Enhancing Figures: ggplot2 to Adobe Illustrator

Simon Tye, PhD student
Siepielski Lab, University of Arkansas

Introduction

Many graduate students use the open-source programming language R to compile, examine, and visualize data. While there are numerous freely-available resources online for students to learn how to compile and examine data (e.g., R Cookbook), many graduate students still have difficulty crafting stimulating figures for publications or presentations. These figures are typically created via one of the many visualization R packages that are available (e.g., ggplot2, lattice, leaflet, plotly) that provide numerous options for altering different aspects of figures, from color schemes to axis labels to typography. However, there are inherent limitations to customizing figures when using a specific package’s framework and it may be cumbersome to write code that performs the required task.

To help graduate students enhance their figures and dissemination abilities, I am going to briefly show you how to edit a figure that was created in R via Adobe Illustrator. For this tutorial, I will be using a built-in dataset in R, iris, and the Essential Classics Workspace in Adobe Illustrator CC 2020. This dataset has information on sepals and petals for 3 species of Iris (I. setosa, I. versicolor, and I. virginica). Below is an overview of these data.

head(iris)
##   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1          5.1         3.5          1.4         0.2  setosa
## 2          4.9         3.0          1.4         0.2  setosa
## 3          4.7         3.2          1.3         0.2  setosa
## 4          4.6         3.1          1.5         0.2  setosa
## 5          5.0         3.6          1.4         0.2  setosa
## 6          5.4         3.9          1.7         0.4  setosa

R: Summarizing your data

First, we need to calcuate the means, standard deviations, and standard errors of these data for plotting. We will due this via the commonly used dplyr package, as shown below. For brevity the data are abbreviated as follows: Sepal.Length = SL, Sepal.Width = SW, Petal.Length = PL, Petal.Width = PW.

library("dplyr")

iris.sum <- iris %>%
  group_by(Species) %>%
  summarize(
    # Sepal.Length
    SL.length    = length(Sepal.Length),
    SL.mean      = mean(Sepal.Length),
    SL.sd        = sd(Sepal.Length),
    SL.se        = SL.sd / sqrt(SL.length),
    # Sepal.Width
    SW.length    = length(Sepal.Width),
    SW.mean      = mean(Sepal.Width),
    SW.sd        = sd(Sepal.Width),
    SW.se        = SW.sd / sqrt(SW.length),
    # Petal.Length
    PL.length    = length(Petal.Length),
    PL.mean      = mean(Petal.Length),
    PL.sd        = sd(Petal.Length),
    PL.se        = PL.sd / sqrt(PL.length),
    # Petal.Width
    PW.length    = length(Petal.Width),
    PW.mean      = mean(Petal.Width),
    PW.sd        = sd(Petal.Width),
    PW.se        = PW.sd / sqrt(PW.length))

R: Creating a figure with the ggplot2 package

We will then use these summarized data to plot a figure using the R package ggplot2, one of the main third-party packages that is used to construct data visualiations in R. First, we will construct a simple barplot of the petal lengths for each Iris species. The first few lines are code are basic ggplot2 functions that load the dataset, define the barplot that will be generated, and add error bars based on our previous calculations. For this figure, I chose to use standard deviations for the error bars, simply because the standard error values were so low that the error bars were inconsequential. The subsequent lines (e.g., theme_bw…) define different elements of the plot and are not wholly necessary, but I find them useful. For example, the axes and tick marks in ggplot2 are a dark gray color by default, and the last section of code changes the color of these elements to black.

library("ggplot2")

ggplot(data = iris.sum, aes(x = Species)) +
  geom_bar(aes(y = PW.mean, fill = Species), position = "dodge", stat = "identity") +
  geom_errorbar(aes(ymin = PW.mean - PW.sd, ymax = PW.mean + PW.sd), width = 0.5, position = position_dodge(width = 0.5), color = "black") +
  theme_bw(base_size = 12) +
  theme(panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        panel.border = element_blank(),
        axis.line = element_line(color = "black", size = .25, lineend = "square"),
        axis.ticks = element_line(color = "black", size = .25),
        axis.title = element_text(color = "black"),
        axis.text.y = element_text(color = "black"),
        axis.text.x = element_text(color = "black"),
        axis.title.x = element_text(margin = margin(t = 20, r = 0, b = 0, l = 0)),
        axis.title.y.left = element_text(margin = margin(t = 0, r = 20, b = 0, l = 0)),
        axis.title.y.right = element_text(margin = margin(t = 0, r = 0, b = 0, l = 20))) +
  labs(x = "Species", y = "Petal Width (cm)")

R: Transferring a ggplot2 figure to Adobe Illustrator

While the resulting figure might suffice for a quick presentation, it is not very captivating or visually stimulating. To remedy this, we are going to add some elements in Adobe Illustrator, which is often available through academic institutions for a discounted price. For example, the entire Adobe Creative Cloud suite is available through the University of Arkansas for ~$10/year. Luckily, it is a simple process to export figures from R and import them into Illustrator; you just need to export it as a PDF.

Many R users utilize the RStudio interface, which makes the export process rather straightforward. Once you run the code that creates a particular figure (i.e., the code listed above), the resulting figure should display in the lower right corner of your RStudio interface. Above the displayed figure, click Export and Save as PDF. In the pop-up display, you can change the size and export location of the figure. The initial figure size is determined by the Device Size, which is simply the size of the window within RStudio that is currently displaying your figure. After changing the size parameters and save location to suit your needs, click Save.

Adobe Illustrator: Adjusting the artboard

Next, locate this file on your hard drive, right-click it, and open it in Adobe Illustrator. Depending on your Illustrator settings, the loaded figure may or may not be placed on a similarly-sized artboard (i.e., the canvas in Illustrator). Typically, only the graphics that are on an artboard will be exported, though you can easily change this setting when saving a file. If you need to adjust the size of your artboard, select the Artboard Tool (red circle, Fig. 1) or press the keyboard shortcut Shift + Q. Then click and drag the corners of your artboard to the edge of your figure.

Figure 1. How to adjust an artboard (i.e., canvas) in Adobe Illustrator CC 2020.

