Here are some links to code and protocols that we routinely use, as well as several documents on lab policy.
We believe in openly sharing our analyses and data. Here’s our GitHub repo. We release the data and analysis associated with our publications, usually as a series of Jupyter notebooks (see Publications for specific links).
PySCA, a python (v 2.7) implementation of the statistical coupling analysis: [github]
Python workshop for Scientific Computing:
Programming and data science are key elements of modern biological research. To encourage young scientists to get started early with coding, Kim collaborated with a team of UTSW graduate students to develop a Python workshop for high school students. It will be offered through the UTSW STARS summer research program for the first time in Summer 2022.
Continuous culture of bacteria:
We often use continuous culture for our evolution and deep mutational scanning experiments. Recently, we’ve been trying out the eVOLVER platform for this, alongside our own home-built models. Here is our (also evolving) lab eVOLVER wiki.
The Reynolds lab strives to provide a supportive and intellectually rigorous environment for doing science. Below are a few important documents on lab policy and culture.