About a week ago we the grad students in our lab virtually hosted a panel* of a few* of the lab alumni who after their postdocs with us are now professors. I get a lot of messaging (from the University, surprisingly, and from student groups and of course from twitter) against academia and toward industry—about the transition from academia to industry, about destigmatizing “leaving” academia, about the flaws in the academic system, about low pay in academia, about how miserable everyone is, etc.—, I think to try to balance the pressure to follow an academic career path after a PhD but somehow at least the pieces that reach me have tipped in the other direction, to the extent that I don’t think I receive much pro-academia or even happy-academia messaging at all. I really enjoyed this panel. Everyone seemed happy. After the conversations I’m used to it was like stepping out of a loud smoke-filled bar into an open hillside with cows grazing. I want to share it with you, in case you see a potential future for yourself in academia, like I do, because I was reassured to know that that hopeful future can stay hopeful and light and that there are people in my field who love their jobs.
We asked about what we can do in grad school to be better prepared for a career in academia. Along the same lines, we also asked what the most important and underrated skill to focus on building in a postdoc is:
You learn A LOT as a grad student.
The fellowships you apply for are great practice in writing proposals. You get better at it; you learn how to use feedback.
Learn all of the stuff that happens behind the scenes—what gets funded, what doesn’t. Learn how money is spent.
Network and find connections.
Write papers well.
Learn the nitty-gritty of your science, but also the big picture of your science.
As a PI, managing people is new—being a cheerleader for the team is critical, and it’s something you can work on in a postdoc.
On applying to postdocs and finding a good lab for your postdoc:
When looking for a postdoc, look for the specific things YOU need to grow in.
Meet with people at conferences.
Meet others in the lab to get the vibe of the lab you’re interested in.
Tell people DIRECTLY and candidly that you are applying for postdocs. BE DIRECT.
Your postdoc is your last opportunity to do something totally different from what you’ve been doing.
Getting a postdoc is all about personal connections, or it can be.
For your postdoc, find a lab that gives autonomy—enough autonomy to learn how to run a research project, with training wheels. You don’t want a lab where postdocs are treated like “super grad students.”
A larger lab can be more autonomous. On the other hand, there can be less opportunity for direct mentorship from the PI in a large lab.
Get a fellowship; then you can go wherever you want.
On applying for professorship jobs:
The job committee wants to know what you’re doing that will make science better for their university in the future.
The job committee also wants to know you can bring in grants.
Talk with faculty in the department you’re applying to.
Your applications are a crapshoot—the commitee uses imperfect heuristics to get the job done. There’s a lot behind the scenes you can’t see from the job posting.
Don’t make enemies—a single advocate can push your application forward, while a single nemesis can sink you.
Apply to a lot of positions.
You have an edge if you have interesting science, connections, and a well-written proposal.
Pay attention to teaching requirements—at a non-R1 university, you will actually be teaching, whereas in other universities you might have very few teaching responsibilities. Our panelists had a wide range of teaching requirements, from a lot to almost none.
Look for the kind of position YOU WANT.
On moving (or not moving) for jobs in academia:
There is a bias against people who don’t want to move or are attached to a particular area.
On the other hand, passion to be in a certain location can also be an advantage, and a big one, because it also shows you are more likely to take the position. If you’re targeted in your search, your commitment comes through.
Interviewers might legally not be allowed to ask about your partner or your personal life, depending on the state. Tell them up front about your partner, their job needs, and any other parts of your personal life that affect your job search and your interest in and needs within this particular job.
On the job of being a PI:
You learn quickly as a PI that even though you’re the same person you always were, everything you say carries more weight than it did before you got the Professor title.
Think about and try to learn whether or not you will actually like the job of being a PI. The actual job involves a lot of management and a lot of writing.
Once you become a professor, there is no one you report to regarding what you are doing as long as you can get money.
There is room to make the job what you want it to be, but even small labs come with a lot of work; making even a small team run is really hard.
One of us asked when our panelists found “their thing”:
One of our panelists got hooked in undergrad (“some fire was lit inside of me in one class”), which as a person who also occasionally teaches made me very happy to hear.
In science, some things you find interesting, while some things FASCINATE you.
Going down rabbit holes* is a good fit for academia.
You have to be creative and excited about your ideas.
You should try to find an intersection between what people will give you money to study and what you are naturally interested in (—and that intersection might also be a role in industry).
On doing science:
Just do the science you really want to do; don’t think just about tenure.
Have a proven track record of fantastic research.
Look for opportunities as you encounter them.
Have a five-year goal that you slowly move towards, but keep all doors open. If getting to your five-year goal will be miserable or you’ll hate the process, that’s a red flag and a sign that your five-year goal should change. Your five-year goal needs to be fun, exciting, and interesting along the way.
General advice:
When you need to get in touch with a professor, email them multiple times—again if they don’t respond.
At every point in your academic career, your life keeps going. Don’t put it on hold—live your life.
“I liked what I was doing.”—enjoy it. Don’t torture yourself. Your job should be a job you love.
* (I organized this panel, which was one of those things I was very very excited for then forgot I did until I appeared at the meeting thankfully on time and was surprised and delighted to discover that that thing I wanted to happen was, indeed, happening, and happening now, and I was doing it, and doing it now—and then it went great and it was really lovely.)
* (We have TONS of lab alumni who are now professors with labs of their own, but I like a panel of three people; any more than three feels like we wouldn’t really get to know anyone.)
This is my favorite window view at work. It is right by the coffee machine in the little kitchenette on the 6th floor of the Broad, where I work. When I am waiting for my coffee I like to stand by this window. The view is of a corner of the Broad Institute and one side of the Whitehead Institute. Every square in this large grid is a part of a lab; each little window contains miniature people like me whose days are spent in the lab and in front of the computer—in my view, just a two-dimensional glass square and sometimes the publications that ultimately flow out of it; to them, everything, and if they looked out their window they’d see me waiting for my coffee and I would be small.
This is my favorite window view at home. We live in Peabody, which is not quite a suburb, more a small town in its own right but without the usual trappings of a small town, and far too far away to be an extension of Boston like Cambridge is. As I write this it’s raining, and foggy, and dark—the start of spring. Cars bring up rain from the street and their headlights illuminate it and the lights and the chimneys and the treetops are outlined in the bright night sky, and you can just see the lights on our fence. I grew up in a neighborhood without fences, low to the ground; now I live and I work exclusively in tall places, surrounded always by the little lights of other people’s lives.
In 2020, right before the start of the pandemic, I bought myself tickets to see Carmen at the Boston Ballet as a late birthday present. Carmen was postponed to August, then canceled, and now in 2022 I have transferred my tickets finally to see a ballet set to the Rolling Stones as a late birthday present.
Ballet has a magical effect. The last time I went to the ballet I saw Robbins. I was just about to start my PhD. On the way home on the train platform waiting for the Red Line, looking over the tracks at the other platform, everything seemed magical, timed. For a few hours I saw intention in everyone’s movements and postures and I felt a beautiful connection to the train schedule and to the city and everywhere I looked I saw mathematics and art. I felt myself a part of a giant clock, ticking and ticking and me so small in it. And tonight looking out at the windows and the fog I feel a part of a giant clock, ticking and ticking and me so small in it.
Possibly the coolest thing that’s happened to me, definitely the coolest thing that’s happened to me professionally, is getting to be a part of a project that not only got to be in Cell, but also got to be on the cover of Cell. In this blog post, I want to tell you about the process that created that cover, because it’s very different from anything else that has happened to me and I think it went extraordinarily well.
We worked with Thought Café, whom you might recognize because they also illustrate CrashCourse videos. We worked with Julia Nadeau, Head of Production, and with amazing illustrator Eric Diotte—check out Eric’s instagram and web site:
A few of us (Katie S., Gage, Bronwyn, Danny, Steve S., and I) from deep in the science of the project on the Broad side of the collaboration met and brainstormed as a group before engaging the illustration team. This was a very fun meeting—we all pitched ideas for the cover and riffed off each other. After our brainstorming session, I sent an initial email to the illustration team. In this initial email, I included:
I also included a summary of our group’s initial brainstorming—
Looking at existing Cell covers, we think we’re going to want to go for something more abstract, with mostly metaphorical connection to the work and with some elements added in literally.
(Can you tell I love Escher?)
The one thing I did not include but should have included is examples of existing Cell covers that we liked. (Julia asked for links to existing Cell covers and we provided them in a follow-up email.)