Adobe Illustrator: Removing bounding boxes

The second step is to remove figure elements that impede certain edits you may wish to perform. Specifically, ggplot2 figures have various bounding boxes that, while not noticeable at first, will get in the way when you want to select elements later on. The easiest way to accomplish this is to select the Direct Selection Tool (red circle, Fig. 2) or press the keyboard shortcut A. Then click and drag over one corner of the figure (red square, Fig. 2), and press Delete twice. It is very important that you press Delete twice, as pressing it once will delete these specific points (i.e., in the corner), and pressing it twice will delete all associated points (i.e., the remaining points in the object).

Figure 2. How to remove bounding boxes of a ggplot2 figure. Be sure not to select any important elements of your figure, such as the barplot or legend.

Adobe Illustrator: Ungrouping the plotting area

The third step is to make ungroup objects within the plotting area (red rectangle, Fig. 3) so that they may be edited separately. When a PDF is exported from R, the objects within the plotting area are in a Clip Group. To remove them from this group, select the plotting area (red rectangle, Fig. 3) and click Edit Clipping Path on the left end of the top toolbar (red circle, Fig. 3). Next, reselect the plotting area and go to the top menu and click Object / Ungroup. Now all the objects within your plotting area have been ungrouped and may be edited separately.

Figure 3. How to ungroup objects within the plotting area (red rectangle) of a ggplot2 figure.

Adobe Illustrator: Enhancing your ggplot2 figure

Now that you have imported your ggplot2 figure into Illustrator, removed the bounding boxes, and become acquainted with the basic tools required to move objects, the sky is truly the limit. To finish this tutorial, I will show you how to import images of the focal Iris species in this dataset and match the color of each bar to a prominent petal color of each species. First, I found images of each Iris species, that are available for educational use via a Creative Commons license, on Wikipedia (Fig. 4). After renaming the files and placing them within your working project folder, drag the files into your Illustrator workspace.

Figure 4. Images of the the focal Iris species from the built-in R dataset, iris. Image credits, from left to right, are Radomil (CC 3.0), D. Gordon E. Robertson (CC 3.0), and Eric Hunt (CC 4.0).

Figure 4. Images of the the focal Iris species from the built-in R dataset, iris. Image credits, from left to right, are Radomil (CC 3.0), D. Gordon E. Robertson (CC 3.0), and Eric Hunt (CC 4.0).

Adobe Illustrator: Adjusting image sizes

After importing the image files into your workspace, you will likely need to resize the images (e.g., same widths and/or heights). This may be done by clicking the Selection Tool, holding the Shift key (to ensure the image stays proportional while scaling), and dragging the image to the desired size. After you determine the size of one image, you can quickly make the remaining images the same width or height via image editting tools located at the top of the workspace (Fig. 5). You will notice there is a cropping tool, as well as boxes for horizontal and vertical dimensions. For this example, I clicked on a bar within the plotting area, recorded the horizontal dimension of the bar (that was displayed in the top toolbar, and made each images the same width as its respective bar. After resizing the images, I would recommend adding a small border around each image, to emphasis and differentiate them from the white background. This can be done several ways, but the most straightfoward would be to use the Rectangle Tool to create a rectangles, each with a black border and no fill, that are the same size as the images.

Figure 5. How to edit the dimensions of imported or embedded images in Adobe Illustrator CC 2020.

Adobe Illustrator: Editting the plotting area

Next, I am going to match the color of each bar in the plot to a prominent petal color of the associated Iris species. To do this, use the Selection Tool to select a particular bar (red rectangle, Fig. 6), then select the Eyedropper Tool (red circle, Fig. 6) and click on the petal of the associated species (red arrow, Fig. 6). After repeating these steps for each bar, you can go then to the Color panel, on the upper right of the workspace, and find the color hex code for each petal. To improve your original code, these hex codes can then be entered into the original ggplot2 code (e.g., by adding scale_fill_manual(values = c(“#5f5da9”, “#7556a4”, “#8c8ec6”))) to automatically match the colors of your barplot and focal taxa.

Figure 6. How to match the colors of your barplot and the petal color of the associated Iris species.

Adobe Illustrator: Exporting the enhanced figure

Once you are satisfied with the resulting figure, go to the top menu and click File / Save As. You should always save your projects as either an .ai file (Adobe Illustrator format) or a PDF with the Preserve Illustrator Editting Capabilities box checked. Like many things in your research career, this draft of your figure will likely be revisited to make additional edits, and either of these file formats can be reopened and edited in Illustrator. To save your figure for a paper or presentation, go to the top menu and click File / Export / Export As, then select the appropriate file type (e.g., .jpg, .tiff) and settings (e.g., resolution). Now that you know a little bit more about how to combine the functionality of R with the creative power of Adobe Illustrator, I encourage you to spend some extra time creating stimulating data visualizations for future papers, presentations, and outreach events. A forthcoming blog post will detail more advanced editing techniques that may be used to further enhance R figures using the Adobe Creative Cloud suite. For more information about the outlined steps or suggestions for future blog plots, feel free to email me at simontye@uark.edu.

Figure 7. Comparison between original and enhanced ggplot2 figure. Image credits for insets on the enhanced image, from left to right, are Radomil (CC 3.0), D. Gordon E. Robertson (CC 3.0), and Eric Hunt (CC 4.0).

Electronic Lab Notebooks: Hope or Hype?

The lab notebook has long been hallowed as the fundamental unit of scientific research. From the cuneiform tablets to meticulous scrolls, written records of scientific discoveries have played a key role in human innovation. Because of this importance, before I switched to an electronic lab notebook, I would often wake up in a cold sweat, dreaming that fire, flood, or calamity had befallen the lab overnight and all of my treasured data and lab notebook had been forever lost. But in the wonderful age of cloud computing and digital documents, my fears are assuaged. In case of emergency, my trusty electronic lab notebook has my back.

What is an electronic lab notebook?

An electronic lab notebook is a complete and semi-digital set of documents that are stored on a device and often also in the cloud. Entries could be entirely stored in an app (either made for lab notebooks or a generic note-taking app) or exported in a generic file format (i.e. .pdf) and stored in your normal file system (i.e. Finder/Documents). These files, whether in an app or in your own filing system, are typically backed up in the cloud. This increases security (in case of loss/destruction/theft of your device) and also allows you to access your entries from other devices (such as at home or on the go from your phone). I will go into detail about how I manage each of these aspects in this blog post.

