ChIP-seq analysis notes from Ming Tang

The official code implementation for Chromoformer in PyTorch. (Lee et al., Nature Communications. 2022)

🧬 🦀 A fast and efficient tool to perform a genome wide Single cell Chromatin State Analysis using multimodal histone modification data.

Pipeline for predicting ChIP-seq peaks in novel cell types using chromatin accessibility

A unified framework for discovering, analyzing, integrating, and visualizing regulatory motifs and transcription factor binding sites across bulk, single-cell, and long-read sequencing modalities.

geneSpark is a bioinformatics software program written in Python and Apache Spark for big data epigenetic histone modification ChIP-seq analysis.

This is a R package that intends to perform all the features possible by tensor decomposition based unsupervised feature extraction

Cell type-specific Histone Acetylation Score

Processing, benchmarking and analysis of CUT&Tag against ENCODE ChIP-seq.

Using CNNs to model affect of histone modification on gene expression

geneXtendeR analysis on 198 human histone modification ChIP-seq ENCODE datasets

Usage analysis of histone post-translational modifications using msqrob2PTM

This is the fork of the Bioconductor-mirror repository. Package Homepage: http://bioconductor.org/packages/devel/bioc/html/chipenrich.html Bug Reports: https://support.bioconductor.org/p/new/post/?tag_val=chipenrich.

Practical and home works in the discipline Bioinformatics.

The abstract and poster for my internship under the Stanford Institutes of Medical Research at the Khatri Lab in the summer of 2019. More code/scripts can be made available upon request (I used primarily R and SQL)

Preprocessing pipeline for CUT&TAG data.

In this module, you will learn how to perform the bioinformatics analysis of differential chromatin occupancy using data generated by three well-known high-throughput sequencing assaying, including differences between them and integration of chromatin accessibility and differential gene expression

Gene expression prediction with Convolutional Recurrent Neural Networks

ChIP-seq normalization according to background reads density. (R package)

my master's research in bioinformatics