A collection of scripts for analyzing data obtained from single-cell Targeted Analysis of the Methylome (scTAM-seq)

manuscript

The collection of R scripts needed to re-generate the plots that we already generated for the manuscript. The scripts are ordered by the Figure/panel they are needed for.

If you want to re-generate all of the plots of the publication, you'll have to download several datasets and put them into the base folder of this repository (called scTAM-seq-scripts):

• The count matrices from GEO (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE198019). They should be extracted into a folder called data in the base directory of this repository.
• The CITE-seq reference dataset from: https://figshare.com/ndownloader/files/28408917
• The reference bulk DNAm data from: https://figshare.com/account/projects/134468/articles/19323623. This data should also be placed into the data folder.

In addition, you'll have to install the following R-packages

• RnBeads: (source('https://rnbeads.org/data/install.R'))
• Seurat: (BiocManager::install('Seurat'))
• Signac: (install.packages('Signac'))
• monocle3: (install.packages('monocle3'))
• SeuratWrappers:(devtools::install_github('satijalab/seurat-wrappers'))
• viridis: (install.packages('viridis'))
• ComplexHeatmap: (BiocManager::install('ComplexHeatmap'))
• ggsci: (install.packages('ggsci'))
• rstan: (install.packages('rstan'))

tapestri

This contains the re-implementation of the Mission Bio tapestri pipeline to generate all of the files needed for downstream processing.

Citation

If you use this software in your publication, please cite:

Bianchi, A., Scherer, M., Zaurin, R. et al. scTAM-seq enables targeted high-confidence analysis of DNA methylation in single cells. Genome Biol 23, 229 (2022). https://doi.org/10.1186/s13059-022-02796-7