I use my iPad with an Apple Pencil as my electronic lab notebook. I keep my lab notebook entries in Microsoft OneNote. I export completed entries as PDFs and save them on my computer in a Box Sync folder, which saves them on the cloud. When I am doing sterile lab work, I store my iPad and Apple Pencil in Ziplock freezer/sandwich bags that I spray with ethanol.

ELNFigure 1: My iPad and Apple Pencil in bags that can be sterilized with ethanol. You can write on the iPad with the Pencil when both are in bags!

Why keep an electronic lab notebook?

  • Easy sharing between lab members and teams:
    • I am working with close collaborator who is based in New Zealand. It was very useful that they could reference my lab notebook as needed.
    • This is also helpful when overseeing undergraduate researchers. Most of my undergrads keep a semi-electronic lab notebook. In the lab, they write in a paper lab notebook and upload scanned copies to our shared Google Drive (thanks @Meg Duffy for sharing her lab’s management system in this Dynamic Ecology post). This way, I can see their progress. I add them to view my electronic lab notebook through Microsoft OneNote folder sharing so they can see my progress on the project in real time and can download relevant protocols on their own.
  • Better back-up and accessibility. No more concerns about the building burning down or flooding and losing all of your data or notes–the notebook is always backed up the cloud and is accessible on any device. This has saved me a few times when my advisor emailed/texted me a quick question while I’m away from the lab and I could quickly send them a screenshot of the relevant results from my lab notebook.
  • Notebook can be encrypted and password protected (if necessary): I’ll discuss security with electronic lab notebooks at length below, but with PDFs and especially in Microsoft OneNote, it’s easy to protect your work with a password, or encrypt your documents (such as with an app like Encrypto). Besides keeping my work on an encrypted server, I don’t individually lock or password protect my lab notebook because most of my lab notebooks are accessible by members on various collaborative teams.
  • More features: Unlike paper lab notebooks, it’s easy to add a lot of different unique features to an electronic lab notebook. For example, I can easily embed (and write in) photos in my entries that I take as I complete an experiment. With a click of a button, I can paste plots from R, as well as link to my RMarkdown/Rproject files. I can insert PDFs and documents into my entries, as well as insert tables that auto-update from linked Excel spreadsheets. I can also search all of the text in my lab notebooks, which is nice when I’m trying to find something and forgot which entry contains the experiment.

Because everything is already online, I can easily attach lab notebook entries (and their names) to emails, calendar invites, and other project management apps I use like Todoist, Trello, and Toggl (see this blog post I wrote last year about how I use these apps to streamline my project management workflow). Because my figures and conclusions are all in one place (and digital), I can easily drag and drop figures from my lab notebook into presentations for my advisor, lab meetings, or meetings for collaborators.

I use a tablet for my electronic lab notebook, and it’s nice to have a timer, calculator, a web browser, and music source nearby.

Do I need a tablet?

No, you do NOT need a tablet to keep an electronic lab notebook. You can use all of the functionality of an electronic lab notebook by simply writing in it on your computer. However, it’s much easier to write notes in your notebook while you are doing experiments (assuming you are doing experimental work) if you have a device close to you. If you’re not into keeping your computer near you in lab, or if this isn’t safe, then scanning a paper lab notebook may be a better option.

I use a tablet for my lab notebook. I purchased a used Apple iPad with an Apple Pencil on Ebay and has been working well for the past three years. When I am wearing nitrile gloves in the lab, especially if I am working in a Biosafety Cabinet, I put my iPad in a gallon Ziplock freezer bag and my Apple Pencil in a Ziplock sandwich bag and spray both down with ethanol (see picture above). That way, I can touch them with gloves on and everything stays sterile. This seems more sterile than a paper lab notebook, I’d say! Also, music from the iPad seems louder when it is in the bag, bizarrely.

Besides tablets, a PLOS paper on electronic lab notebooks describes how some researchers have been using Apple Watches to read protocols and keep time. This seems better for biochemists and molecular biologists who are frequently using highly repetitive, timed protocols. Right now, this is too much for me, but others in my lab have an Apple Watch (although not for lab notebooks) and seem to like them. I worry about touching an Apple Watch with gloves on.

Apps for electronic lab notebooks:

There are a lot of paid options, but if you’re looking for free options here are my top suggestions (in no particular order):

  1. Microsoft Word: This means saving documents on your computer as PDFs, printing them off, and signing and dating them as experiments are completed OR saving them as secure PDFs and using Adobe Acrobat Pro to sign them. It works but isn’t efficient, hard to search, and it is easy to become disorganized. I’m switching away from this. Recently, you can annotate Microsoft Word documents with an Apple Pencil, but it’s still clunky and I think that Microsoft OneNote (described in detail later) is better.
  2. Google Docs: You can write and update all of your lab notebook entries in Google Docs. A nice benefit is that you can track changes easily, but I worry about how to sign and verify lab notebook entries in Google Docs. I would imagine this would work well if you’re doing highly collaborative work and for some reason don’t want to share a OneNote notebook.
  3. Evernote: This free program with an optional paid subscription service has, until about 2017, was a favorite for electronic lab notebooks. It has great features like inserting documents, tables, pictures, writing in line with text, screenshots, handwriting searching (via iPad app Penultimate), and tagging for easy searching through entries.
  4. Microsoft OneNote: This is what I use. OneNote is a free program if you have Microsoft 365 and has lots of great features, including allowing handwritten observations side-by-side of typed notes and protocols. You can also insert and edit Excel spreadsheets directly from within OneNote entries, which is very helpful when wrangling datasets, and OneNote has all of the features (and more) Evernote has. OneNote also has an excellent iPad app. You can see below for pictures of how I set up my lab notebook in OneNote.
  5. Benchling: This is new software, free for academics, which has become increasingly popular with molecular biologists because it has some really nice native features for cloning and bioinformatics. I decided not to use this because it is web based, so I couldn’t use it in the field. It’s new and pretty buggy. Not recommended for ecologists.
  6. Notability: If you’re planning on handwriting the majority of your lab notebook entries and want easily printable PDFs that auto-upload to the cloud, I’d suggest using Notability. I’m a big fan of OneNote and avoid paid apps, but several of my colleagues are big Notability fans and I wanted to include it here.

