The Quantitative Virology and Evolution Unit is led by Patrick Dolan, Ph.D., Earl Stadtman Tenure-Track Investigator and Unit Chief in the Laboratory of Viral Diseases, NIH-NIAID, in Bethesda, MD.

Our work is focused on the use of quantitative experimental and computational approaches to understand the roles of heterogeneity, history, and constraint in viral emergence and evolution. In one focus area, we use single-cell sequencing approaches to characterize the responses to infection in cell culture and animal models. We hope to these studies will help us understand within-host evolutionary dynamics, and the determinants of host tropism and pathogenesis. In another focus area, we use phylogenetic tools to reconstruct the evolution of emerging viruses. We then experimentally interrogate these ancestral evolutionary paths with mutational screens to understand how viruses emerge.

Those interested in developing independent projects in single-cell transcriptomics, single-genome viral population genetics, phylogenetics and evolutionary biochemistry while working in a supportive and well-resourced environment on a range of viral pathogens and host systems should send a CV and cover letter to Patrick Dolan, Ph.D..

• Tutorials for computational tools used by the lab: https://github.com/QVEU/QVEU_Code/tree/main/Tutorials

We use Git for version control. It helps us disseminate our work and promote reproducibility. Use it to make your work and the work of others more efficient and effective.

To contribute to this or any repository, you will need to create a GitHub account and fork the repository. This creates a new, personal version of the code. Once you have forked the repository, you can clone it to your local machine or to the cluster and begin working on your changes. When you have changes that you feel are stable enough to replace the current code version, you can submit a pull request. We won’t describe Git in detail here, but many good resources exist. For beginners (and experts) the GitHub Desktop App is very helpful.

The NIAID Skyline Cluster is an essential tool for your work in the QVEU lab. Skyline is a high-performance computing (HPC) cluster that is used by researchers at the QVEU lab to do their research and store long-term data. The cluster is a shared resource that is managed by NIAID. For help, please contact NIAIDHPCSUPPORT@niaid.nih.gov and CC Patrick for tracking purposes.

The cluster is composed of a number of compute nodes, each of which has multiple CPUs and a large amount of memory (https://skyline.niaid.nih.gov/hardware/). The nodes are connected by a high-speed network, which allows them to communicate with each other quickly and efficiently.

The cluster is used for a variety of purposes, including:

• Running our analyses
• Accessing software packages for analysis
• Developing code in R, python, BASH/UNIX or others languages.
• Hosting jupyter notebooks we can access through the browser
• Storing large datasets
• Check out these links to get started.
  • https://skyline.niaid.nih.gov/
  • https://skyline.niaid.nih.gov/scheduler/#command-overview

All code should be written in accordance with the following coding standards:

• Use descriptive variable and function names
• Add comments to your code to explain what it does as a favor to your future self and others.
• Test your code thoroughly, and save well documented working versions with ‘readme’ markdowns (like this one).

All changes to code should be committed to this repository using Git. Please include a brief description of your changes in the commit message. Use Github Desktop if you prefer.

All code should be documented using docstrings. Docstrings should include the following information: A brief description of the function or class The parameters of the function or class The return value of the function or class Any exceptions that the function or class may raise

To the extent possible, we should aspire to test and include testing units with all finished code. Unit tests should be written in a separate file and should test the functionality of each function or class.

If you have any questions about this repository or the coding standards, please contact Patrick Dolan, Unit Chief (Patrick.Dolan@nih.gov).