single cell Cut&Tag in the mouse brain

Marek Bartosovic

Goncalo Castelo-Branco lab

This repo contains code needed to generate figures for the paper

https://www.biorxiv.org/content/10.1101/2020.09.02.279703v1

The code is under development

The analysis is performed in two steps:

1. Fastq files are processed using standard cellranger-atac count
2. Snakemake pipeline contains scripts and R markdown notebooks used for merging of the samples, analysis and figure generation

Step 1.

Each sequencing run is processed separately with cellranger:

cellranger-atac count --fastqs=./fastq/ --reference=PATH_TO_CELLRANGER_REFERENCE_MM10 --sample=SEQUNCING_ID --id=SAMPLE_ID

Step 2.

Prepare

cd into folder where you want to do the analyis

mkdir scCut-Tag_2020
cd scCut-Tag_2020

Clone the git repo

git clone https://github.com/Castelo-Branco-lab/scCut-Tag_2020/master

Create conda environment with all necessary tools installed by:

conda env create -f scCut-Tag_2020/envs/CT_snakemake.yaml
conda env create -f scCut-Tag_2020/envs/meme.yaml

Install extra R libraries that are not present in conda or have trouble working:

TODO 

Modify config files

Modify config files in scCut-Tag_2020/config/step2/ to specify path to cellranger output files for individual samples

Run Snakemake

snakemake --cores 56 -p

We also provide an IGV server with bw tracks for all modifications and cell types

Change the URL to IGV server in IGV preferences

IGV -> View -> Preferences -> Advanced -> Data registry url

Change the URL to:

https://raw.githubusercontent.com/mardzix/IGV_track_server/master/registry/IGV_registry.txt

Then, just go to File -> Load from server

Enjoy!