Beta-matrix - Differential methylation analysis
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Dave Emir • 0
@dave-emir-15488
Last seen 3.1 years ago
Behrain

Hello All,

I am a Biologist and have very less exposure to coding. My problem is, I have  300 samples beta matrix file of LUSC, which I have downloaded from TCGA. I have to run a Differential methylation Analysis on this data. I tried my best to work with ChAMP R package but I couldn't get it working. Currently, I have only beta matrix file and I don't have idat file as well.

Can you guys please let me know how to run the DMR analysis using ChAMP on beta-Matrix file? It would be really great if you can share codes.

Sorry for bothering, but I would be really happy if I can successfully run DMR on my matrix file.

Dave.

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Yuan Tian ▴ 220
@yuan-tian-13904
Last seen 3 months ago
University College London

Hello Dave:

One of the feature for ChAMP is supporting beta-matrix for analysis instead of IDAT data. Because nearly all function in ChAMP are require pure matrix or data frame as input (parameter "beta" in functions). You just need to organize your data into a matrix or dataframe format, then put it into ChAMP.

Based on your question, I think you already have beta matrix, but not sure if you currently have "file" or have been organized into matrix format in R session. Also, you did not mention if you have PD file, which means phenotypes for each sample. I have analysed LUSC data I remember, you should be able to find PD information from above.

After your collecting beta matrix and PD file, you can use champ.DMP(), champ.DMR() functions for analysis. (By the way, what is DME?)

myDMP <- champ.DMP(beta=your_beta_matrix, pd=your_phenotype, arraytype="450K")

Then it should work. If you have any questions, you may post here or email me (ChAMP developer).

Best

Yuan Tian

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Hi Yuan,

Thanks a lot for the prompt reply, I will be grateful for your kind help.
Sorry for the DMA here, it was supposed to be DMR analysis.
I have downloaded the data from GDC Portal (TCGA) and my main aim is to perform a DMR (different methylated region) analysis, which will give the difference of DNA methylation for the probes of the groups and their significance value. I have used the following code from TCGAbiolinks to download the data.

query.met <- GDCquery(project = "TCGA-LUSC", data.category = "DNA Methylation",platform = "Illumina Human Methylation 450", barcode = c("TCGA-34-5231-01A-21D-1818-05","TCGA-77-7138-01A-41D-2043-05"))

met <- GDCprepare(query = query.met,save = TRUE,  save.filename = "DNAmethylation_LUSC.rda", summarizedExperiment = TRUE)

I have two groups of samples like set A samples (~100)--> tumor A and Set B samples (~30) --> tumor B. I wanted to get the DMR for this two categories.
the phenotypic file looks like with column 1 listing the samples and column 2 listing if it belongs to SETA or SETB. (Example PD file as follows)

Samples type
TCGA-34-5231-01A-21D-1815-0 SETA
TCGA-34-5231-01A-21D-1816-0 SETB
TCGA-34-5231-01A-21D-1814-0 SETA

Hope its bit clear to you, I am interested in running ChAMP on it. Can I use the same set of codes as defined in the "The Chip Analysis Methylation Pipeline" Or if you can help me in this? it would be of great help.

Sorry for the inconvenience.
Thanks a lot for helping me,

Regards,
Dave