Hi all,

I have downloaded 56G data from ICGC and I am having trouble analyzing it on R (Although I have access to a server). I know that ICGC data is stored in GDC. However, to analyze big data on R, I see suggestions like using SQL through dplyr/R. 

Do you know any way to do that? And I would like to know how do you work with big data from databases such as ICGC and TCGA when you need to use R.

I downloaded methylation data for 269 donors `meth_array.PACA-AU.tsv.gz` from here using *wget*:

    https://dcc.icgc.org/releases/current/Projects/PACA-AU

I want to compare mean methylation level of selected cg probes across patients.

I would appreciate any help!
We don't need full dataset in R, subset before importing, for example using *data.table::fread* + *bash* (not tested):

    # use head meth_array.PACA-AU.tsv to find out which columns we need
    # here we need columns 4 and 9
    # 4=icgc_sample_id
    # 6=probe_id
    # 9=methylation_value
    
    # read only columns 4 and 9 for probe cg00000029
    x <- fread("grep -E '^cg00000029$' meth_array.PACA-AU.tsv | cut -f4,9")
    
    # then aggregate as usual
    x[ , .(myMean = mean(methylation_value)), by = icgc_sample_id]

