macs2

ChIP-seq peak-calling, QC and differential analysis pipeline.

ATAC-seq processing pipeline

ChIP-seq analysis pipeline

Multiple-replica multiple-condition ChIPSeq pipeline

Benchmarking ChIP-seq peak callers

DISMISS is an R script, which as an additional step in MeDIP-Seq data analysis workflow, enables the allocation of strands to methylated DNA regions. It does this by analyzing the proportions of first mate reads aligning to the methylated locus from the plus and minus strands.

Reproducible ChIP-seq analysis pipeline for GSE107221 using Galaxy, ChIPseeker and DiffBind to identify KDM5A-regulated H3K4me3 loci.

docker file for genomic tools

Reproducible Snakemake ChIP-seq pipeline: Bowtie2 → MACS2 (narrow/broad, input/IgG control) → IDR & consensus peaks → ENCODE-grade QC → differential binding, peak annotation & motif enrichment. Containerized (Docker/Apptainer)

CCBR pipeline for preliminary QC, peak calling, differential chromatin accessibility analysis with ATACseq datasets 🌲

End-to-end Snakemake ATAC-seq pipeline (spike-in-free): Bowtie2 → MACS2 → reproducible fixed-width consensus peaks + a self-contained interactive QC report, plus opt-in CTCF-anchored differential openness (DESeq2) and TF footprinting (TOBIAS). Fully containerized (Docker/Apptainer).

Analysis of Existing ChIP-seq data to identify NANOG and SOX2 binding targets

This project explores the PBRM1-PIAS1 interaction in epithelial differentiation through ChIP-seq analysis, highlighting EZH2's role and implications for cholesterol biosynthesis in cellular processes.

Snakemake Pipeline for the Analyses of ChIP-seq data in Cancer samples

Dockerized MACS2

Peak calling optimization via real time results assessment and interactive parameter adjustment.

A simple nextflow pipeline for calling peaks and producing tracks from ChIP-seq data

A pipeline to call intron and intergenic eRNAs from PRO-seq Data

Snakemake workflow used to call peaks with Macs2

Comparative ATAC-seq analysis of Alzheimer's Disease and Medulloblastoma microglia using BWA, SAMtools, MACS2, DiffBind, BEDTools, and HOMER to identify shared chromatin accessibility patterns.