Initial Sketches
Because we had brainstormed ahead of time, Eric already had sketches of the four most promising of our ideas ready for our initial meeting.
We talked through each of the four:
In A, a dandelion flower has SARS-CoV-2 virions in place of the seeds. Its seeds, the SARS-CoV-2 virions, blow off the flower and into the air; in the background are rolling hills of many, many dandelion flowers.
In B, a tree has many dense branches (like a phylogenetic tree of an outbreak) and roots made of genetic material, with SARS-CoV-2 virions growing like flowers on its branches and appearing in the air around it.
In C, a wave represents the different “waves” of COVID, SARS-CoV-2 virions appearing in the foam.
In D, colorful wildflowers shaped like SARS-CoV-2 virions represents the many introductions of Delta into the outbreak; in the background are fields of identical flowers showing that only one plant had taken over, one Delta introduction accounting for most of the outbreak.
Eric modified the dandelions live during our meeting, confining them to a bubble to convey that the Ptown outbreak was successfully contained.
At this stage the dandelions were my personal favorite because I love dandelions as a metaphor for pretty much anything, but the dandelions were getting complicated in their bubble and they didn’t neatly fit the actual messages we wanted to convey. We couldn’t decide on a favorite as a group, so we polled the covid side of the lab over slack to choose between the two top contenders, Hokusai and the dandelions. Hokusai was of course a very clear winner.
Revision and Final Version
Having chosen our overall vision of Hokusai’s Delta wave, we then went through a series of (very) fast revisions with Eric and Julia. Eric revised, Julia sent us the revisions, we discussed internally and suggested, Eric revised, and so on. This was a very collaborative and iterative process: seeing the image converge in the direction of its final form made that direction much clearer, and in almost all cases, we didn’t know what we wanted until we saw something almost but not quite there. The final, polished version looks like this:
I’m very proud of this image. Eric did an extraordinary job, and every detail is something special to us. Here is the write-up I sent Cell describing each of the details:
This cover is a reference to Hokusai’s The Great Wave off Kanagawa—in this case illustrating instead the SARS-CoV-2 Delta wave in Provincetown, Massachusetts. In “Transmission from vaccinated individuals in a large SARS-CoV-2 Delta variant outbreak,” we use genomic sequencing to learn from the first wave of the Delta variant in Massachusetts, which resulted in a large outbreak in the coastal tourist town of Provincetown. The proposed cover image shows waves containing SARS-CoV-2 virions crashing into a lighthouse. The lighthouse shines a light at the waves, illuminating the single-stranded RNA genomes in the SARS-CoV-2 virions. In this illustration, the waves represent waves of the Delta variant, while the lighthouse represents Provincetown, the site of the outbreak we studied. The light emanating from the lighthouse represents genomic sequencing. The wave that is illuminated, or sequenced, is the first wave approaching Provincetown; it represents the Provincetown outbreak, which was the first wave of Delta in Massachusetts. The Provincetown outbreak was not the largest wave of Delta in Massachusetts, and so the illuminated wave in the illustration is similarly closely followed by another, larger wave. The water to the right of the waves is calm, to signify that Provincetown had very few COVID-19 cases before the outbreak. The lighthouse itself recreates the distinct and consistent coloration and silhouette of the real lighthouses in Provincetown.
The characters in question live in my twitter thread summarizing our study on the July COVID-19 outbreak in Provincetown, Massachusetts—then a preprint, now out in printon the cover of Cell. As I write this sentence, the first tweet of the thread has been viewed over 100,000 times, most of those views having happened within days of the tweet—which means that more than twice the population of my hometown saw at least a summary of our main findings at the moment they had the greatest potential for public health impact. I am quite delighted that the research we all poured our minds and hearts and summer and autumn into was seen by so many people so quickly. I am very impressed by how fast it spread and to whom.
Tweeting about science isn’t something I thought I was good at (and this was my first time doing it), but since it went so well I want to share with you what I’ve learned—for a long time as a consumer and now apparently as a creator. Here is my guide to writing a good twitter thread (tweetorial or tweetstorm, though I’m not a fan of either word) about your research.
Step 0: Before You Tweet
Before you start drafting your tweets, think about who your audience is and what you want your audience to take away from your work:
What are your key scientific findings?
How do you hope your key scientific findings will contribute to people’s everyday lives, immediately or someday?
What action do you want to inspire? Are you hoping that people will alter their behavior? Are you hoping that people will use your tool? Are you hoping that people will build on something you’ve started?
As you wrote the above, whom did you think of? Who are the people who are positioned to use your work immediately? Who are the other people who might also be interested in knowing about it? Who else might stumble on it?
Do you have strong emotions about your work? Do you feel delighted? surprised? grateful? horrified? Is there a particular emotion you want your audience to feel? Are you hoping to delight? to surprise? to horrify? How strong is your own emotion? Does it contribute to your message or does it detract from your message?
In what ways can your work be misinterpreted, misunderstood, or misused, unintentionally or maliciously? Can your work be used to fuel misinformation? Can your work be used to fuel hatred? What content did you personally find helpful in understanding how your work fits into a compassionate, good world? What content might help correct possible misinterpretions of your work?
Step 1: The First Tweet
The first tweet in your thread is the most important tweet of your thread. Most people will not click your link to read your paper and most people will not click your first tweet to read the full thread. For many people, this first tweet is all they will see of your work. It should communicate enough of your main findings and your call to action that not seeing the rest is more or less okay.
To maximize the chance that someone scrolling will read and understand it, your first tweet, more than any of the other tweets in the thread, needs to be short, be easy to understand, and not look like a block of text. Where possible, I recommend using bulleted lists and breaking up your text with plenty of vertical whitespace.
Your first tweet should include a link to the paper (though some people save it for late in the thread, as a sort of reward). If you don’t like the preview that appears when you paste in the URL, you can attach an image. I attached two images: one with the title and one with the abstract. Maybe you have a very pretty image, or a graphic that nicely summarizes your main findings—those would be nice to attach instead. We did not have a graphical abstract yet when I posted this thread, but if I were posting it today I would attach our graphical abstract instead of the images I did attach.
Your first tweet should have some indication that there is a thread attached to it. That indication can be the thread emoji (🧵) or the word thread, perhaps with an arrow (⬇), or it can be a a 1/, or it can be something else.
The first tweet also needs to do the important work of appearing in search results when people look up keywords. Try searching terms related to your work. Look at what results appear on twitter, how many results appear, what kinds of discussions are happening around those terms, and if those discussions involve the audience you are hoping will see your work. In my case, I knew that my twitter thread needed to contain the following keywords:
COVID-19
SARS-CoV-2
Provincetown
Ptown
outbreak
Delta
vaccinated
vaxxed
vaccine
public health
symptoms
(I don’t see any reason to use hashtags for these keywords—the terms appear in search results regardless of whether or not they have a hashtag in front of them, and having that many hashtags just seems a bit alarming. But I could be wrong.)
These 11 words account for almost a third of the 35 total words of the tweet. I made sacrifices to ensure that they all appeared. (Vaccinated, for example, is much longer than vaxxed, and Provincetown is much longer than Ptown—but they each produce their own search results and I wanted our paper to appear in all of them.)
If you would like and if it comes naturally, you can also (or alternatively) include in your first tweet some kind of a hook—a funny joke, a cliffhanger, an unanswered question, or content that elicits an emotional response. With a hook people will be more likely to click to read the details, but they are also less likely to walk away understanding your work if they don’t click. If the thing that is important to you is that as many people as possible walk away with some understanding of your work, you probably want to summarize your work in the first tweet. If you would like to connect more deeply with a smaller number of people, rather than shallowly with a large number of people, it might be better to use a hook. (I of course did not do that.)
Finally, I think it is important to include yourself in the work. The science is done by people and people like other people. I start the first tweet with Our and many of my other tweets in the thread start with We. I am a person who likes exclamation marks so I include exclamation marks—because exclamation marks best capture how I feel about this paper.
Things to Know
Here are seven general principles to keep in mind as you draft your twitter thread.
I recommend you draft your tweets in Google Docs or similar, and that you get feedback from your co-authors and revise at least once before posting. This thread took me three days with feedback from multiple co-authors: Katie, Bronwyn, Gage, and Pardis all helped me revise this thread and made it much better. (In its original form, it didn’t even have capital letters.)
