ChIP-seq analysis notes from Ming Tang
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Updated
Aug 5, 2024 - Python
ChIP-seq analysis notes from Ming Tang
MACS -- Model-based Analysis of ChIP-Seq
Automated and customizable preprocessing of Next-Generation Sequencing data, including full (sc)ATAC-seq, ChIP-seq, and (sc)RNA-seq workflows. Works equally easy with public as local data.
Publication quality NGS track plotting
Regulatory Genomics Toolbox: Python library and set of tools for the integrative analysis of high throughput regulatory genomics data.
A Snakemake workflow and MrBiomics module for performing genomic region set and gene set enrichment analyses using LOLA, GREAT, GSEApy, pycisTarget and RcisTarget.
(DEPRECATED) epic: diffuse domain ChIP-Seq caller based on SICER
Transcription Factor Binding Prediction from ATAC-seq and scATAC-seq with Deep Neural Networks
A robust model for quantitative comparison of ChIP-Seq data sets.
A Python package for fast operations on 1-dimensional genomic signal tracks
Pipelines for NGS data preprocessing by the Bock lab and friends
The ChIP-Seq peak calling algorithm using convolution neural networks
Pipeline to analyse ChIP-Rx data, i.e ChIP-Seq with reference exogenous genome spike-in normalization
A toolkit for NGS analysis with Python
To pre-process a set of ChIP-seq samples and coordinate with MAnorm2 for differential analysis
Sargasso disambiguates mixed-species high-throughput sequencing data.
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