There’s a nice Nature Toolbox article outlining other considerations for choosing an electronic lab notebook here and a comparison of ELN options from Harvard Medical School here.

Backing up to the cloud:

Saving documents in most of the apps I listed above will automatically back up your digital lab notebook entries to the cloud. I would encourage you to turn on version control so you and others can track when changes are made and protect yourself against any fraud accusations. In addition to keeping version control tracking on my lab notebook entries, once an entry is finished for the day, I export it as a PDF and upload it to the cloud (in my case, a Box Sync folder), which also maintains version control on the PDF. Box is supported by my university, but any other cloud provider such as Dropbox and Google Drive work just as well.

Electronic Lab Notebook security:

As mentioned above, electronic lab notebooks have pros and cons with security. A big pro is back-up to the cloud and version control. However, in some ways, an electronic lab notebook is not as secure as a paper one. Most academic labs that don’t need to meet FDA regulations or might file for a patent don’t need this level of security, but I’ll briefly outline some additional security measures.

  • Not all apps support version control: With a digital document, how do you know that an entry, note, or picture was actually taken on the day that you say and not added after the fact? The gold standard is to use version control on your lab notebook, but this is challenging for many apps that don’t have built-in version control. You can bypass this by exporting each entry to a Cloud service that has built-in version control or using Git (if you’re that kind of person).
  • Getting digital signature are hard: There is a lot of different expensive electronic lab notebook software available for purchase from companies like Perkin Elmer. They are quite expensive, almost always require an internet connection for use (which makes them useless in the field), and are primarily used by companies with many employees and have patent/FDA regulations that require all lab entries be electronically signed off by a supervisor and stored on a secure server. These systems are good for large companies who have hundreds of people working on projects and need to coordinate ordering large quantities of chemicals, etc. I don’t think this is necessary for a relatively small, academic lab like ours. It’s possible that you can get one using Adobe Acrobat, but I’m not sure how this works.
  • Federal reporting requirements: The FDA outlines specific lab notebook requirements (21 CFR Section 11) which are required for using lab notebooks as evidence in a patent application for “first-to-discover,” which is the new standard for US patents (this new rule is what caused the recent CRISPR patent battle). I believe that some Microsoft 365 accounts can be configured to be 21 CFR Section 11 compliant, but the entire lab needs special (and expensive) licenses. If you have to be 21 CFR Section 11 compliant, I’d recommend using a corporate lab notebook software.

How do I organize my ELN?

  1. Each lab notebook entry: I write the protocol for the experiment in Microsoft Word (or sometimes directly into OneNote). Then as the experiment progresses, I write in the app (just like how you would with a paper lab notebook) with pictures and notes about the experiment. In OneNote, you can also insert PDFs, Microsoft Word, PowerPoint, and Excel documents.

ProtocolFigure 2: Example lab notebook entry with photos and annotations

  1. Within the app: Within the app (I use Microsoft OneNote), I organize projects into notebooks (NXX), then projects (NXX-PXX), then specific experiments (NXX-PXX-EXX) (Figure 1).

Example Notebook StructureFigure 3: Electronic lab notebook organization within an app (Microsoft OneNote)

  1. On my computer/cloud: I export PDFs of each lab notebook page and store them in a folder on my Box Sync folder on my computer, which automatically backs up to the cloud using version control.

File storage systemFigure 4: File organization on my computer

Concluding thoughts:

Based on my experiences having used a semi-electronic lab notebook for the past three years, a tablet-based electronic lab notebook is my preferred option. However, although ELNs have lots of benefits, I don’t think an ELN is for everyone so I certainly wouldn’t recommend requiring everyone to use one.

 

Additional References:

  1. Guerrero, S. et al. A quick guide for using Microsoft OneNote as an electronic laboratory notebook. PLOS Computational Biology 15, e1006918 (2019).
  2. Guerrero, S. et al. Analysis and Implementation of an Electronic Laboratory Notebook in a Biomedical Research Institute. PLOS ONE 11, e0160428 (2016).
  3. Kanza, S. et al. Electronic lab notebooks: can they replace paper? Journal of Cheminformatics 9, 31 (2017).

 

Exploring Careers Outside of Academia

by Shengpei Wang

Determining which career you want to pursue can be a daunting task. In addition to loving research, part of my motivation for getting a PhD was to kick that decision down the road a bit. However, I need to find the path that’s right for me eventually, and it’s better to start early. Whether you have interests in staying in or leaving academia, I want to urge you to start to consider your future and take action, now.

There are many career options after getting a PhD. The most traditional route is to pursue a tenure track position at a R1 University. However, the supply of qualified PhDs greatly outnumbers available tenure track positions, especially in Biology. Just think about how many students your lab will train throughout your advisors’ career, that number minus one is the oversupply your lab produces (see this blog https://lucklab.ucdavis.edu/blog/2018/7/4/job-market for more involved calculations). Most of us will develop careers other than becoming a tenure track faculty. Within academia, there are roles such as non-tenured teaching positions, university administrators, student services, lab managers, staff scientists, etc. There are even more opportunities outside of academia, including non-academic research scientists, medical science liaison, science writers, management consultants, etc. I am not trying to persuade you to stay or to leave academia but to point out that only a very small number of us will reach the goal that most of us set out to achieve. Making a career choice may not be easy, but you will be better off if you start early.

I want to first share with you some resources I found especially helpful to start the journey. They are useful for developing careers both inside and outside of academia. If you have any interests in careers outside of academia, you will need advice from sources other than your academic mentors. Most of our mentors have only been through the tenure track faculty career path and have limited experience with other options. Additionally, the job market is constantly shifting, and we need to be up to date if we want to enter the competition.