Each tweet should be its own complete thought. If a person retweets one tweet from your thread and not any of the others, its message should be clear. It should not be possible to take any individual tweet out of context to mean something you did not intend.
Where possible, and especially when making important points, make your text easier to digest by breaking it into bullet points or breaking it up with vertical whitespace.
If you include a url in your tweet, your tweet will have a nice link preview. If you attach any images to your tweet, the link preview will not appear. The link preview in the final, posted tweet will look the same as it looks in the draft tweet before you post.
If you end your tweet in a url (if the url is the very, very last thing in your tweet) and you have not attached any images, the url itself will not appear in the tweet when it is posted (but the link preview will).
Most people do not click on images. You should size your images so that the preview that people see on twitter looks the same as the image itself. If you are attaching one image, it should be 1500 pixels wide and 850 pixels tall (or scaled with that same aspect ratio). If you are attaching more than one image, all of your images should be square. The final cropping of the images does not always match the preview of your tweet draft, nor is it consistent between devices. If it is important that people see the entire image, including the edges, add some white space all around your image so that the content of the image will still be visible even the edges are slightly cropped. (If you do not have image editing software, you can download and use GIMP for free.) I do not recommend attaching more than two images—the previews will be too small to see without clicking, and most people will not click.
Create a secret fake twitter account to test out your tweets before posting them for real. Delete your test tweets immediately. Do test post the actual images you intend to post to make sure they appear as you expect them to appear and are cropped as you expect them to be cropped. Do not link to your work or post any of the actual text you intend to post—not even for a moment. Other than images, replace your actual text with dummy text and your actual urls with dummy urls when you test post. You can also use this account to draft your actual tweets (without posting them) to make sure they fit within the character limit—don’t rely on other applications to count characters; they all seem to count in their own ways.
Step 2: Context, Background, Collaborations
This part is easy. I initially had this tweet closer to the end, but my co-authors encouraged me to move it to the front and I think it is much better here. We start off by acknowledging the organizations involved in this study, because the list was huge. If it were a much smaller study, I might start off by acknowledging the individual authors. It is also helpful to start off with some context—has this work been peer reviewed? Does this work build on previous work? Does this work build on anything familiar to the audience?
If someone has clicked your first tweet to read the thread, they are already in and willing to skim. Your second tweet does not have to be very exciting.
You might notice that while this tweet includes an attractive preview of the link, it does not include the actual url. That is because the url is pasted after the 2/. Because the url is the very last thing in the tweet and there is no image attached to the tweet, the actual url does not appear.
Step 3: Paper Summary
The paper summary will likely be the bulk of your thread. As much as possible, each tweet should include one complete and clear idea and be retweetable on its own. Where relevant, you should include figures from the paper. Try to add some emojis. You can also include links to previous work or work that you use or build on. I start many of these tweets with We.
The order in which ideas appear and the ways you present those ideas might not match their order or presentation in the paper. Your audience on twitter is almost definitely broader than the audience you wrote the paper for, and your language and narrative should adapt. Your focus should be on communicating the findings that are most relevant to this broader audience in a way that is understandable (and not condescending), with minimal jargon. In some cases you might want to delve into more detail, and that’s okay—tweets including jargon should be easy to skim and easy to grasp at least the purpose of without extensive background in your field and should not be necessary for understanding the overall story.
Step 4: Findings Summary
Your paper summary should end in a tweet summarizing the findings that are most relevant to your audience, or most actionable.
Step 5: Your Findings Out in the World
This is the hardest part.
This section is about the role you hope your work will play in the world, and it is a part of your efforts to shape that role. Here, you need to anticipate the ways in which your work could be used to misinform or hurt. You should address possible misinterpretations explicitly and head on. You should provide links to informative content people can engage with to address possible misinterpretations before they arise. Wherever possible, that content should be readable by people outside your field.
If you are less worried about misinterpretation or misuse of your work, you can instead or additionally use this space to explore the life you hope your work will live in the world—how you hope people will use or build on your work, or your own emotional response (if you have one you’d like to share) to your findings.
In either case, it is nice to end with a positive or hopeful feeling before your call to action, because hope is empowering.
Step 6: Key Takeaways/Calls to Action
Finally, at the very end, I have the final takeaways (the third time I am adding takeaways—but that is what this thread is). These takeaways do not relate to the content of the paper itself; instead, they are focused on how I hope the paper’s findings will be useful in the real world. I end by making explicit the calls to action I tried to imply in the first tweet and have been building toward throughout the thread.
Step 7: The End/Thank Yous
This part is fun (and easy). Thank your co-authors—the first and last authors first, if the full author list is very long, and the full author list listed out or in summary. If anyone is on twitter, tag them.
When you are ready to post, use twitter in a web browser on your computer (not the app on your phone) to prepare the thread in advance and then post the entire thread at the same time.
The time you post your thread is important. Don’t tweet when your target audience is having dinner or asleep. I think it’s probably best to time your thread for when your target audience is browsing twitter at work, but there are tons of more informed articles on timing of tweets that you can read instead of using my guesswork.
Finally, the number of people twitter shows your tweet to is determined not only by the number of likes and retweets your tweet gets, but also by the speed at which it gets them. Tell your colleagues and co-authors about your tweet immediately after you tweet it. Hopefully they will engage with it quickly and help it spread.
That’s all! I hope this guide helps your work reach its audience.
Every PhD student I talk with seems to have a different qualifying exam and a different qualifying exam experience. My department, Organismic and Evolutionary Biology at Harvard, has a very flexible and customizable quals, in line with the overall very flexible and customizable PhD program. Our qualifying exams usually happen in the second (G2) year, and consist of the following parts:
Three committee members, in addition to your advisor, one of them (not your advisor) Chair of the committee—all available at the same time, all in the same room (or zoom room). This part was trickier than I expected. The committee does not all have to be from the department, which helps. Connecting with professors I had already had excellent and productive interactions with helped. Asking for broad availability before sending out possible exam times helped. Booking the room well in advance helped (but did not end up being necessary in my case).
A written dissertation research proposal describing the work you plan to do during the rest of your PhD. I have been told that a lot of people end up deviating from the proposal. My proposal consisted entirely of projects I had already started and am committed to finishing. Even so, I am already doing work I could not have even imagined when I wrote my proposal, even though I wrote it something like seven months ago.
Three syllabi of courses you think you are qualified to teach, on varying topics and of varying levels. This is open ended and different from what I usually do and (I think) a lot of fun.
An oral exam, up to three hours long, consisting of two parts. First, you present and answer questions about your work. This part is (I think) a lot of fun. Then, the committee asks you questions, guided but not constrained by your syllabi, to find the depth (or shallowness) of your knowledge. This part is (I think) a lot harder and less fun.
I passed my quals in the spring, during my G3 year, on Monday, April 13th (like Friday the 13th but worse, because it’s a Monday). We’re required to pass sometime during the G3 year, so I just slipped under the radar. (I had also scheduled a back-up time a few weeks later in case I failed, but I did not end up needing it (!!!!).) April 13th was at the very end of the very start of the pandemic in the United States—my quals were virtual, over zoom. I had originally timed the exam to be right before my mom’s birthday and just after my dad’s and brother’s birthdays, and planned to go home to Pennsylvania right after, hopefully accomplished and with a weight off my shoulders and with full focus on family. Of course that did not happen, and I haven’t seen my family since spring break in March. Instead, I got back from my own birthday with my family over spring break in Florida to a lockdown, thinking it was temporary, and focused fully on quals prep.
I wrote my dissertation research proposal first, with three chapters covering my three in-progress projects (and one tiny transition chapter-ish section covering a relevant smaller completed project). These wound up being 1,970+510+2,245+2,628 = 7,353 words not including references and took a lot longer than I expected, largely because the writing required a lot of reading. I then compiled my syllabi. I got carried away and added far too many papers; I ended up (by request of my committee) sending another version with key papers highlighted. This sequence of events was bad, because it allowed early tasks to steal preparation time from later tasks; it was also good, because it allowed me to work on just one thing at a time, which (I think) I am better at than I am at multitasking. I give a lot of presentations at work, so my slide deck covering my research was largely already ready—which meant that in the weeks leading up to my exam I was able to focus almost entirely on reading the papers on my syllabus.
