Handbook

Welcome to the Moncla lab! This lab handbook is intended to give you an overview of how I think about running a scientific lab and expectations I have for myself and team members. It also includes some materials that may be useful for getting acquainted with programming, phylogenetics, and virology.

Research goals and ethics

We are excited about RNA viruses and the ways that they evolve, transmit, and emerge in new host species. We are generally interested in these questions across a spectrum of levels: how viruses evolve during replication and transmission within individuals, how new variation is generated and propagated along transmission chains, and how viruses are spread among global populations, communities, and host species. The primary tools that we use to answer these questions are computational, but we also do wet lab experiments to generate sequence data and to validate our computational findings. I believe that open science is both the right way to approach science, and is also the way of the future. Towards this end, a priority in the lab is to do reproducible science that is shared openly and freely to the public and the scientific community. This means that our projects, code, and protocols will be made available on Github, our sequence data will be uploaded to public repositories (Genbank, SRA and GISAID), and that data that is ready for the world will be made available as preprints prior to publication. We will also use resources that are freely available and public whenever possible, and acknowledge individuals who have contributed data and software. It also means that we will strive to include the voices of groups and individuals who are impacted by our research, and whose perspectives deserve to be part of our work. Although I find RNA viruses endlessly fascinating, it is crucial to remember that we study these viruses because they impact the lives of human beings, often with significant disparities across sociodemographic lines. It is our responsibility to ensure that the science we put forth into the world serves the goal of improving human health, without encouraging stigma or blame.

Lab goals and ethics

Labs function best when individuals feel supported, rested, and happy. It is my goal to foster an inclusive environment in which individuals are able to work with others, contribute new ideas, receive criticism and feedback, and grow as scientists. It is my job to put the proper supports in place to make that happen. What I ask of you is to tell me if something is not working for you, and to be honest with me about the support that you need. I will do my absolute best to accommodate your needs, and will work with you to learn how to best support your science. If you or someone you know is experiencing harassment, please report it to me. I believe that there is no place in science for harassment or discrimination, regardless of how scientifically productive someone is, and that is non-negotiable.

Mentorship philosophy

One of my favorite things about science is the opportunity to work with new people who have exciting, fresh ideas. My overarching mentorship philosophy is that my job is to work with you to develop the skills you need to achieve your career goals. I believe that all career paths are valid, and I am committed to working with you to help you develop the skills and experiences you need to be successful in the next stage of your career. I believe that a laboratory environment works best when everyone is able to contribute to lab goals and directions, and I will strive to ensure that each person has a voice in decision making in the laboratory. Together, it is my goal to work with you to develop the critical thinking, speaking, and writing skills necessary for success in your chosen scientific career, so that you leave the lab as a colleague poised for success. Towards this end, we will have a yearly meeting to discuss your career plans, and how we can modify your work in the lab to best fit that plan. We will also have regular, recurring meetings to discuss progress in the lab and to strategize about new directions and experiments. I would imagine these meetings being more frequent at the beginning, and become less frequent depending on career stage and desired independence, and it is my hope that this can develop organically.

Thoughts/guide to PhD rotations

I think that rotations are a wonderful way to try out different labs and see if they are a good fit. I’ve seen many students realize during rotations that they really like a kind of work they never imagined, and conversely, sometimes realize that work they thought they would like is not for them. I also believe that there is no better way to get a sense for the lab environment than spending a rotation with the lab and PI. During a rotation, you should get a sense for several things that are important for a PhD: how helpful and collaborative are the other lab members? Are people in the lab happy and productive? Do people keep flexible schedules, or is it more highly structured? Will you have sufficient mentorship, and are your interactions with the PI and other lab members helpful and productive? These are all things that are hard to evaluate through interviews alone, but become very obvious during a rotation.

My general philosophy on rotations are that they are best thought of as extended, 2-way interviews. As the PI, my job is to evaluate whether you are a good fit for the lab. As a rotator, your job is to figure out if you can see yourself spending the next several years in this lab environment doing this type of work. I would recommend thinking about the following: Do I like the PI? Do I like the overall lab environment? Do I feel intellectually excited about these research questions? Are the day-to-day activities of performing the research ones that I enjoy, or do I find this type of work really tedious? Do I enjoy reading the papers that are in this field? Am I able to ask questions and get good feedback?