  1. Talk to people. Talk to your advisors and mentors, family and friends, your career services, or others with careers you find interesting. They are there for you, so put them to work.  This was hard for me personally, but I received many insights that uniquely fit my needs. The scariest part was emailing people I didn’t know, but the advice I received was invaluable. If you are intimidated and want to do your homework, the following resources may help.
  2. Blogs from Nature Careers (https://www.nature.com/careers) and Science Careers (http://www.sciencemag.org/careers). We are their target audience, and they are there to help us develop a fulfilling career. The diverse perspectives they offer are useful regardless of whether you want to stay in academia.
  3. My IDP (http://myidp.sciencecareers.org/). This tool was developed to help PhDs and postdocs for career exploration and development, so again we are the target audience. It can help you set and track goals, in addition to all the tools we discussed in last month’s post. My IDP can also offer you career suggestions based on your interests and preferences.
  4. Medium (https://medium.com/). I am not sure how this blogging site appeared on my radar, but it has been useful. A lot of people in “the industry” write about career advice and trends there. It’s also great for stalking people with interesting careers.
  5. Job boards. This might be the most important place to look if you are finishing and need a job. Developing a career is bigger than getting a job, but it doesn’t hurt to know what’s currently on the market. Here are a few online job boards I have ventured: Ecolog, EvoDir, Nature Careers, Science Careers, USAjobs.gov, LinkedIn, Indeed.com, and Glassdoor.com.

How I started my journey:

My attitude towards my career has changed profoundly through the four and half years of my PhD training. When I started, I was not concerned about careers and thought that I would “figure it out”. I believed that “There would be more time”.  As it went on, the ideas I had about my future did not become clearer as I became more experienced with research. It was only after I started exploring career options more explicitly, I started to realize the vast world of opportunities both inside and outside of academia. This was my first lesson; you have to take action to figure it out.

My experience was not unique; many people I know didn’t start their MS or PhD training with a set idea of what’s next. Most of us were willing to pursue the career path of a tenure track faculty, but a good chunk of us decided not to towards the end of our trainings. These decisions take time to develop and everyone has a different reason. For me, I like research and analyses, but I don’t want to spend over half of my time writing and teaching forever. It took me three years to admit that, and only after I started exploring different career options. Regardless of what you are passionate about, it doesn’t hurt to start thinking about your careers now.

What really attracted me to careers outside of academia was the diversity of things people do. There are also abundant opportunities to learn new things, to move, and have new experiences. One thing I didn’t quite expect from my exploration was that no one mentioned any regrets leaving academia. Many people told me that it’s much less stressful and more fulfilling because you can help people more directly. There are different challenges, but you are less bound to any one situation. I believe that getting a PhD should open up a world of opportunities. This might mean embracing a world outside the ivory tower.

We’d love to hear from you about your career journeys! Please post in the comments below.

Some other resources that inspired this post:

Academia Is the Alternative Career Path (https://medium.com/@drmdhumphries/academia-is-the-alternative-career-path-106c89fc3412)

Rise of the Science Ph.D. Dropout (https://www.insidehighered.com/news/2018/12/11/new-study-says-scientists-are-leaving-academic-work-unprecedented-rates)

 

Work smarter, not harder: Resources for time management in graduate school

by Callie Chappell 

I’m a little obsessed with work efficiency. I track all of my time (details below), take notes on an iPad, and have a calendar that most people would shudder at. Throughout my life, people know me as the person to help “get s**t done.” However, I have a dirty secret: most of the time, I keep a 40-hour work week. And I don’t just keep a 40-hour work week, but I also regularly take long weekends, go on vacation, and spend a little too much time cleaning my apartment…I mean procrastinating.

This obsession with work efficiency was motivated by a sly comment I overheard while in high school. Working the check-in table at parent-teacher conferences, I overheard a classmate’s mother point at me and whisper, “that Callie, she’s a hard worker, but she’s not very smart.” Although it took some time for my self-confidence to recover, it motivated me to show her—and the world—that I could work harder and smarter.

In this post, I want to share some of the resources I use to maximize my work efficiency and I’d love to hear your strategies as well.

Calendars:

As an undergraduate, I used a Passion Planner to outline my time management for each day. I loved the Passion Planner because I could visually block off my time and included a wide range of times. Additionally, Passion Planner includes a variety of personal and professional goal-setting tools, both over the long and short-term. Although I no longer use the Passion Planner (I switched to a completely digital system) I still utilize these goal-setting strategies and I know several graduate students who love using the Passion Planner.

Other similar products include the Bullet Journal and the hipster’s (do people even talk about hipsters anymore?) favorite, the Moleskine.

Now, I keep several digital calendars for different topics (lab, the official lab calendar, university events, social events, coordinating with undergraduates I supervise, classes, etc.) and since they are mixed Google calendars and Outlook calendars (for some reason, Stanford no longer uses Gmail, much to my extreme displeasure), I sync them all through iCal. I also send scheduled to-do items from Todoist into their own separate calendars, but I will talk more about Todoist below.

Project Management:

As graduate students, we balance several projects at once. Most projects have many moving parts, collaborators, and perhaps also undergraduate research assistants. Because I often have a bazillion things on my plate, it’s useful for me to break each project into chunks, assign myself a soft deadline for each chunk, and also outsource those chunks to collaborators and other researchers. Luckily, some companies have thought much more about efficient management than most researchers, and I took a leaf out of the business school book when designing my project management strategy.

I use a combination of Trello and Todoist. Both are digital apps that can be organized by projects and integrate due dates and check lists. Most importantly, they can be shared with collaborators that can edit checklists and projects in real time.

I use Trello to organize projects. Each research project (dissertation chapter/paper) gets its own “Board” in Trello, which I can share with other Trello users to collaborate on. Below is an example I was working on for a summer, primarily in collaboration with two exemplary undergraduate researchers in the lab. As you can see here, for each board, I can create “Cards” for each component in the project. In each card, I can include check-lists, due dates (with calendar integration), attach documents, and do many other functions (see below). I move cards that I’m working on into “working” and “done” piles. This project management strategy is also useful for working on a team and especially with working with undergraduates. I can track which components of projects undergraduates are working on in Trello as they move cards from “to-do”, to “working” and “done” piles, as well as individual items on the checklists. This is especially useful to help undergrads work autonomously. I also ask undergraduates to upload scanned copies of their lab notebook pages to corresponding Trello cards to keep up-to-date on their experiments, even if I don’t see them in the lab.

