Project name : DNA methylation analysis for Bipolar

Project time : 2019.09.07 - 2019.11.02

Description :

• The project was conducted as part of "RISE (Research Intensive Self-motivated Education)" class in the Molecular Life Sciences at Incheon National University, Korea.
• The purpose of this project is to learn how to analyze DNA methylation datasets using the "ChAMP" R package.
• According to this project, I want to understand which genes exhibit differential methylation at CpG sites between the control and bipolar groups.
• It mainly deals with steps below.
  1. Quality control (QC) & Preprocessing
  2. Differentially methylation analysis
  3. Gene Set Enrichment analysis (GSEA)
  4. estimate Copy number variation (CNA)

Dataset information

• Infinium MethylationEPIC array chip (850K) platform
• Post-mortem hippocampus tissue
• the number of control group is 32 samples
• the number of bipolar group is 32 samples
• IDAT format. (GSE129428, Download from GEO database)

We uploaded these files:

• ChAMP_analysis.R : DNA methylation analysis code using ChAMP R package.
• GSE129428_pd.csv : Metadata (Phenotype, Age, Smoke status, BMI and so on.)
• GSEA_result.csv : GSEA result
• CNA : CNA analysis result
• Normalization : QC results after normalization (MDS plot, Hirechical Cluster, Density plot)
• SVD_analysis : SVD analysis result (check batch effect)
• Annotation.py : Python script that proceeds with gene annotation based on estimated CNV information.

Important !!!

1. Metadata and IDAT files are in the same directory.
2. Check the Slide columns in Metadata. (ex) Slide : 202816900054, Basenames : GSM3712754_202816900054_R01C01