Data for the paper Ravichandran et al., Pronounced sequence specificity of the TET enzyme catalytic domain guides its cellular function

This repository contains the scripts and datasets for the paper Pronounced sequence specificity guides cellular function of TET enzymes, Ravichandran et al. Components of the analysis Scripts Python script to quantitate methylation by hexamer (call_hexamers.py). Python script to sort methylation according to CGI location (classify_CGI.py). Python script to merge results and obtain summary tables (summarize.py). R Script to perform the Intra-motif positional preference analysis and plot the results in R (IMPP_analysis.R). R Scripts to determine sequence logos using linear regression for logarithmic rates (seqlogo_NgTET_weighted_in_vitro.html, seqlogo_mTET[1-3]_weighted_in_vitro.Rmd, seqlogo_TET-TKO-TET3-expression.Rmd). Datasets CpG Illingworth bed file converted to GRCm38 (CpG_Il_mm10.bed). Demethylation velocity table (Slope_summary.txt). Last update: 12:57 26/01/2021 EST