Trello 1.png

Figure 1: This is what the desktop Trello interface looks like on Mac (personal information redacted). The web interface looks similar. As you can see, we have various “cards” (each labelled with the notebook, project, and experiment number) in “stacks” of “to-do”, “doing”, “done”, and “no longer doing”. Each of the 5 members working on this project had access to edit this board and we communicate with Slack (which Trello interfaces with). Additionally, Trello syncs with our team calendar, which also helps use coordinate lab work and stay on the same page with due dates. Trello also apparently syncs with GitHub and BitBucket (the Atlassian GitHub equivalent – Trello is an Atlassian product), although we’re not currently using this feature.

Trello 2

Figure 2: Within each card, we can include a summary of each experiment, a to-do list for the experiment, and attach files such as lab notebook pages, analysis, and figures. We use a shared Google Drive as the repository for all files, but Trello is a nice central area to refer to the status and key findings for each experiment. Personal information has been redacted.

As a compliment to Trello, I also use Todoist, which is a mega to-do list app (as the name implies). I don’t know about you, but I find the satisfaction of checking an item off a to-do list one of life’s great pleasures. In Todoist (see below), you can make multiple to-do lists for different tasks (some of my categories include various projects I’m working on, lab deadlines, class deadlines, re-occurring meetings, etc.) and each task is assigned a deadline, so it only shows up on my daily to-do list on the day it is relevant. Todoist also syncs with Google Calendar and iCal, so my to-do list items show up on my calendar as well, so I can plan around big (and small) deadlines that aren’t a calendar event. Todoist also lets you rank the urgency of various tasks, lets you tag tasks into categories, and tracks your accomplishments over time, in case you are interested and make weekly charts of what you’ve completed. Not that I do that…Also, you can share to-do lists with collaborators and assign different tasks to different collaborators.

Todoist

Figure 3: This is what the Todoist interface looks like on Mac (personal information redacted). As you can see, you can create various projects, and within each project, assign various tasks with due dates. For any given day, you can see which tasks are assigned for that day and which project they belong to. 

Time Management:

As graduate students, we often have more work than hours in the day. For me, the constant pressure to always be doing more has been challenging to combat, and at some points, mentally debilitating. I’ve tried to address this by tracking my time and letting myself feel okay about stopping work at 40 hours. A wise former graduate student told me this trick, and I’ve found it helps me stay focused when working and feel okay about not working. Of course, sometimes I work much more than 40 hours and other times, take time off.

However, I keep track of my hours using toggl, an old-fashioned timer for the 21st century. You can create “projects” and track the time spent on various tasks on the desktop or web interface, as well as their sleek app (see below). Toggl also generates weekly, monthly, yearly, (or any time you want) reports of your work, as well as the tasks you’ve worked on and how much time you spent. You can also use toggl to track billable hours, if you’ve got a side hustle. I use their weekly and monthly report feature to reflect on how I am spending my time and make adjustments.

Toggl

Figure 4: This is what the toggl desktop interface (right) and toggl online summary report looks like. As you can see, you can assign each task to a project, as well as a tag (for experiments, I used tags for each individual experiment number that corresponds to my lab notebook so I know how long each experiment takes me). Online, I can track how much I worked per day, as well as what tasks I spent my time on. This is what my last week looked like.

However, despite capping my obligatory work week at 40 focused hours, I don’t want to compromise what I’m able to accomplish. One helpful tool for time management, especially when working on heavy focus tasks like reading or writing, is the Pomodoro technique. Our lab has weekly/bi-weekly 2-hour writing sessions where we use this method. Essentially, you work really hard for a set amount of time (such as 25 minutes), followed by a short break (such as 5 minutes). These sessions are timed and seem to help us feel more productive and focused.

Finally, I think it’s important to note when you are working. Everyone is productive at different times, and it’s important to be aware of when you are most productive, creative, or hungry and plan your time around your natural rhythms. For example, I am very good about analytical tasks that require a lot of focus in the mornings, intellectually useless in the afternoons (optimal for mechanical tasks!), and very creative at night. Therefore, I reserve the mornings for reading papers and working on analysis, doing lab work in the afternoon, and writing in the evening.

Goal setting:

Knowing how you’re spending your time is much less important than feeling empowered about what you’re spending your time doing. I attended a great workshop earlier this year at the infamous Stanford d.school addressing vision and goal setting in scientific research. I got two main things out of that workshop about goal setting. First, goals can be ambitious, but must be broken down into actionable chunks. Second, goals must be prioritized by importance and urgency. One way to do that is to use an Eisenhower Matrix: take all goals for a set amount of time (i.e. a week, and break down each item into importance and urgency items in order to decide what to tackle immediately, what to tackle later, and what to delegate. I make yearly, monthly, and weekly goals with this method and revisit the goals at the end of each period, as well as compare my goal list with how I spent my time with the toggl reports. The Passion Planner has great built-in tools for goal setting as well, which was why I loved using mine for so long. One feature I especially appreciated was making space for personal, as well as professional, goals each week.

Electronic Lab Notebooks:

Perhaps unsurprisingly, I used an electronic lab notebook (ELN). Although this is a topic for another blog post, I do want to briefly mention that I have found using an electronic lab notebook very helpful to replicate experiments, keep data organized, and collaborate. I use Microsoft OneNote (totally free!) on an iPad with an Apple Pencil and keep both sterile by putting the iPad into a gallon freezer bag and the Apple Pencil in a Ziplock sandwich bag, spraying both down with ethanol. Yes, the Apple Pencil works fine through two plastic bags. Another free (for academics) electronic lab notebook system many like is Benchling. Although not widely adopted by ecologists, Benchling is well organized and has great support for molecular biology.

Even if you choose not to use any of these free apps, I hope this blog post was helpful in terms of thinking about productivity and project management. Even though I’m not a Facebook, Google, or Apple employee, going to school in the heart of Silicon Valley has encouraged me to embrace the campy-ness of innovation in my lab and life.

 

Organizing outreach events in the biological sciences

By Sheela Turbek

A basic understanding of biological processes is necessary for informed decision-making on societal issues such as public health, food security, and conservation. However, despite scientific consensus on many biological topics, including the validity of evolutionary theory, the benefits of vaccination, and the contributions of human behavior to climate change, these ideas continue to be subject to widespread debate by the general public. The United States is particularly culpable of low levels of scientific literacy. A 2015 poll by the Pew Center, for example, revealed that only 62% of U.S. adults believe that humans and other living beings have evolved through time. A mere 33% of the surveyed adults conceded that these beings evolved as a result of natural processes. One must look no further than the results of this poll to recognize the major disconnect that often exists between scientific consensus and public opinions regarding scientific topics.

