Hi all,

This question is directed to those who may have experience with the QSEA R package, which proceeds from MEDIPS. 

I have MeDIP-seq data which I hope to begin analyzing very shortly, but unfortunately I'm not too familiar with processing genomic data. I've been able to following the tutorial for QSEA up until the normalization section, which suggests the use of a previously validated dataset. 450k TCGA data from lung is used in this example, and I such I presumed to use Head and Neck for mine. However I'm unable to figure out how to average the beta values within 500bp windows across all samples, as described within the tutorial, which looks like this:

I believe it may have been done by GRanges, or another R package which utilizes GRanges, but I am unable to generate the same object format. I've tried packages such as minfi, GRanges, but I lack the hands-on knowledge to further process the TCGA data after import.

I was wondering if anyone has any suggestions as to what R packages or software I can use to produce a similar R object.

Thank you,

Justin

Hi Justin,

I used two perl script to summarize the TCGA data into genome wide bins:

1) SummarizeTables.pl combines several sample files in a single table.

2) summarize_bs_in_bins.pl sumerizes bisulfite values in genome wide bins of fixed size by computing the average % methylation values.

I provide these scripts on my github repository: https://github.com/MatthiasLienhard/hts_scripts.git

The tables can then be averaged over normal and tumor samples in R directly.

For TCGA head and neck squamous cell carcinoma, I already prepared an 500 base overview table, in case you are interested, please contact me.

Best, Matthias