This repository for the MeDIP-seq data analysis workflow in R. This workflow built on the QSEA package and can analyze DNA methylation at gene levels.
- The prepare_samples folfer contain the bash script to prepare the data (from raw .fastq file) before doing the QSEA analysis in R
- The QSEA_Rcode_in_server and QSEA_Rcode_server_2021Jan18 are the R script to run QSEA analysis.
- The data folder stores all the needed data information and output after the QSEA analysis.
- The R_code_forACM, R_code_forFrontier, and R_code_forFrontier_RNAseq are the R script to run the downstream analysis for the publications in ACM and Frontiers in Bioscience - Landmark journal, respectively.
- The outcome_ACM and outcome_Frontiers folders store all the outcome for the publications in ACM and Frontiers in Bioscience - Landmark journal, respectively.
Other files:
- R_functions - store all the functions that are used in other R scripts
- anotation_NN_2020Nov16 - script to prepare the annotation files
Nhan Nguyen, Matthias Lienhard, Ralf Herwig, Jos Kleinjans, and Danyel Jennen. “Epirubicin alters DNA methylation profiles related to cardiotoxicity”. Frontiers in Bioscience - Landmark (2022, in press).
Nhan Nguyen, Matthias Lienhard, Ralf Herwig, Jos Kleinjans, and Danyel Jennen. “A bioinformatics workflow to detect genes with DNA methylation alterations: a case study of analyzing MeDIP-seq data in cardiac microtissue exposed to epirubicin”. International Conference Proceedings by ACM (2022). https://doi.org/10.1145/3510427.3510437
LinkedIn: nhannguyen | ORCID: 0000-0001-8720-1195