During my masters thesis project I worked with a single-nuclei ATAC-sequencing dataset in order to better understand the chromatin dynamics of mouse brain behavior in response to spaceflight experiment. A multiomic dataset was available with both RNA-seq and ATAC-seq from the same nuclei. In order to better leverage what was happening, I needed a performant tool which focused on ATAC data but which could also incorporate RNA-seq. I used ArchR which is one of the most updated and performant R-based tool for single-cell ATAC-seq analysis. I don't intend to sell the software but however recommend to read the documentation before use.
The investigation focused on analyzing the behavior of the mouse brain in the context of spaceflight. Notably, intriguing changes resembling neurodegenerative alterations were observed.
The finalized Quarto script utilized for generating the presented results can be accessed in the archr_multi folder under doc > archr_multi > archr_multiome.qmd.
The exact same code is available as R script if necessary.
Reproducibility of the analysis necessitates a specific version of ggplot2 (version 3.3.6) within the ArchR framework as well as a Python tool, MACS2, which may be inconvenient for some users. To address this concern, a Singularity container is provided on the corresponding GitHub page, accompanied by basic instructions on employing Singularity, accessible here.
The written report detailing the findings of this study is available on KTH-DiVA.