MACS -- Model-based Analysis of ChIP-Seq
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Updated
Nov 30, 2024 - Python
MACS -- Model-based Analysis of ChIP-Seq
ATAC-seq and DNase-seq processing pipeline
chromatin Variability Across Regions (of the genome!)
Regulatory Genomics Toolbox: Python library and set of tools for the integrative analysis of high throughput regulatory genomics data.
PECA is a software for inferring context specific gene regulatory network from paired gene expression and chromatin accessibility data
deepStats: a stastitical toolbox for deeptools and genomic signals
Big data Regression for predicting DNase I hypersensitivity
🐛 How to use CENTIPEDE to determine if a transcription factor is bound.
Pipeline for predicting ChIP-seq peaks in novel cell types using chromatin accessibility
Improving the feature density based peak caller with dynamic statistics
PECA is a software for inferring context specific gene regulatory network from paired gene expression and chromatin accessibility data
A robust statistical test for TF footprint data analyses
This repository contains the prebuilt models for BIRD.
A dataset for big data prediction.
Scripts to run footprinting and motif-flanking accessibility analysis in DNase-seq/ ATAC-seq data
Codes for data processing and figure generation
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