Open Science

We practice open science.

Open source software.

Multiple open science practices are fundamental to the way my lab teaches, practices, and disseminates science. We are primarily a computational lab whose major impact is the contribution of algorithms and software tools that empower our science and that of others. Open-source software development is the rule in my lab. We have published more than 50 freely-available, open-source software tools that have empowered diverse research areas. All of our software is freely available on Github (for example, BEDTOOLS), and we are also known for creating comprehensive documentation and extensive testing to ensure rigor and reproducibility.

Early dissemination with preprint servers.

Open science also demands making one’s contributions available to the research community as quickly as possible so that discoveries and contributions make an impact without delay. Since 2016, the vast majority articles we have published were first posted on biorxiv.

Open sharing of data and code.

Scientific reproducibility is maximized not by delayed sharing through personal request, but rather when the data and analysis code used in a manuscript is made easily available. We strive to make our findings transparent and accessible on open-source frameworks such as Github. A salient example of our efforts is our 2019 study titled Large, three-generation human families reveal post-zygotic mosaicism and variability in germline mutation accumulation. This manuscript was published in eLife where reviews are open to others, and we made the underlying data and software available on both Github, and an interactive data analysis notebook.

Sharing knowledge.

We also strive to share teaching materials openly on Github (e.g., here and here) and Youtube, where scientists from all over the world can access them and use them for their own purposes without obligation.