While working on a genomics project that utilized Python tools from Bioconda, I upgraded to an M1 Mac laptop.  Unfortunately, due to the unique architecture of the CPU, this broke some of the Python modules I was utilizing in my work (and Rosetta, while great, didn't fix the issue).  In order to finally get things working, I generated a Linux-based Docker image with Bioconda and the libraries I needed, and then forwarded a Jupyter Notebook to the base OS to run in a browser.  Thus I was able to get everything running again. Code and explanation on GitHub: https://github.com/CompBioLevings/M1_Docker_bioconda

These are a set of Jupyter Notebooks I put on GitHub for downloading and plotting mouse brain cell type-aggregated scRNA-seq and snATAC-seq results for an example gene & region.  

snATAC-seq data from CATlas: http://catlas.org/mousebrain/

scRNA-seq data from Mouse Brain Atlas: http://mousebrain.org/

The code used to create these plots are available at: https://github.com/CompBioLevings/snATAC-and-scRNA-seq-plots and https://github.com/levin252/NRF2_brain_single-cell-analysis

I built an R Shiny application for my lab to browse an RNA-seq dataset comparing how gene expression changes during a time course of the acute response to two oxidative stress-inducing compounds, menadione (MEN) and tert-Butyl hydroperoxide (tBOOH), versus controls (ethanol, EtOH, or the untreated time 0 sample).

URL address to use application available upon request (on shinyapps.io).

The code used to create this application is available at: https://github.com/CompBioLevings/MCF7-ROS-RNAseq

This is an RMarkdown script I created that will auto-download data from multiple sources, do some calculations and generate plots showing the COVID19 trends both nation-wide and for local states/counties over the past two weeks. Specifically, it generates maps showing COVID death and case rates for the United States and for MN and WI, and dot plots with trendlines showing how COVID case rates are changing locally. This is all output to an HTML file for easy viewing. 

RMD script/code is available for modification and use on Github at: https://github.com/CompBioLevings/COVID19_local_maps_trends