- Introduction: Quick Start, Tutorial, Flowchart, Outputs structure
- Install: Dependencies, Containers, References, Test datasets
- Inputs: Data, Design, Parameters
- 1. Preprocessing: ATAC reads, ATAC peaks, mRNA
- 2. Differential Analysis: ATAC, mRNA, Split
- 3. Enrichment Analysis: Enrichment, Figures, Tables
- Preprocessing:
- ATAC-Seq: Reads are merged, trimmed and aligned to the genome with bowtie2. Aligned reads are filtered (low quality, duplicates, mitochondrial, small contigs) and shifted (to account for the 9 bp offset of the transposase). Narrow peaks are then called using MACS2. These are further split, filtered (blacklist, gDNA) and annotated with ChIPseeker.
- mRNA-Seq: Transcripts are quantified using Kallisto.
-
Differential Analysis (DA): DA refers to both differentially accessibility analysis done with DiffBind and to differential gene expression analysis done with Sleuth. Standardized plots (Volcano and PCA) and tables are produced. DA results are then split in subsets (which are called DASs for Differential Analysis Subsets) by experiment type (ATAC, mRNA or both), significance/rank threshold, direction of fold change (up or down), and DAR (Differentially Accessible Region) peak annotation (such as promoter, gene body, distal non coding, ...). Tables and Venn Diagrams are made for each subset. For both ATAC-Seq and mRNA-Seq: genes (DARs' closest genes and DA genes) and genomic regions (DARs and DA genes’ promoters) are exported.
-
Enrichment analysis: Genes are used for ontologies and pathway enrichment analysis. Genomic regions are used for chromatin state, motifs and CHIP enrichment analysis. Additionally, enrichment of internal entries (i.e., between DASs) is performed. Results are saved as tables, and displayed as barplots and heatmaps.