The exam itself was fine. I took it sitting on the floor between the couch and the coffee table in our living room, with my computer on the coffee table and cups and cups of water and coffee just offscreen on the floor next to me. I was very nervous leading up to the exam and didn’t sleep, which was a mistake. My presentation of my research was excellent, I think, though (not surprisingly) I was not able to get to everything I wanted to talk about and we exceeded the allotted time. The oral exam was a weaker point. I did not know the papers on my syllabus well enough to answer pointed questions about the material anywhere near as well as I would like, even though I had read every paper. I was very nervous, and made some embarrassingly dumb mistakes. In retrospect, for both the presentation and the syllabi, it would have been better to give myself less material—to go deeper into the material on the syllabi and to go less deep into my own work, at least for the presentation (not the written proposal).
When I entered the time crunch of the last few weeks left I put together a spreadsheet tracking my progress and timing of remaining work. (You update the count of papers you’ve read in the “done” columns and everything else fills in automatically.) I make a spreadsheet like this one every time I have some work to do that is both time pressured and easily quantified, which is rarely the case in grad school (except for quals prep) but was usually the case in undergrad. I started making these kinds of spreadsheets a few weeks into freshman year; my friend Mika taught me pretty much immediately after we both arrived on campus. It is motivating and reassuring and probably also a method of procrastinating. I’ve attached a version of my spreadsheet below, with Halloween set as the deadline, in case you would like to go nuts in the way I particularly like to go nuts and use it as a template or inspiration:
All in all I spent about exactly a month on full-time/overtime quals prep (pretty much quals prep and sleeping (probably not enough sleeping) and very little else) from the middle of March to the middle of April. I think it was good for me to constrain this chapter of the unending project of self-improvement and mind expansion—but if I could go back in time, I would have started compiling my syllabi and reading the papers on my syllabi during the first year of my PhD. Some of the texts on my syllabi are material I read and learned at the start of my PhD, but because I chose to also include a lot of material I wanted to know well but didn’t, there was a lot for me to read leading up to the exam and I am not satisfied with how well I absorbed some of it. Reading just one or two papers a week spread out over a year would have probably resulted in far better retention and learning, and would have allowed me to dedicate more time to getting everything I could from each paper. At the time I was intimidated by the process of putting together my syllabi, but I didn’t need to be. Organizing my favorites of the papers I was already reading into vague themes would have been a good enough start to later retrofit to the desired format.
I have been told that some students dedicate an entire semester to preparing for quals. I don’t think I would like to do that (and if the pandemic hadn’t paused my primary project I probably would have continued to try to multitask and continue working on research—which probably would have ended badly for my qualifying exam, though who knows), but focusing entirely on reading and writing for a stretch of time was very productive for me.
I learned a lot, both about my current projects while preparing my dissertation research proposal and about what kinds of work and tools are available to me in the field more broadly while preparing my syllabi. As I expected, having to write out the current and future directions of my current projects and having to read deeply enough to write every sentence with full truth and confidence forced me to gain a much, much better understanding of my own work and of the adjacent literature. What surprised me was that when I returned to my research after my qualifying exam, I returned with a lot of clarity of a sort I hadn’t had before. I knew where I was and where I was going in my current projects. I also found myself coming up with exciting new project ideas at a rate and of a quality (if I may say so myself) I hadn’t expected from myself at this stage of my career; quals definitely caused a leap in my ability to think like a scientist.
The document itself is also helpful as a compilation—I rather frequently refer back to my project proposals, my syllabi, and especially the references at the end of each project proposal. My strategy in undergrad and at the start of grad school was to do the science first, then write only when the science was done. Now I am trying something new and writing the paper as I go, and I find that so far it has made the work far more focused, informed, and efficient, and has give me a way to identify (and hopefully fix) problems and gaps in my work well before I try to build anything on them.
To sum up, here is my advice to anyone getting ready to prepare for their qualifying exam:
Start identifying and reading papers for the exam well in advance, even before you actually start officially preparing for the exam—a little at a time. Amortize as much as you can of the paper reading part of the work.
For every paper you read, put together a few sentences summarizing the key takeaways from the paper. Review your list of papers and summaries in the days leading up to the exam.
I found quals to be a great opportunity to learn things I did not know but wanted to know. You can fill your syllabi with material you know well, material you want to learn, or a mix. Consider what you want to get out of the experience and plan from there.
When scheduling the test, first ask your committee for broad swaths of time (weeks or months) that are or aren’t good and for any recurring commitments when they are always busy. Then send out a poll with specific test time options. I initially sent out a poll with five timeslots, and then when none of those worked I sent out another poll with ten additional timeslots. I had access to two of my four committee members’ calendars, which helped. I also found it helpful to allow committee members to give each time slot a score from 1 to 5 (5—extremely convenient, 3—I can make it work, 1—doesn’t work for me) rather than just saying yes/no/maybe, which made it easier to work with potential scheduling conflicts. Here is what my first scheduling form looked like:
Send out and ask your committee to reserve time for not one, but two three-hour timeslots for your exam, several weeks apart. This way, it won’t be as hard to reschedule your test on short notice if someone has an emergency or a conference or an unexpected vacation or speaking opportunity. And if you fail your test you have another one already lined up with time to prepare for it.
Don’t worry about fitting everything into your presentation. If you’re anything like me, you should make the presentation itself shorter than you think it should be—if you have more slides, then you can have plenty of hidden slides ready in case they come up in questions and discussion.
There will be questions you don’t know the answer to. Hopefully you are able to answer the shallower, easier questions before reaching something you do not know.
Have a nice, efficient stress-relief activity that doesn’t hook you into spending a lot of time on it. I almost never played video games until studying for my quals and for some reason occasionally playing Animal Crossing elevated rather than decreased my productivity, which is not something I would ever have expected.
Get plenty of sleep the nights leading up to the exam itself.
What follows is my three syllabi:
Evolutionary Perspectives on Human Disease, which is meant to be an introduction to the immune system as it appears throughout life (in humans, in animals more broadly, in plants, and in bacteria), a not very deep look at disease (infectious and otherwise) across life, and interactions between and co-evolution of infectious agents and their hosts, especially when the hosts are human (but also, briefly, when the hosts are bacteria), culminating in the evolution of the placenta.
Microbial Inhabitants and Infectious Agents of the Human Body, which is a sweeping view of past outbreaks and epidemics, culminating in the current COVID-19 pandemic, as well as short visit to some of the microbes that we more happily coexist with.
Introduction to Data Analysis Methods for Biological Inference, which covers everything from experimental design and statistical tests to multivariate models to GWAS and PCA to how sequencing works and metagenomic sequencing and genome assembly and phylogenetic trees, culminating in an exploration of how genomic sequencing can be used to track and react to infectious disease outbreaks (which is one of the things that I work on).
I tried to design the syllabi as if I were actually teaching these courses—and I would actually be very excited to teach them. They encompass, I think, most of what I know that is most relevant to my research, including a lot of things that I did not know until I put these syllabi together, found gaps in my knowledge that I was not satisfied with, and filled them. (I would also like to teach creative writing, but alas.)
You might notice that the readings include both actual papers and science journalism, in some cases science journalism about papers that are also included. (This actually came up as a question during my exam!) Including both was a very intentional choice: science journalism—specifically, Popular Science and then MIT Technology Review—was the first context in which I read about and got excited about research. I still get most of my science news from popular science journalism, especially in fields that I am curious about but am not doing research in. My hope, if I were actually teaching these courses, is that offering both research articles and popular science would
allow students who are just starting to learn about infectious disease to engage in the class, hopefully leading to increasing comfort and a transition to the primary literature as the semester goes on,
give students who are confused about or lost in a paper a way to get untangled (and teach students to seek out ways to get untangled), and
show students some of the many different ways of writing about science, and show them good (and possibly bad) examples of how to communicate both with their peers and with a broader audience.
You might also notice that I put these syllabi together in March—some of the work on COVID-19 is already out of date.
As an Amazon Associate I earn from qualifying purchases. The next few paragraphs of this blog post includes links with my Amazon referral code. If you click one and buy something, I get up to 4% of the price as commission. You don’t have to buy these books from Amazon—you can support local bookshops by buying books from Bookshop.org, or you can buy them used and donate them to or start or build a little lending library in your neighborhood, or you can not buy anything at all. You can also support me by buying merch of my art, by buying me a campground store decaf coffee, or by simply reading and enjoying. Thank you!
