Differential Methylation Analysis with the MethylKit BaseSpace Labs App
In May 2015, Illumina introduced the MethylSeq 1.0 BaseSpace app for performing analysis on bisulfite sequencing data. Now we are happy to announce release of the MethylKit BaseSpace Labs app (https://basespace.illumina.com/apps/1550550/MethylKit), which is focused on differential methylation analysis on two groups of bisulfite sequencing samples. This BaseSpace Labs app is based on the MethylKit R package, published in 2012 in Genome Biology (http://www.genomebiology.com/2012/13/10/r87). The MethylKit app includes these features:
- Coverage Stats Plot for each sample
- Methylation Stats Plot for each sample
- Methylation Correlation Plot
- Differential Methylation Summary Table (Per Chromosome)
- Differential Methylation Regions (in csv file and bigwig file)
- Methylation Stats Summary
- Methylation Stats Percentile Information
Notably, the BaseSpace implementation of MethylKit (but not the R package) outputs a differential methylation bigwig file for visualization in genome browsers such as the Broad’s IGV. The screenshots below show some outputs from the MethylKit app for two Projects. One is a comparison of NA12878 WGBS data from ENCODE vs some Illumina-generated NextSeq 500 v2 data. This data shows very small differential methylation because each sample is from the same reference genome, but it may be useful for technology & software comparisons. The second data set is from WGBS for HCC1187 tumor/normal samples prepped using Illumina’s TruSeq DNA Methylation prep kit. This data shows a large difference in global and site-specific methylation levels because it is a comparison of tumor cells vs healthy tissue.
The screenshots shown above are from two new demo projects posted to the BaseSpace Public Data Projects listed below.
The IGV screenshots from the HCC1187 tumor/normal data show a couple of interesting views of epigenetic changes that can occur in many cancers. The chromosome 7 differential methylation bigwig track suggests possible long range epigenetic silencing and activation events, while a zoomed in look at the EGFR oncogene shows a large hypomethylated region for the tumor cell line vs the blood derived normal.
NextSeq 500 v2: TruSeq DNA Methylation (NA12878)
HiSeq 2500 v4: TruSeq DNA Methylation (HCC1187 Tumor/Normal)
We hope you find the MethylKit app useful. Questions can be directed to email@example.com.
Note: HCC cell lines were invented by Drs. Adi F. Gazdar and John D. Minna at the University of Texas Southwestern Medical Center. Rights in and to the HCC cell lines, progeny, and unmodified derivates thereof belong to the Board of Regents of The University of Texas System. Illumina, Inc. has obtained permission from the Board of Regents of The University of Texas System through the University of Texas Southwestern Medical Center to use the HCC cell lines and publish the data and results herein displayed.