ChromSCape

What is ChromSCape ?

ChromSCape - Chromatin landscape profiling for Single Cells - is a ready-to-launch user-friendly Shiny Application for the analysis of single-cell epigenomics datasets (scChIP-seq, scATAC-seq, scCUT&Tag, ...) from aligned data to differential analysis & gene set enrichment analysis. It is highly interactive, enables users to save their analysis and covers a wide range of analytical steps: QC, preprocessing, filtering, batch correction, dimensionality reduction, vizualisation, clustering, differential analysis and gene set analysis.

Prompsy, P., Kirchmeier, P., Marsolier, J. et al. Interactive analysis of single-cell epigenomic landscapes with ChromSCape.
Nat Commun 11, 5702 (2020).

Launching ChromSCape

ChromSCape requires R version 4.02. To install ChromSCape, open R or Rstudio and run the following commands :

``` if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager")

BiocManager::install("ChromSCape") ```

Once the installation was sucessful, launch ChromSCape using the following command :

library(ChromSCape) launchApp()

It is recommended to use Chrome browser for optimal display of graphics & table. If no browser opens, copy the url after 'Listening on ...' and paste in your browser.

Demo

Checkout the application look & feel at : Demo. On this demo application, you can follow analysis of Jurkat & Ramos scChIP H3K4me3 cells.

User guide

Take a look at the user guide before starting: User guide

Test datasets

ChromSCape takes as input one tab-separated count matrice (in .tsv or .txt) per sample. In order to upload multiple matrices, the matrices should be placed in the same folder of your computer. Before you input your own matrices, it is recommended you try playing around and familiarize with ChromSCape by downloading our example matrices and uploading them in ChromSCape :

Try out ChromSCape with various kind of dataset : Dropbox repository

Run Time

On a Intel® Core™ i5-6500 CPU @ 3.20GHz × 4 with 31,3 Gio RAM, the installation took less than one hour. The running time of of scChIP_H3K27me3 test dataset was 25 minutes without peak calling and 35 minutes with peak calling.

Input

The matrix format should be tab-separated file, with Cells as column & Features as rows. The first line should be cell names, the first column should be feature names. Feature names can be either genomic coordinate in the format 'chr:start-end' or 'chrstartend' or gene symbols (e.g: A1BG, A1BG-AS1 for hg38 or Rab23, Bag2 for mm10).

Output

The app automatically creates a directory Chromscape_analysis in which a new directory is created for each analysis with a different input name. Inside that directory are created a directory for each part of the analysis, containing RData and figures.

Other

The Gene Set Enrichment Analysis is based on MSIG database (http://software.broadinstitute.org/gsea/msigdb).

Advanced requirements for optional Peak Calling step

The peak calling step is important for Gene Set Enrichment Analysis particularly for features defined as genomic bins >= 20kbp or broad peaks. It will aggregate signal of cells in each cluster ('in-silico cell sorting') and call peaks separately for each cluster using MACS2 peak caller. Then the annotation of genes to bins is refined and genes TSS not falling closer to 1000bp of any peaks are removed from annotation. This exclude any 'false' association of large genomic bins/regions to genes.
This step requires BAM files of each sample (one BAM file must contains reads of all cells of a given sample) as input. The user should be on a Unix system (Mac, Linux) and have installed MACS2:

macs2 2.1.2 (https://github.com/taoliu/MACS) The application will automatically check if these tools are available and will give you a warning if they are not installed/available.

Note for Windows users

Windows user are not able to run the peak calling step, as both and macs2 are not yet available on windows.
Therefore, if users want to run peak calling, they can use the docker version.

Docker

A docker image with all dependencies is available at DockerHub. To run the docker image and launch ChromSCape, run : sudo docker run --rm -p 4747:4747 -v ~/ChromSCape_analyses_docker:/root/output/ -t pacomito/chromscape:v0.0.9001 Explanation:

• sudo run with admin rights, a password will be asked
• docker run -t pacomito/chromscape:v0.0.9001 download and run the image
• --rm supress container when run ends
• -p 4747:4747 expose docker port 4747 to localhost:4747
• -v ~/ChromSCape_analyses_docker:/root/output/ output folder where ChromSCapeanalyses folder will be created is linked to the container '/root/' folder. Change '~/ChromSCapeanalyses_docker' to your preferred output path

Optionally, if you want to input BAM, BED of Peak-Index-Barcode files, add another -v option from your local machine directory to the docker container: -v ~/file_inputs:/root/input After the downloading of the image and the loading of ChromSCape, navigate to : http://127.0.0.1:4747

You can change the port number if it is already taken, e.g. port = 5858, by changing the -p option and adding '5858' as final argument : sudo docker run --rm -p 4747:4747 -v ~/ChromSCape_analyses_docker:/root/output/ -t pacomito/chromscape:v0.0.9001 5858

MACS2 is installed on the Docker image so this is a way to run the peak calling on Windows.

Authors

Please do not hesitate to post an issue or contact the authors :

Celine Vallot : celine.vallot@curie.fr

Pacome Prompsy : pacome.prompsy@curie.fr