There are two books I reference a lot, because I like them a lot, that I highly recommend—
Regression and Other Stories (Analytical Methods for Social Research) by Andrew Gelman, Jennifer Hill, and Aki Vehtari:
We used Regression and Other Stories in OEB 201 (Introduction to experimental design and model building for ecologists and evolutionary biologists) with Professor Lizzie Wolkovich my first semester of my PhD. The class and the textbook were both extremely useful and enjoyable—definitely one of my most efficient and relevant learning experiences. Our version of the textbook was an earlier draft, spiral bound, years before it came out—we got to read it early and we got to contribute feedback that went into the final version, which I thought was a fun and special experience and a neat way to feel connected to a work that I greatly enjoyed reading. My copy is very, very dog-eared and highlighted and covered in notes and thoughts in every margin. I refer to it often whenever I need to do any modeling or think about experimental design.
Zoobiquity: The Astonishing Connection Between Human and Animal Health by Barbara Natterson-Horowitz and Kathryn Bowers:
Zoobiquity completely changed the way I think about the human experience and broadened my view of human disease—which was extremely valuable because human disease is the focus of my work. I got to be a Teaching Fellow a few years ago for three sections of HEB 1328 (Evolutionary Medicine: Comparative Perspectives on Medical, Surgical and Psychiatric Illness) with Professor Barbara Natterson-Horowitz. The lectures largely followed the book, which is nice because it means you can get a good part of the learning by reading it.
Evolutionary Perspectives on Human Disease
Immune systems, infection, and inherited disease across life.
This is a lecture-based class introducing the human immune system from a comparative perspective, along with some of the diseases our immune systems help us fight or can cause. We will learn about immune systems across life, in bacteria, plants, humans, and non-human animals—and how comparing immune systems allows us to better understand zoonotic transmission of disease. We will then look at some examples of infectious disease and inherited disease in animals and plants, and how animal parallels of human disease have helped us solve our own, human mysteries and make strides in medicine. Finally, we will look at how pathogens and their hosts impact each other’s evolution, and how human evolution has been impacted by disease.
We will meet on Tuesdays and Thursdays. Every week, you are responsible for reading your choice of two of the other listed texts closely enough to be an expert, and emailing me one generous tweet-length response to each text that you choose (≤250 words each). For the last 15 minutes of each lecture, I will display two responses on the projector and we will discuss them as a class. Highlighted texts are strongly recommended.
In lieu of a final exam, you will choose your favorite of your peers’ “tweets” that we discussed in class (not your own) and use it as a jumping-off point to write a 1,000- to 2,000-word response drawing from the texts and from class discussion.
By the end of this course, you will have a broad understanding of immune systems and disease across life, and (hopefully) the value of knowing it all.
The Immune System
Week 1: The Human Immune System
“Understanding the Immune System: How It Works,” published by the NIH in 2003 [link]
“The immune system,” published in Essays in Biochemistry in 2016 [link]
“Overview of the human immune response,” published in The Journal of Allergy and Clinical Immunology in 2006 [link]
Week 2: Bacterial Immune Systems
“The Origin of the Bacterial Immune Response,” Chapter 1 of Self and Nonself, 2012 [link]
“Systematic discovery of antiphage defense systems in the microbial pangenome,” published in Science in 2018 [link]
“Temperate Bacterial Viruses as Double-Edged Swords in Bacterial Warfare,” published in PLOS ONE in 2013 [link]
“Viruses Have Their Own Version of CRISPR,” published in The Atlantic in 2016 [link]
Week 3: Plant Immune Systems
“The plant immune system,” published in Nature in 2016 [link]
“Origin and evolution of the plant immune system,” published in New Phytologist in 2019 [link]
Week 4: Animal Immune Systems and Evolution
“Comparative Immune Systems in Animals,” published in Annual Review of Animal Biosciences in 2014 [link]
“Origin and Evolution of Adaptive Immunity,” published in Annual Review of Animal Biosciences in 2014 [link]
“Evolution of Immune Systems From Viruses and Transposable Elements,” published in Frontiers in Microbiology in 2019 [link]
Week 5: Vector Immune Systems and Zoonotic Transmission
“The Immune Responses of the Animal Hosts of West Nile Virus: A Comparison of Insects, Birds, and Mammals,” published in Frontiers in Cellular and Infection Microbiology in 2018 [link]
“Mosquito Vectors and the Globalization of Plasmodium falciparum Malaria,” published in Annual Review of Genetics in 2016 [link]
“Host phylogenetic distance drives trends in virus virulence and transmissibility across the animal-human interface,” published in Philosophical Transactions of the Royal Society B: Biological Sciences in 2019 [link]
“Surprise! British Red Squirrels Carry Leprosy,” published in The Atlantic in 2016 [link]
“Is It Possible to Predict the Next Pandemic?” published in The Atlantic in 2017 [link]
Week 6: Bats as Disease Vector
“Why Are Bats’ Immune Systems Totally Different From Any Other Mammal’s?” published in Popular Science in 2015 [link]
“Bats’ immune defenses may be why their viruses can be so deadly to people,” published in Science News in February 2020 [link]
“Accelerated viral dynamics in bat cell lines, with implications for zoonotic emergence,” published in eLife in 2019 [link]
“Dampened NLRP3-mediated inflammation in bats and implications for a special viral reservoir host,” published in Nature Microbiology in 2019 [link]
Infectious Disease Across Life
Week 7: Infectious Disease Across Life
“The Koala and the Clap: The Hidden Power of Infection,” Chapter 10 of Zoobiquity
“Plant and pathogen warfare under changing climate conditions,” published in Current Biology in 2018 [link]
“How Viruses Cooperate to Defeat CRISPR,” published in The Atlantic in 2018 [link]
“The Viruses That Eavesdrop on Their Hosts,” published in The Atlantic in 2018 [link]
Week 8: Extinctions and Mass Mortality Events
“Recent shifts in the occurrence, cause, and magnitude of animal mass mortality events,” published in PNAS in 2015 [link]
“A Starfish-Killing Disease Is Remaking the Oceans,” published in The Atlantic in 2019 [link]
“Why Did Two-Thirds of These Weird Antelope Suddenly Drop Dead?,” published in The Atlantic in 2018 [link]
“What We Can Learn From the Near-Death of the Banana,” published in Time Magazine in 2019 [link]
The Chytrid Fungus:
“Amphibian fungal panzootic causes catastrophic and ongoing loss of biodiversity,” published in Science in 2019 [link]
“The Worst Disease Ever Recorded,” published in The Atlantic in 2019 [link]
“The Cascading Consequences of the Worst Disease Ever,” published in The Atlantic in February 2020 [link]
Inherited Disease Across Life
Week 9: Inherited Disease Across Life
Heart Disease:
“The Feint of Heart: Why We Pass Out,” Chapter 2 of Zoobiquity
“Scared to Death: Heart Attacks in the Wild,” Chapter 6 of Zoobiquity
Mental Health:
“Grooming Gone Wild: Pain, Pleasure, and the Origins of Self-Injury,” Chapter 8 of Zoobiquity
“Fear of Feeding: Eating Disorders in the Animal Kingdom,” Chapter 9 of Zoobiquity
“A Landmark Study on the Origins of Alcoholism,” published in The Atlantic in 2018 [link]
Cancer:
“Jews, Jaguars, and Jurassic Cancer: New Hope for an Ancient Diagnosis,” Chapter 3 of Zoobiquity
“Elephants Have a Secret Weapon Against Cancer,” published in The Atlantic in 2018 [link]
Diabetes:
“The Blind Fish That Should Have Diabetes, But Somehow Doesn’t,” published in The Atlantic in 2018 [link]
Week 10: Allergy and Autoimmune Diseases
Allergies:
“Comparative Immunology of Allergic Responses,” published in Annual Reviews in 2015 [link]
“Early life factors that affect allergy development,” published in Nature Reviews Immunology in 2017 [link]
“Pet-keeping in early life reduces the risk of allergy in a dose-dependent fashion,” published in PLOS ONE in 2018 [link]
“Comparisons of Allergenic and Metazoan Parasite Proteins: Allergy the Price of Immunity,” published in PLOS Computational Biology in 2015 [link]
“Interactions between helminth parasites and allergy,” published in Current Opinion in Allergy and Clinical Immunology in 2009 [link]