As graduate students in the biological sciences, we have a responsibility to close this gap between scientific consensus and public understanding by learning how to effectively communicate our findings in a manner that is accessible to the general public. Organizing outreach events is a great way to practice science communication skills and break down common misconceptions about biological ideas and the scientific process. These events can range from one-time activities that require a low level of commitment (e.g., organizing a public lecture on a scientific topic or visiting a school to discuss careers in the biological sciences) to lasting partnerships with local organizations in order to enhance scientific literacy.

Below are several ideas for outreach activities that would be feasible to organize as graduate students. However, feel free to get creative! The possible ways in which to engage the general public in scientific research are endless.

  • Partner with a local museum to organize a monthly or annual event aimed at increasing public understanding of biological concepts such as evolutionary theory
  • Organize a public lecture that targets non-traditional audiences or coordinate with an established program that connects scientists with the public in informal settings such as coffee shops, restaurants, and bars (e.g., Science Cafés and Pint of Science)
  • Organize a nature walk that introduces participants to the natural history of local flora and fauna
  • Incorporate a citizen science component into your research. Check out this website for a cool project that leverages citizen science to study the abundance and diversity of native bees and wasps in Colorado
  • Participate in 30-60 minute Q&A sessions about the life of a scientist with classrooms around the world through Skype a Scientist
  • Organize an interactive event for undergraduate students (particularly non-science majors) at your university to enhance public understanding of evolutionary principles
  • Work with local middle and high school teachers to develop science curriculum through the National Science Foundation’s Research Experience for Teachers (RET) program
  • Hold a training workshop for public middle and high school teachers that provides innovative ways to teach topics such as climate change or evolutionary theory in the classroom

Depending on the type of outreach event that you are interested in planning, you may require financial support. Several funding sources exist to promote educational outreach activities in ecology and evolutionary biology:

In addition, some universities offer internal funding for outreach initiatives aimed at making research more accessible to the general public and strengthening relationships with the community.

In the post-truth era in which we arguably now live, it is more important then ever to convince the public that our research matters and that continued support for the biological sciences is a worthwhile endeavor. Organizing outreach events to increase scientific literacy and share recent scientific findings with the broader community will not only heighten public awareness of the importance of ongoing research, potentially improving our ability to secure funding in the future, but also increase diversity in the biological sciences by making science more accessible to audiences that have traditionally been excluded from the scientific process. Finally, participating in outreach initiatives will allow you to practice communicating the impact and relevance of your work clearly and concisely to diverse audiences, thereby making you a more effective writer, educator, and scientist.

 

How to get a Postdoc: It’s never too early to start thinking about it.

By Abigail Pastore

Assuming you intend to incorporate research in your future career, you will probably need to get a postdoc position.  Most academic positions expect job candidates to have at least a year as a postdoc to provide evidence of their skills as a researcher beyond their dissertation.  Possible career paths facilitated by a postdoc include professor positions at R1 institutions, small liberal arts colleges (SLACs), primarily undergraduate institutions (PUIs), and conducting research for government, non-profit or industry jobs.  

Regardless of your career plans, there are a few different strategies that an individual can mix and match to find the postdoc position that is correct for them.

A continuum of certainty

Graduating students generally fall on a continuum of how certain they are about what they want to research at the next step.  Some individuals know exactly what questions they want to address and how, and just need to find the support to do the work.  Other students may feel that a wider range of research topics would be acceptable. Depending on where a student falls on this continuum could dictate the path leading to their ideal job.

Here I outline three strategies for finding postdocs depending on the student’s degree of certainty regarding research topics.  These strategies are not mutually exclusive and can be mixed and matched.

On one side on the continuum: ‘I know exactly what project I want to do next.’

If this is the case, then write up that proposal ASAP.  Seriously, go write a rough draft right now.  There are several grants that you could apply for to take funding into your own hands, and the sooner you start preparing these grant applications the better.  Plus, it never hurts to clarify your ideas with the process of writing!  The added benefit of writing your proposal now is that it will be easier to talk to EVERYONE you meet about it.  This will help you get lots of feedback and aid in networking to find someone who might sponsor your research.  If you already have someone in mind to work with on the project, email them right away and talk to them about prospects of working together.  Send them a decent draft of your research proposal to show them how you are committed.

On the other side of the continuum: ‘I would be happy working on any number of different projects.’

If you’d be happy working on many different projects and are a bit crunched for time, getting on relevant listservs will give you an idea of what jobs are available.  Popular listservs are ECOLOG and EVOLDIR.  They are fun to watch in and of themselves, but you may want to filter emails using the word ‘postdoc’ so you don’t go nuts from getting hundreds of additional emails a week.  As you see job ads go by, make a spreadsheet that helps you keep due dates and application requirements straight.  Start early and apply for as many jobs as you can stomach.  The advantage of starting before you are ready for a job is that the first version of your applications will not be the best, so work out those bugs before its crunch time. And who knows, the perfect job may be willing to wait for you.

Anywhere in the middle of the continuum: ‘I’m not totally certain what I want to research, but I’ve narrowed it down.’

If you have some project ideas or favorite faculty members in mind, you can go ahead and start contacting people about opportunities they might have.  Make a list of the people you’d like to work with and email them to ask if they are interested in having a postdoc.  Ask if you can write a proposal together.  Start very early if this is the route you want to take because you will need a bit of luck for things to work out.

Mix and match these three strategies to suit your individual needs.  Common factors: (1) Start early. (2) Talk to lots of people.  To that end, be visible in the community, give talks at conferences, participate in national societies, and take other opportunities that arise.  When you talk to as many people as possible it will help refine your ideas, and improve your odds in this numbers game.  Talk to other graduate students and postdocs- it’ll put you in touch with other labs, and postdocs often become faculty members with big startup salaries from which they could hire you as a postdoc.  Finally, be productive so that people trust that you will help them be productive.