On my end, when I evaluate fit, I ask myself the following questions: Does this person conduct themselves professionally, and are they good team members? Are they self-motivated and hard-working? Are they intellectually engaged, and do they take ownership of their project and work to push it forward? Is this person organized and detail-oriented, and can I trust their work? Are our communication styles compatible, and do they take constructive criticism well? Is the degree or type of mentorship this person requires something I know I can provide? I will never evaluate your progress based on your level of past computational training, and am much more interested in understanding how you think about and approach problems, think through solutions, and evaluate them. I also want to see how you intellectually engage with the research questions and why they matter, and observe how you go about learning new things. To me, these things are all much more important than your background, so don’t let your experience keep you from a rotation!

Working hours

I personally find working in a group setting to be a great way to learn from others and foster a sense of camaraderie. Being in a social lab environment has absolutely helped me during times where my science was challenging, and made me enjoy the day to day of my job. However, I know that many people are not like me, and may work better at home or during non-standard hours. It is my expectation that people are generally available during the hours of 10 to 4 pm, Monday through Friday. It is also my expectation that people physically come into work at least 4 days a week, with the more the better. Should you require a special accommodation, I am happy to discuss it to find a schedule that works well for you. That being said, I do not want to keep track of your hours, and will mostly be happy if you get your work done.

Vacation time

I love vacation! I also really like doing things that are not science. I bake, hike, ski, play trumpet, and watch trashy movies with my partner, and it is really important to me that I maintain time in my life to enjoy activities outside of work. I wouldn’t expect anything different from personnel in my lab, and absolutely expect you to take vacations and enjoy your life. I will not ask you to do weekend work, and won’t expect you to respond to emails after work hours. I usually take about 4 weeks off per year in addition to standard, legal holidays, and hope personnel in my lab do the same. So, you get 20 paid vacation days per year, in addition to university holidays, no questions asked. Please let me know when you will be out so that I can plan, but know that I expect you to take time off (seriously, please do it!).

Sick time

We are an infectious disease lab, and there is no universe in which I would want you to come in if you are sick. If you are sick, please stay home and recover, and come back when you feel ready to do so. If you end up requiring a prolonged sick leave, let me know and we can discuss how to manage your responsibilities in the lab while you recover.

Meetings

Once our lab gets to a critical mass, we will have a once a week lab meeting. These meetings are there for group members to present their ongoing work, lead discussion of a cool paper or topic, or lead some other group activity that is relevant to the lab. Once a year, I will host a state of the lab meeting, where I will give updates on where the lab is going, and where we can strategize about how to improve lab function.

Social activities

Occasionally, we will have social events with the lab, like lab dinners or happy hours. Although it is my hope that people would enjoy attending these events, they are absolutely not required. However, if there is anything that I could do to make lab hangouts more accessible or appealing, please let me know!

Resources

Personnel Resources

1. What the lab will provide: In this lab, anything work-related (travel, meals, computers, office equipment) will all be covered by the lab. This includes expenses for travel to workshops and conferences, with an expected frequency of ~1 big conference per person per year. You will also be provided with a laptop, monitor(s), hard drives, and any office or computing supplies that would improve your work environment. Work-related books, software licenses, and subscription services can also be purchased by the lab.

2. Graduate emergency fund. This is a cool resource to help defray the costs of emergency expenses for graduate students. Emergency situations include things like surprise medical bills, travel for family emergencies, and theft of personal items. Check it out!

3. Title IX office. This page has a lot of links for issues of harassment and discrimination. Policies and guides for submitting sexual harassment complaints can be found here, and information about university Ombuds (who are often a good first point of contact for reporting harassment issues) can be found here.

4. Employee Assistance Program. Penn has a system in place for students, faculty, and staff (including post-docs) to access up to 8 free therapy/counseling sessions per year. For faculty, staff, and post-docs, this program is EAP (the employee assistance program), while for students this service is provided by CAPS (Counseling and Psychological services). This page has information on who to call to set up counseling. You will be matched with a provider who participates in the EAP or CAPS program, who is a licensed therapist/counselor.

Computation

I spent a majority of my life believing that computational skills were an inherent ability that I simply did not possess. When I learned to code in graduate school, I felt this overwhelming sense that I had learned a very accessible skill that made my life much easier. It also became clear to me that anyone can learn to code, and I feel quite passionate about making sure that people have the support they need to develop computational skills. If you are interested in the lab, but are hesitant about your ability to do computational work, please do not let that stop you from contacting me. While coding may not be enjoyable to everyone, I promise that it is a skill anyone can learn. Below, I’ve compiled a few resources that helped me learn.