Autoimmunity:
“Human autoimmune diseases: a comprehensive update,” published in The Journal of Internal Medicine in 2015 [link]
“Thymic tolerance as a key brake on autoimmunity,” published in Nature Immunology in 2018 [link]
“Regulatory T cells in autoimmune disease,” published in Nature Immunology in 2018 [link]
“Narcolepsy confirmed as autoimmune disease,” published in Nature News in 2013 [link]
Co-Evolution of the Human Immune System and Infectious Agents
Week 11: Co-Evolution of Microbial Pathogens and Their Hosts
“Rapid evolution of microbe-mediated protection against pathogens in a worm host,” published in The International Society for Microbial Ecology Journal in 2016 [link]
“The evolution of the host microbiome as an ecosystem on a leash,” published in Nature in 2017 [link]
“Harnessing the Power of Defensive Microbes: Evolutionary Implications in Nature and Disease Control,” published in PLOS Pathogens in 2016 [link]
“Some Microbes Have Been With Us Since Before We Existed,” published in The Atlantic in 2017 [links]
Relationships Between Bacteriophages, Bacteria, and the Human Immune System:
“Virus tricks the immune system into ignoring bacterial infections,” Nature News in 2019 [link]
“Bacteriophage trigger antiviral immunity and prevent clearance of bacterial infection,” published in Science in 2019 [link]
“We Might Absorb Billions of Viruses Every Day,” published in The Atlantic in 2017 [link]
Week 12: Human Evolution and Disease
“Signatures of Environmental Genetic Adaptation Pinpoint Pathogens as the Main Selective Pressure through Human Evolution,” published in PLOS Genetics in 2011 [link]
“Natural selection contributed to immunological differences between hunter-gatherers and agriculturalists,” published in Nature Ecology and Evolution in 2019 [link]
“How Viruses Infiltrated Our DNA and Supercharged Our Immune System,” published in The Atlantic in 2016 [link]
“Migrating microbes: what pathogens can tell us about population movements and human evolution,” published in Annals of Human Biology in 2017 [link]
Plasmodium falciparum and Sickle Cell:
“How Malaria Has Affected the Human Genome and What Human Genetics Can Teach Us about Malaria,” published in The American Journal of Human Genetics in 2005 [link]
“Sickle-cell mystery solved,” Nature News in 2011 [link]
“Hemoglobins S and C Interfere with Actin Remodeling in Plasmodium falciparum–Infected Erythrocytes,” published in Science in 2011 [link]
The Evolution of the Placenta:
“The Viruses That Made Us Human,” published by PBS in 2016 [link]
“Retroviruses and the Placenta,” published in Current Biology in 2012 [link]
“The placenta goes viral: Retroviruses control gene expression in pregnancy,” published in PLOS Biology in 2018 [link]
Microbial Inhabitants and Infectious Agents of the Human Body
Overview of common viruses, bacteria, and eukaryotes, pathogenic and not, and a history of disease outbreaks.
This class is an introduction to our neighbors in the human body: common viruses, bacteria, and eukaryotes—helpful, neutral, pathogen, or some combination of the three—that we share our bodies and our lives with, and which have profound impacts on both.
At the end of this course, you should have a broad understanding of the kinds of microbes that live in the human body and how they affect our health. You should also have a perspective and opinion on disease outbreaks throughout history, and the lessons we have hopefully learned from them. Finally, you should be able to critically read primary literature and use it to contribute to the broad conversation about human health in both speech and writing.
We meet on Mondays and Wednesdays. On Mondays, this is a lecture class, covering the texts and the topics listed below. On Wednesdays, this is a fast-paced discussion-based class. Every Wednesday meeting starts with a prescribed question, then progresses to your questions, switching topics at any ≥30-second lull in conversation.
The first week, I would like you to read all five papers. Every week after, you are responsible for reading at least two of the provided texts closely enough to be an expert, and for skimming or lightly reading at least three of the others to whatever extent is necessary for you to be able to respond to arguments and carry on intelligent conversation. In both cases, you are expected to go beyond what we cover in the Monday lecture. Come to class on Wednesday with at least three unique and interesting questions about the text(s) you choose to focus on or their implications to discuss with your colleagues. Highlighted texts are strongly recommended.
This class is a safe space. Please feel welcome to share your questions, thoughts, and opinions, even ones that seem “dumb” or “wrong.” We will work through them with empathy together as a class. To enable this atmosphere, please approach debate and discussion with empathy and enthusiasm, and remember that we are growing together and through each other. One of my favorite professors in undergrad started the semester distinguishing uncomfortable and unsafe. Fruitful discussion and growth can, at times, feel uncomfortable. If at any point this class makes you feel unsafe, let me know.
In lieu of a final exam, you will choose your favorite question proposed by a classmate (not by me and not by you) and write a 500- to 1500-word response to it drawn from the text and from class discussion. I will compile all responses into one anonymized document, and you will choose at least three classmates’ thoughts to respond to in generous tweet-length (≤250 words).
We include both scientific papers and publications from other media. I hope that every week, we will have a balance of experts in all texts in all formats, and that we start every new week more knowledgable and thoughtful than we were the week before.
Introduction
Week 1: A Bird’s-Eye View
“Introduction to Pathogens,” from Molecular Biology of the Cell, published in 2002 [link]
“Cell Biology of Infection,” from Molecular Biology of the Cell, published in 2002 [link]
“Visualizing the History of Pandemics,” published in Visual Capitalist on March 14, 2020 [link]
“The Microbiome and Human Biology,” published in Annual Review of Genomics and Human Genetics in 2017 [link]
“Highlights from studies on the gut microbiome,” published in Nature Outlook in January 2020 [link]
Neutral or Helpful Inhabitants
Week 2: The Microbiome, and Occasionally Helpful Parasites
The Microbiome:
“Man and the Microbiome: A New Theory of Everything?” published in Annual Review of Clinical Psychology in 2019 [link]
“No Vacancy: How beneficial microbes cooperate with immunity to provide colonization resistance to pathogens,” published in The Journal of Immunology in 2015 [link]
“When Poop Becomes Medicine,” published in The Atlantic in 2018 [link]
“A Probiotic Skin Cream Made With a Person’s Own Microbes,” published in The Atlantic in 2017 [link]
“The Hottest New Cancer Drugs Depend on Gut Microbes,” published in The Atlantic in 2015 [link]
“How Bacteria Could Protect Tumors From Anticancer Drugs,” published in The Atlantic in 2017 [link]
“A Tiny Tweak to Gut Bacteria Can Extend an Animal’s Life,” published in The Atlantic in 2017 [link]
Parasites:
“Friendly foes: The evolution of host protection by a parasite,” published in Evolution Letters in 2017 [link]
“Parasites inside your body could be protecting you from disease,” published in The Conversation [link]
“Helminth infection, fecundity, and age of first pregnancy in women,” published in Science in 2015 [link]
Week 3: GB Virus C, a Helpful Virus
“GB virus C: the good boy virus?” published in Trends in Microbiology in 2012 [link]
“Effect of early and late GB virus C viraemia on survival of HIV-infected individuals: a meta-analysis,” published in HIV Medicine in 2006 [link]
“GBV-C/HIV-1 coinfection is associated with low HIV-1 viral load and high CD4+ T lymphocyte count,” published in Archives of Virology in 2017 [link]
“Pegivirus avoids immune recognition but does not attenuate acute-phase disease in a macaque model of HIV infection,” published in PLOS Pathogens in 2017 [link]
“Fighting the Public Health Burden of AIDS With the Human Pegivirus,” published in American Journal of Epidemiology in May 2019 [link]
“GB Virus C Coinfections in West African Ebola Patients,” published in Journal of Virology in 2015 [link]
Harmful Inhabitants
Week 4: The Common Cold and Influenza (and why they won’t go away)
The Common Cold:
“Rhinoviruses,” Chapter 238 of Principles and Practice of Pediatric Infectious Diseases, 2018 [link]
“Human Coronaviruses,” Chapter 222 of Principles and Practice of Pediatric Infectious Diseases, 2018 [link]
