Predicting Tissue Specific Enhancer Activity from Epigenetic Marks and Sequence
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Updated
Dec 3, 2014 - Python
Predicting Tissue Specific Enhancer Activity from Epigenetic Marks and Sequence
The documented analysis of the results reported in Akol et al., 2023 as R markdowns, Galaxy histories and jupyter logs..
Computational methods for our manuscript in 5fC and nucleosomal organization
Github Page for the Baccarelli Lab
Code for "Comprehensive computational analysis of epigenetic descriptors affecting CRISPR-Cas9 off-target activity"
Supplemental codes for the Chapter 14 Chromatin Sequencing and Data Analysis of the NYMU-GRC eBook 基因體技術與資料分析手冊
A collection of simple scripts to facilitate the setup of everyday epigenetics experiments and to handle genomic methylation data
Code for SCLC cfMeDIP-seq PRIME as described in the following paper: doi: 10.1016/j.isci.2022.105487
Snakemake workflow for processing small RNA-seq libaries
Machine learning models of conserved regulatory elements and human genetics of neuropsychiatric traits
CutNtag pipeline for Pasini's lab written in snakemake
Code for the crb2a multi omics manuscript
A machine learning tool that uses DNA sequence and epigenetic data to enhance recombination hotspot predictions.
This pipeline is designed for the analysis of DNA methylation data generated from the Illumina HumanMethylation450 BeadChip platform.
ChIP-seq pipeline specific for the Zwart lab
Python code to control my physical model of an Epigenetic Landscape.
Code and data to build and use Cis-Regulatory Hubs.
Poster presentation at the (American Society of Human Genetics) ASHG Virtual Meeting, 2021.
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