This repository accompanies the preprint Liu et al, bioRxiv 2025b.
codeutils: helper functions for motif analysis, ChromBPNet motif clustering, and color palette00-techdev01: comparing OmniATAC and RoboATAC QC metrics from benchmarking datasets02: script to check fraction of reads in peaks
01-preprocessing- Using the SE branch of the snakeATAC preprocessing pipeline
Snakefile.py: snakemake file to process single-ended Ultima reads of RoboATAC libraries
02-atac01: create ChrAccR object, consensus peak calling, read normalization, chromVAR02: dimensionality reduction with PCA03: matching sequences in consensus peaks to JASPAR2020 motifs04: differential peak analysis05: correlating ATAC and RNA differentials06: TF footprinting07: dimensionality reduction with UMAP08: analyze peak type compositions of differential peak sets09: motif scores and motif counts within differential peak sets10: linear and Hill fits of peak dose response to determine peak sensitivity group11: correlating motif scores and motif counts with Hill-fitted parameters12: calling nucleosome position with NucleoATAC13: calculate motif distance to nucleosomes14: in silico marginalization with ChromBPNet models15: ChromBPNet model performance evaluation, multinomial logistic regression models16: hit dose analysis, PWM and pileups of different hit dose sets17: overlap with ENCODE ChIP-seq data18: ChromHMM annotations19: motif pattern distribution in the genome
03-rna00: snakemake pipeline to preprocess RNA data with kallisto01: PCA, differential analysis02: plot average TPMs for overexpressed TFs03: GO term enrichment for differential gene sets
04-chrombpnet- snakemake pipeline to prepare input regions, train ChromBPNet models, interpret models, discovery motifs, and identify hit instances
05-bravo- scripts and device configuration file for running RoboATAC on an Agilent Bravo liquid handling robot (NGS Option B layout)
If you use this data or code, please cite: Liu et al, bioRxiv 2025b.