“Adenoviruses,” Chapter 210 of Principles and Practice of Pediatric Infectious Diseases, 2018 [link]
“The Economic Burden of Non–Influenza-Related Viral Respiratory Tract Infection in the United States,” published in Archives of Internal Medicine in 2013 [link]
“Why Haven’t We Cured the Common Cold Yet?” published in Scientific American in 2018 [link]
Curing the Common Cold:
“Scientists think the common cold may at last be beatable,” published in STAT in 2016 [link]
“A polyvalent inactivated rhinovirus vaccine is broadly immunogenic in rhesus macaques,” published in Nature Communications in 2016 [link]
“Scientists close in on a cure for the common cold,” published in Stanford Medicine Scope in 2019 [link]
“Enterovirus pathogenesis requires the host methyltransferase SETD3,” published in Nature Microbiology in 2019 [link]
Influenza:
“Influenza Viruses,” Chapter 229 of Principles and Practice of Pediatric Infectious Diseases, 2018 [link]
“Plague genome: The Black Death decoded,” Nature News 2011 [link]
“Yersinia pestis and the plague of Justinian 541-543 AD: a genomic analysis,” published in 2014 [link]
“A draft genome of Yersinia pestis from victims of the Black Death,” published in Nature in 2011 [link]
Smallpox:
“A time transect of exomes from a Native American population before and after European contact,” published in Nature in 2016 [link]
“How Europeans brought sickness to the New World,” Science News 2015 [link]
Typhoid Mary:
“Mary Mallon (1869-1938) and the history of typhoid fever,” published in the Annals of Gastroenterology in 2013 [link]
“Typhoid Mary’s tragic tale exposed the health impacts of ‘super-spreaders’,” published in National Geographic in March 2020 [link]
“A Life in Pursuit of Health,” about Josephine Baker, published in The New York Times in 2013 [link]
And a Few Other Superspreaders:
“Extensive Transmission of Mycobacterium tuberculosis from a Child,” published in The New England Journal of Medicine in 1999 [link]
“Party Zero: How a Soirée in Connecticut Became a ‘Super Spreader,’” published in The New York Times on March 23, 2020 [link]
Week 6: Plasmodium/Malaria
“Plasmodium Species (Malaria),” Chapter 271 of Principles and Practice of Pediatric Infectious Diseases, 2018 [link]
“About Malaria,” CDC, especially “FAQs” [link], “Disease” [link], “Biology” [link], “Where Malaria Occurs” [link], and “Malaria’s Impact Worldwide” [link]
“The History of Malaria, an Ancient Disease,” by the CDC [link]
“Greater political commitment needed to eliminate malaria,” published in Infectious Diseases of Poverty in 2019 [link]
“Malaria Genomics in the Era of Eradication,” published in Cold Spring Harbor Perspectives in Medicine in 2017 [link]
How Malaria Spread to Humans and Around the World:
“Resurrection of the ancestral RH5 invasion ligand provides a molecular explanation for the origin of P. falciparum malaria in humans,” published in PLOS Biology in 2019 [link]
“Human migration and the spread of malaria parasites to the New World,” published in Nature in 2018 [link]
Acquired Immunity:
“Quantification of anti-parasite and anti-disease immunity to malaria as a function of age and exposure,” published in eLife in 2018 [link]
“Malaria: Age, exposure and immunity,” in eLife as an Insight, 2018 [link]
“Host-mediated selection impacts the diversity of Plasmodium falciparum antigens within infections,” published in Nature Communications in 2018 [link]
Week 7: Hepatitis A
“Hepatitis A Virus,” Chapter 237 of Principles and Practice of Pediatric Infectious Diseases, 2018 [link]
“Widespread outbreaks of hepatitis A across the United States,” CDC, March 2020 [link]
“Increase in Hepatitis A Virus Infections – United States, 2013-2018,” CDC, 2019 [link]
“Summary of reported hepatitis A cases linked to person-to-person outbreak, Massachusetts, April 1, 2018-March 6, 2020,” MA DPH [link]
“Forgotten but Not Gone: Learning From the Hepatitis A Outbreak and Public Health Response in San Diego,” published in Topics in Antiviral Medicine in 2019 [link]
“Molecular Genotyping of Hepatitis A Virus, California, USA, 2017–2018,” published in Emerging Infectious Diseases in 2019 [link]
“Emergence of Hepatitis A Virus Genotype IIIA during an Unprecedented Outbreak in New Hampshire, 2018-2019,” unpublished
Bathroom Access:
“An outbreak waiting to happen: Hepatitis A marches through San Diego’s homeless community,” published in STAT in 2017 [link]
“After crackdown on tent city, homeless recount Hepatitis horror stories,” published in the San Diego Union-Tribune in 2017 [link]
“Hepatitis A outbreak sparks call for L.A. to give homeless people more street toilets,” published in The Los Angeles Times in 2017 [link]
“The Politics of Going to the Bathroom,” published in The Nation in 2019 [link]
Herd Immunity and Co-Infections:
“Notes from the Field: Acute Hepatitis A Virus Infection Among Previously Vaccinated Persons with HIV Infection – Tennessee, 2018,” CDC, 2019 [link]
“Herd Immunity Likely Protected the Men Who Have Sex With Men in the Recent Hepatitis A Outbreak in San Diego, California,” published in Clinical Infectious Diseases in 2019 [link]
Week 8: HIV/AIDS
The Virus:
“Introduction to Retroviridae” Chapter 231 [link] and “Human Immunodeficiency Virus” Chapter 233 [link] of Principles and Practice of Pediatric Infectious Diseases, 2018
History:
“HIV epidemiology. The early spread and epidemic ignition of HIV-1 in human populations,” published in Science in 2014 [link]
“Origins of HIV and the AIDS Pandemic,” published in Cold Spring Harbor Perspectives in Medicine in 2011 [link]
“Response to the AIDS Pandemic—A Global Health Model,” published in The New England Journal of Medicine in 2013 [link]
“The Reagan Administration’s Unearthed Response to the AIDS Crisis is Chilling,” published in Vanity Fair in 2015 [link]
“How the Media, the White House, and Everyone Else Failed AIDS Victims in the 80s,” published in VICE in 2016 [link]
“Long-term survivors of HIV/AIDS reflect on what they’ve witnessed and endured,” published on PBS in February 2020 [link]
HIV/AIDS today:
“Today’s HIV/AIDS Epidemic,” CDC Fact Sheet published in 2016 [link]
“Ending AIDS? These three places show the epidemic is far from over,” published in Science News in 2018 [link]
Curing HIV:
“Loss and Recovery of Genetic Diversity in Adapting Populations of HIV,” published in PLOS Genetics in 2014 [link]
“Second person cured of HIV is still free of active virus two years on,” in CNN on March 11, 2020 [link]
“Evidence for HIV-1 cure after CCR5Δ32/Δ32 allogeneic haemopoietic stem-cell transplantation 30 months post analytical treatment interruption: a case report,” published in The Lancet on March 10, 2020 [link]
“Sequential LASER ART and CRISPR Treatments Eliminate HIV-1 in a Subset of Infected Humanized Mice,” published in Nature Communications in 2019 [link]
Week 9: Viral Hemorrhagic Fevers: Ebola and Lassa
“Filoviruses and Arenaviruses,” Chapter 230 of Principles and Practice of Pediatric Infectious Diseases, 2018 [link]
Lessons from sequencing Ebola and Lassa:
“An Outbreak of Ebola Virus Disease in the Lassa Fever Zone,” published in The Journal of Infectious Diseases in 2016 [link]
“Clinical Sequencing Uncovers Origins and Evolution of Lassa Virus,” published in Cell in 2015 [link]
“Genomic surveillance elucidates Ebola virus origin and transmission during the 2014 outbreak,” published in Science in 2014 [link]
“Ebola Virus Epidemiology, Transmission, and Evolution during Seven Months in Sierra Leone,” published in Cell in 2015 [link]
“Ebola Virus Epidemiology and Evolution in Nigeria,” published in The Journal of Infectious Diseases in 2016 [link]
“Temporal and spatial analysis of the 2014–2015 Ebola virus outbreak in West Africa,” published in Nature in 2015 [link]
“Rapid outbreak sequencing of Ebola virus in Sierra Leone identifies transmission chains linked to sporadic cases,” published in Virus Evolution in 2016 [link]
“The evolution of Ebola virus: Insights from the 2013–2016 epidemic,” published in Nature in 2016 [link]
Ebola adaptations to host:
“Virus genomes reveal factors that spread and sustained the Ebola epidemic,” published in Nature in 2017 [link]
“Ebola Virus Glycoprotein with Increased Infectivity Dominated the 2013-2016 Epidemic,” published in Cell in 2016 [link]
Week 10: Genomic Epidemiology and Modern Outbreak Response
“Tracking virus outbreaks in the twenty-first century,” published in Nature Microbiology in January 2020 [link]
“Precision epidemiology for infectious disease control,” published in Nature Medicine in 2019 [link]
“Real-time digital pathogen surveillance — the time is now,” published in Genome Biology in 2015 [link]
Ebola:
