Predicting Tissue Specific Enhancer Activity from Epigenetic Marks and Sequence
-
Updated
Dec 3, 2014 - Python
Predicting Tissue Specific Enhancer Activity from Epigenetic Marks and Sequence
DISMISS is an R script, which as an additional step in MeDIP-Seq data analysis workflow, enables the allocation of strands to methylated DNA regions. It does this by analyzing the proportions of first mate reads aligning to the methylated locus from the plus and minus strands.
Anlysis of small RNAs in Arabidopsis SWR1 mutant (published in Choi et al. 2016, Plant Physiology, http://www.plantphysiol.org/content/171/2/1128)
Predicting gene expression using epigenomics data and deep learning
Calculate DNA methylation age using Horvath 2013 method
Sample Analysis for diffloop paper
Python code to control my physical model of an Epigenetic Landscape.
generates reference matrix of average beta methylation values
R codes of the figures from the Epigenetics CSMD1 paper
Histone Modification Interpreter
Produces coverage and methylation percentage data from FASTQ files.
Analysis scripts for the Vertesy 2018 paper: "Parental haplotype specific single-cell transcriptomics reveal incomplete epigenetic reprogramming in human female germ cells"
Computational methods for our manuscript in 5fC and nucleosomal organization
EpiMethEx (Epigenetic Methylation and Expression), a R package to perform a large-scale integrated analysis by cyclic correlation analyses between methylation and gene expression data.
Guide for the Baccarelli Lab GitHub
Add a description, image, and links to the epigenetics topic page so that developers can more easily learn about it.
To associate your repository with the epigenetics topic, visit your repo's landing page and select "manage topics."