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

Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)

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Title Data for the paper Ravichandran et al., Pronounced sequence specificity of the TET enzyme catalytic domain guides its cellular function
 
Identifier https://doi.org/10.7910/DVN/UTMEWY
 
Creator Ravichandran, Mirunalini
Rafalski, Dominik
Davies, Claudia I.
Ortega-Recalde, O.
Nan, Xinsheng
Glanfield, Cassandra R.
Kotter, Annika
Misztal, Katarzyna
Wang, Andrew H.
Wojciechowski, Marek
Rażew, Michał
Mayyas, Issam M.
Kardailsky, Olga
Schwarz, Uwe
Zembrzycki, Krzysztof
Morison, Ian M.
Helm, Mark
Weichenhan, Dieter
Jurkowska, Renata Z.
Krueger, Felix
Plass, Christoph
Zacharias, Martin
Bochtler, Matthias
Hore, Timothy A.
Jurkowski, Tomasz P.
 
Publisher Harvard Dataverse
 
Description 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
 
Subject Medicine, Health and Life Sciences
Epigenomics
 
Contributor Bochtler, Matthias