“Knowledge of Ebola is the weapon to fight it,” published in The Boston Globe in 2014 [link]
“Roots, Not Parachutes: Research Collaborations Combat Outbreaks,” published in Cell in 2016 [link]
“Lessons from Ebola: Improving infectious disease surveillance to inform outbreak management,” published in Science Translational Medicine in 2015 [link]
Zika and mumps:
“Combining genomics and epidemiology to track mumps virus transmission in the United States,” published in PLoS Biology in February 2020 [link]
“Zika virus evolution and spread in the Americas,” published in Nature in 2017 [link]
“Genomic epidemiology reveals multiple introductions of Zika virus into the United States,” published in Nature in 2017 [link]
Week 11: Difficult Decisions and a Case Study in Progress: Coronavirus Outbreak Response
Genomic research:
“Data Sharing and Open Source Software Help Combat Covid-19,” published in WIRED on March 13, 2020 [link]
“Genome Composition and Divergence of the Novel Coronavirus (2019-nCoV) Originating in China,” published in Cell on March 11, 2020 [link]
“Probable pangolin origin of SARS-CoV-2 associated with the COVID-19 outbreak,” to be published in Cell in March 2020 [link]
“The proximal origin of SARS-CoV-2,” published in Nature Medicine on March 17, 2020 [link]
“Why the Coronavirus Has Been So Successful,” published in The Atlantic on March 20, 2020 [link]
Social measures against disease spread:
“Impact of non-pharmaceutical interventions (NPIs) to reduce COVID19 mortality and healthcare demand,” published by the Imperial College COVID-19 Response Team on March 16, 2020 [link]
“Review of Ferguson et al ‘Impact of non-pharmaceutical interventions…’” published by New England Complex Systems Institute on March 17, 2020 [link]
“The Korean Clusters,” published in Reuters on March 3, 2020 [link]
“The U.K.’s Coronavirus ‘Herd Immunity’ Debacle,” published in The Atlantic on March 16, 2020 [link]
Governmental and organizational outbreak response; economic impact and tradeoffs:
“The 4 Key Reasons the U.S. Is So Behind on Coronavirus Testing,” published in The Atlantic on March 13, 2020 [link]
“You’re Likely to Get the Coronavirus,” published in The Atlantic in February 2020 [link]
“A fiasco in the making? As the coronavirus pandemic takes hold, we are making decisions without reliable data,” published in STAT on March 17, 2020 [link]
The Daily podcast:
“Why the U.S. Wasn’t Ready for the Coronavirus” on March 11, 2020 [link]
“Learning to Live with the Coronavirus” on March 13, 2020 [link]
“Why This Recession Will Be Different” on March 16, 2020 [link]
Week 12: Disease Surveillance in the Age of Surveillance
Influenza:
“nextflu: real-time tracking of seasonal influenza virus evolution in humans,” published in Bioinformatics in 2015 [link]
“Flu Near You: Crowdsourced Symptom Reporting Spanning 2 Influenza Seasons,” published in American Journal of Public Health in 2015 [link]
“Comparison of crowd-sourced, electronic health records based, and traditional health-care based influenza-tracking systems at multiple spatial resolutions in the United States of America,” published in BMC Infectious Diseases in 2018 [link]
Coronavirus:
“This is how the CDC is trying to forecast coronavirus’s spread,” published in MIT Technology Review on March 13, 2020 [link]
“We’re not going back to normal,” published in MIT Technology Review on March 17, 2020 [link]
“Singapore is the model for how to handle the coronavirus,” published in MIT Technology Review on March 12, 2020 [link]
“To Track Coronavirus, Israel Moves to Tap Secret Trove of Cellphone Data,” published in The New York Times on March 16, 2020 [link]
Introduction to Data Analysis Methods for Biological Inference
Seminar on experimental design, modeling, working with multiple variables, wrangling messy data, genomic sequencing, and popular techniques and tools in computational biology.
This class is an introduction to some of the tools of computational biology. We will look at statistical tests and learn how to disentangle the effects of multiple variables. We will learn how to do genome-wide association studies and principal component analysis. We will learn about how genomic sequencing works, and look at how it can be used for diagnosis or discovery of novel organisms. Finally, we will learn how to use genomic sequencing to trace disease transmission. By the end of this course, you should have the tools you need to analyze your own or publicly available data.
We meet on Tuesdays and Fridays. Tuesdays are lectures on the topics and texts listed. Highlighted texts are strongly recommended. On Fridays, we meet for an extended workshop to apply the week’s tools to publicly available data or to data that you bring with you to class (except in Week 7, when we will generate new sequence data). Before every Friday, you are responsible for writing a short proposal for the week, including what dataset you plan to analyze, what tools you plan to use for what analyses, and any hypotheses you have (≤500 words). At the end of the semester, you will choose whichever workshop was most inserting or successful for you to extend into a short final project, which you can work on alone or in a group. On the last Friday of class we will go around the room and briefly summarize our analyses and findings in an informal setting over snacks.
Week 1: Experimental Design, Statistical Tests, Data Visualization
Experimental Design:
“Experimental Design,” Chapter 7 of MIT’s 6.S085 Statistics for Research Projects course notes [link]
Statistical Tests, from the Handbook of Biological Statistics, 2014:
“Visualization of multiple alignments, phylogenies and gene family evolution,” published in Nature Methods in 2010 [link]
Notes on P-Values:
“The fickle P value generates irreproducible results,” published in Nature Methods in 2015 [link]
“Aligning statistical and scientific reasoning,” published in Science in 2016 [link]
“Measurement error and the replication crisis,” published in Science in 2017 [link]
Week 2: Modeling the Effects of a Single or Multiple Variables: Part I
Regression and Other Stories (to be published in 2020):
Chapter 5: “Background on regression modeling”
Chapter 6: “Linear regression with a single predictor”
Chapter 8: “Linear regression with multiple predictors”
Chapter 9: “Transformations and model building”
Week 3: Modeling the Effects of a Single or Multiple Variables: Part II
Regression and Other Stories (to be published in 2020):
Chapter 10: “Logistic regression”
Chapter 11: “Generalized linear models”
Chapter 14: “Missing-data imputation”
Chapter 15: “Using, evaluating, and comparing models”
Appendix A: “Six quick tips to improve your regression modeling”
Week 4: Genome-Wide Association Studies, Part I
GWAS in Action:
“10 Years of GWAS Discovery: Biology, Function, and Translation,” published in The American Journal of Human Genetics in 2017 [link]
“Benefits and limitations of genomewide association studies,” published in Nature in 2019 [link]
Understanding and Using GWAS:
“Microarrays – DNA Chips,” 2017 [link] and “DNA Microarray,” 2012 [link]
“PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses,” published in The American Journal of Human Genetics in 2007 [link]
“Methods and Tools in Genome-wide Association Studies,” Chapter 5 of Computational Cell Biology, 2018 [link]
Week 5: Genome-Wide Association Studies, Part II
“Population genetics and GWAS: A primer,” published in PLOS Biology in 2018 [link]
From Principles of Population Genetics, 2007:
Chapter 9.1: “Evolution of Genome Size and Composition”
Chapter 9.2 “Genome-Wide Patterns of Polymorphism”
Chapter 9.3: “Differences Between Species”
Chapter 10.1: “Human Polymorphism”
Chapter 10.2: “Population Genetic Inferences from Human SNPs”
Chapter 2.5: “Linkage and Linkage Disequilibrium”
Chapter 2.6: “Causes of Linkage Disequilibrium”
Chapter 10.3: “Linkage Disequilibrium across the Human Genome”
Chapter 10.7: “Seeking Signatures of Human-Specific Genetic Adaptations”
Week 6: Principal Component Analysis (PCA)
PCA in Action:
“Genes mirror geography within Europe,” published in Nature in 2008 [link]
“Spatial population genomics of the brown rat (Rattus norvegicus) in New York City,” published in Molecular Ecology in 2018 [link]
“Urban rat races: spatial population genomics of brown rats (Rattus norvegicus) compared across multiple cities,” published in Proceedings of the Royal Society B: Biological Sciences in 2018 [link]
Understanding and Using PCA:
“PCA in R Using FactoMineR: Quick Scripts and Videos,” 2017 [link]
“A Step by Step Explanation of Principal Component Analysis,” 2019 [link]
“PCA: A Practical Guide to Principal Component Analysis in R & Python,” 2016 [link]
L. A. K. 
