- Please find useful scirpts and codes in folder
bin. - We dissect the analysis into multiple steps, detailed description can be find in corresponding folders.
- This package is still under active development.
This directory contains several necessary steps, including reads mapping, duplicates removal, matrix calculation and generation, quality control, doublets removel, etc.
This directory contains the basic and advanced steps for cell clustering. for small datasets, basic clustering strategy should work. for large/multiple datasets, more steps need to be included.
We shared additional scripts for more detailed analysis, including cell clustering refinement, integration analysis with other modalities (i.e. snRNA-seq);
To correct potential bias due to different depth/number of cells, we optimized peak calling pipeline for snATAC-seq
Clustering of shared and cell-type specific candidate cis-regulatory elements (cCREs) Identification of cell-type/regional specific cCREs
Linkage disequilibrium score regression (LDSR or LDSC) analysis on cis-regulatory elements (cCREs) based on summary statistics from genome-wide association studies (GWASs)
We shared few useful scripts in folder bin/:
- phastCons score calculation in genomic regions;
- script for generating IGV session file, which can be directly load to genome browser
- loomR to seurat object convertor
- loomR to matrix convertor
- script for calculate silhouette score for each cell clustering
Supplementary tables for putative enhancers identified in flagship paper
- python v3.6.8
- R v3.6.0
- Perl v5.26.2
- mouse genome: mm10
- mouse genome annotation: gencode vM16
- mouse blacklist: ENCODE blacklist