A dataset for big data prediction.
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Updated
Jul 18, 2019
A dataset for big data prediction.
Codes for data processing and figure generation
Scripts to run footprinting and motif-flanking accessibility analysis in DNase-seq/ ATAC-seq data
PECA is a software for inferring context specific gene regulatory network from paired gene expression and chromatin accessibility data
Improving the feature density based peak caller with dynamic statistics
This repository contains the prebuilt models for BIRD.
A robust statistical test for TF footprint data analyses
deepStats: a stastitical toolbox for deeptools and genomic signals
Pipeline for predicting ChIP-seq peaks in novel cell types using chromatin accessibility
Big data Regression for predicting DNase I hypersensitivity
PECA is a software for inferring context specific gene regulatory network from paired gene expression and chromatin accessibility data
🐛 How to use CENTIPEDE to determine if a transcription factor is bound.
Regulatory Genomics Toolbox: Python library and set of tools for the integrative analysis of high throughput regulatory genomics data.
chromatin Variability Across Regions (of the genome!)
ATAC-seq and DNase-seq processing pipeline
MACS -- Model-based Analysis of ChIP-Seq
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