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mardzix / bcd_nano_CUTnTag

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Multimodal chromatin profiling using nanobody-based single-cell CUT&Tag

Marek Bartosovic, Goncalo Castelo-Branco

Code repository related to publication

Bartosovic, M., Castelo-Branco, G. Multimodal chromatin profiling using nanobody-based single-cell CUT&Tag. Nat Biotechnol 41, 794–805 (2023). https://doi.org/10.1038/s41587-022-01535-4

and preprint

Multimodal chromatin profiling using nanobody-based single-cell CUT&Tag Marek Bartosovic, Gonçalo Castelo-Branco bioRxiv 2022.03.08.483459; doi: https://doi.org/10.1101/2022.03.08.483459

Pipeline

Standalone pipeline to analyse single-cell nano-CT data is available at: https://github.com/bartosovic-lab/nanoscope

Data availability

Processed files - Seurat objects, fragments file (cellranger), bigwig tracks per cluster and .h5 matrices are available as supplementary files in the GEO repository https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE198467

Reproducing the analysis

Step 1: prepare environment

conda environment is provided in env/environment.yaml

conda env create -f env/environment.yaml

Additional package dependencies that need to be installed:

R
install.packages(c('argparse','ggplot2','funr','Signac','scales','Seurat','rmarkdown','mclust','GGally','BiocManager','patchwork','markdown','UpSetR','pheatmap','viridis','purrr','Rmagic','devtools','raster'))
BiocManager::install(c('ensembldb','EnsDb.Mmusculus.v79','GenomeInfoDb', 'GenomicRanges', 'IRanges', 'Rsamtools','BiocGenerics','rtracklayer','limma','slingshot','BiocGenerics', 'DelayedArray', 'DelayedMatrixStats','limma', 'S4Vectors', 'SingleCellExperiment','SummarizedExperiment', 'batchelor', 'Matrix.utils')))

Have seqtk installed in $PATH

https://github.com/lh3/seqtk

Install papermill for cli for jupyter notebooks

python3 -m pip install papermill

Step 2: Download the data

use fasterq-dump or alternative to download the fastq files

https://github.com/ncbi/sra-tools/wiki/HowTo:-fasterq-dump

GEO repository

https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE198467

Step 3: Clone the github repo with analysis code

git clone https://github.com/mardzix/bcd_nano_CUTnTag

Step 4: Modify config

Change config/config.yaml and specify path to

  1. Absolute path to fastq files
  2. Specific path to the tmp folder (Create any folder, e.g. in home)
  3. Specify conda environment to use
  4. Modify path to cellranger reference

Step 5: Run the pipeline

Pipeline is implemented in workflow management software Snakemake

Change the cluster-specific profile to your preference (e.g. slurm, condor etc.), or run without profile

For some example profiles see:

Johannes Köster, Sven Rahmann, Snakemake—a scalable bioinformatics workflow engine, Bioinformatics, Volume 28, Issue 19, 1 October 2012, Pages 2520–2522, https://doi.org/10.1093/bioinformatics/bts480

Snakemake