1. Codecademy In this lab, we mostly use python and R. Learning some basics of navigating your computer through the terminal, as well as basic python scripting can get you pretty far. I believe that many of the courses are free, but if not, you should be able to do a free trial for 30 days or so. I’d recommend getting started with intro to bash and python.

2. Practical Computing for Biologists This book was my very first introduction to command-line navigation and coding, and I found it to be a really great intro. I have a copy in my office that I keep around to lend to people, and am more than happy to buy additional copies.

3. Git Git is a language developed for version control. In this lab, we use Github to organize projects and data files and to make our science open access. This lab website was build via github pages, and github is a powerful (if sometimes confusing!) tool. This guide gives you some background on getting set up with a github account and some basic commands and tutorials for how it works. This tutorial gets you set up with a basic repo, and this post provides some background on git.

4. Statistical Rethinking This is an amazing book about Bayesian statistics. During my post-doc, our lab did a book club where we went through this book, and I learned a lot about regression models and Bayesian stats. The amazing thing about this book is that it is so well written that it is an interesting read (I’m serious!) and is really easy to follow if you’ve taken any introductory statistics course. It also goes into some explanation about the importance and value of distributions and developing your own test statistics, which are concepts that I find useful and powerful. Finally, it pairs information with practical examples and problem sets in R, so you get actual experience running the analyses. The first 2 chapters are free online, and I have a copy in my office that I’m happy to lend out.

Phylodynamics

The field of phylodynamics has exploded in recent years, which means that there are now some really great resources for learning about it. Below are some tools and background reading that are great for learning.

Lectures, tutorials, and handbooks

1. Lectures and labs on introduction to phylodynamics, Nextstrain and BEAST. I taught 2 lectures and 2 labs for the Genomics of Disease in Wildlife Workshop in 2023. Those lectures go over an introduction to the field of phylodynamics, coalescent theory, and an introduction to Markov Chain Monte Carlo and BEAST. In the labs, I used a nice dataset that Maria put together to go over how to set up a BEAST analysis and to develop and use Nextstrain. Feel free to look through these slides and/or the lab activities. The lab activities are meant to be self-guided, and include screenshots and commands to set up and analyze the results of BEAST and Nextstrain analyses. Check out the entire set of course materials here.

2. Trevor Bedford’s lectures on phylodynamics

3. Nextstrain tutorial Nextstrain is a set of tools for performing phylodynamic analyses. The software powers the live website hosted at Nextstrain.org, which is a platform for real-time tracking of viral pathogens. It was developed by Trevor Bedford and Richard Neher, and is maintained by a large team of scientists and software developers. This documentation page includes background information on what Nextstrain is, how to install the software, and a great tutorial for getting a Zika build up and running.

4. Felsenstein pruning algorithm If there is one paper that is important for understanding phylogenetics, it is this one. This is Joe Felsenstein’s original paper on the Maximum Likelihood approach that is used to infer trees. This basic algorithm is used in most software that is used today, and has been applied to many other applications. It’s also a very well-written paper that I personally found quite useful for learning about phylogenetics.

5. How to read a tree This is generally a very nice, quick introduction on how to read and interpret a phylogeny.

6. David Rasmussen’s reading list David Rasmussen has put together this really great list of papers that cover many aspects of phylogenetics and evolutionary biology as applied to viruses.

7. Black and Dudas Genomic Epidemiology handbook This handbook was written by Alli Black and Gytis Dudas, specifically targeting individuals working in the field of public health practice. It goes over some background concepts in genomic epidemiology, and is a nicely written guide.

8. Trevor Bedford’s dynamics practical. I did this practical when I first joined the Bedford lab as a post doc and it was a really nice introduction to setting up a beast analysis. It is quick, easy, and a good introduction.

Papers

• Pybus and Rambaut, 2009
• Viral Phylodynamics
• Tracking outbreaks in the 21st century. This is a really nice review article about the utility of viral genomics for genomic epidemiology and outbreak tracking.

Population genetics

Population genetics is the foundation of phylodynamics. It is also the primary field that studies of within-host diversity have drawn from. These book chapters by Magnus Nordborg provide a great introduction into the coalescent, and how deviations from ideal populations alter tree topologies. This review is also a good place to start, and provides a nice overview of the coalescent.

Penn Vet resources and guides

Penn Vet has a lot of resources that can be hard to access. Here, we’ve compiled instructions for how to access some of these resources, which we want to make available to others in the department.

1. Instructions for printing at Penn Vet

2. Instructions for connecting to Penn Vet drives