existing color palette packages is a great way to become familiar with the syntax of adding the color layer to your ggplot code. 

2. Use a color theme generator to create a custom palette. If you want to create a palette that is a little more custom, you can utilize one of many available online color scheme generators. Coolors.co is one such generator that I use - it allows you to start with a randomized palette, which you can then add and delete colors to to find an arrangement that suits your taste. You can specify the generator to generate using a monochromatic, analogous, complementary, triadic, or tetradic method, depending on your needs. I like Coolors because it includes an automatic colorblindness viewer, to see how accessible your palette is to those with varying types of colorblindness.

Another great color palette generator is schemecolor, which allows you to browse user-submitted and autogenerated palettes based on different starting colors, themes, holidays, and more. 

With any color palette generator, what you will ultimately need to collect is the hex values of each color. Keep a list of the hex codes as well as the color name handy for tip 3.

3. Write reusable, flexible code for defining your own custom ggplot2 palette. Creating a reusable code chunk that defined my color palette for a given project made me feel like I had leveled up in my coding. Currently I maintain a script for each paper/project I am working on, creating functions for each separate palette that can be run with any script I use for generating my plots.

This is why you will need to hang on to the hex codes from the previous step- the basic premise of this approach is naming a vector of hex codes, creating a function to access those codes, creating a list of palettes (combinations of the color codes you just specified), and creating a function to access those palettes that can be used with ggplot2 syntax.

drsimonj has already created a really wonderful tutorial in creating custom color palettes for ggplot2, which I highly recommend checking out! I based my personal color palette scripts on this tutorial.

I hope these tips are helpful in learning how to create beautiful graphics with ggplot in R! Next time I will write about the use of ggplot's themes for adjusting the aesthetic and layout of your plots.