General tips for applications and interviews:  Always be genuine and honest about your interests and abilities-you want a job that fits you well.  If you go somewhere under false pretenses, everyone loses.  Emphasize what you can bring to the table, not what you are hoping to gain.  Do your homework- show researchers that you know their work and are interested in them specifically.  Once you get that interview, remember: you need to find out if this is the right job for you!  You are not begging for a job, you are looking for the glass slipper that fits. Talk to all the people in the lab you are interested in to find out about the lab culture and what it is like to work with their PI.  Also ask lots of questions to determine if these are the people you want to be spending your work day with.  You will get a job you want, it might just take time (and publications).  Most importantly on this journey: don’t panic!

Also check out some more blogs on the subject!

 

Have you got additional advice for prospective postdocs? Questions not addressed here? Job search horror stories?  SHARE THEM IN THE COMMENTS BELOW☺

Bioinformatics skills – How to get them and not get scared

by: Samridhi Chaturvedi
If you are working in the field of Ecology and Evolution, it is important to build a skills toolbox which can come in handy to visualize, analyze and work through your data. These skills are a set of standard practices that you could start developing which make your work easy and smooth. Here are some skills which can constitute your toolbox:

1) Learn a language

 

 

If you are dealing with big data (ecology or evolution), you will eventually have to develop programming skills to help you manipulate, visualize and analyze your data. This can be quite overwhelming if you do not have prior programming experience. To start developing these skills, you generally have to learn a programming language. I feel there are several languages which are being used in the field at present and each of them have their pros and cons. There is Perl, which is older and is great when working with regular expressions (read more about regular expressions here). There is Python which is newer and is more intuitive. Then there is C/C++ which are compiling languages and using them involves a steeper learning curve. C/C++ are used extensively for theoretical/mathematical modelling and also for developing packages. These are all important skills to build but it is important to recognize that you can spend a lot of time learning and implementing these languages.

I say choose one language between perl and python to start learning the ropes of programming. There are some really helpful interactive learning spaces for both these languages.

Here are the ones I have found helpful:

  • Jupyter (http://jupyter.org/). This is an IDE and interactive website which helps you practice Python interactively.
  • Learn perl (http://www.learn-perl.org/). This is my goto online IDE for learning and testing my perl code.
  • Regex (https://regexr.com/). If you are working on genomic data and use Regular Expressions in scripts to detect specific sample IDs, lines etc to modify your data or calculate number of mapped and unmapped reads in fasta files (just an example), this tool really helps you learn how to write regular expressions for your data. What more, you can actually paste a piece of your text and write a regex to detect specific matches.

The other language widely used for statistical analysis and data visualization is R (free) or MATLAB (paid). I use R extensively so here are my pointers for learning R:

The more you practice the more you learn. The earlier you can start learning R, the better!! This will save you a lot of time in dealing with your data. There are many different only resources for getting started in R, but here is one basic one: http://tryr.codeschool.com

Even after working with R for a long time now, I still find myself Googling for specific commands and options. Here are the three most trustworthy sites which always have an answer to my questions:

These websites also have defined sections which walk you through simple R commands. For example, the sections on plots tell you how to make different kinds of plots, how to modify them and customize them to your data.

Beyond all of these resources, a simple google search can always help you and StackOverflow always has some amazing solutions to problems. It was only in my second year that I realized a PhD in Evolutionary Genomics requires some kick-ass googling skills!

 

2) Choose your favorite script editor/text editor

 

While you learn programming, it is ideal to select a script/text editor and to fall in love with it! I say this because switching between various script editors can be confusing and time consuming.Script/text editors help you edit your code and keep everything organized. Here are some of my suggestions:

  • VIM/VI (http://www.openvim.com/). If you are a programming nerd and like to work on a Terminal, this might be a good choice. However, recognize that it requires some time to learn vim and it is not unusual to find yourself trapped in the editor and even wonder how to exit the editor! Having said that, once you get a hang of it, you really can do a lot with just one editor.
  • Gedit. This comes preinstalled with linux/ubuntu systems and is very very easy to learn. Probably the simplest text editor to start working with and to use everyday.
  • EMACS (http://emacs.sexy/). Similar to VIM and requires some learning but again really powerful.
  • ATOM/SUBLIME?NOTEPAD++ = Editors which are more user friendly and are almost like MS Word.

All these are great tools, but you can choose one which works best with your work environment. I personally use VIM because I work on a TERMINAL and usually work on a remote computer cluster.

 

3) Managing data – scripts, sequences

 

When it comes to managing your data and mostly your analyses, I find it useful to keep detailed notes for my workflow for every project I am working on. I use my lab’s google notes website to do this but you can use alternative notes taking tools to do this (Endnote, Google Drive). The main things which each project page consists of are : a) my folder and file details where I literally write out each folder and details of each of the file in the folder. It is also good to keep a “readme” file in the folder to help you remember what each file in the folder is about, b) I write out step by step notes of each analysis and describe the scripts I used for analysis. If there are some specific options used through command line tools, I describe each of these options, and c) A list of analyses I hope to do for the project in the future.

Believe me, you can forget your data locations within a week/month if you step away from the computer. I store all my scripts remotely on the institution computer clusters. Another way to archive important scripts which will be reused or modified in the future, is to submit them to GitHub (https://github.com/). This is also a good way to make your scripts public if you think this will help a broader audience in your field.

4) Latex

 

 

I learnt about LaTex after starting my PhD and I cannot emphasize the importance of the tool enough. It is very, very helpful in organizing your text (read manuscripts), saves time adjusting sizes of images and tables by clicking multiple times and definitely is cleaner. LaTex basically gives you the power to design and manipulate your text the way you like it and have the control on it. This can be amazing and definitely saves you a ton of time adjusting page limits. I highly recommend learning to use LaTex. I even reuse most of my manuscript outlines and then I have to make minimal adjustments for different texts.

You can basically use any of the editors above to write LaTex documents (this is also a language).  But there are several desktop versions for Linux, Mac, Windows which are user friendly and help you visualize your PDFs from the source Tex document. The best of them all is Overleaf (https://www.overleaf.com/). This is like Google Doc but for LaTex. It is online, autosaves and has many, many templates for various journals and for various documents (CV, Thesis etc.). In addition, it is easy to collaborate on overleaf as many people can work and edit the document at the same time. You can also see the PDF in real time which changes as you write you LaTex code (Super cool!!).

 

5) Important resources

 

Beyond these tips, here are some important resources and articles which helped me learn these skills better: