[R] Help with DNA Methylation Analysis

Sun Aug 26 23:37:45 CEST 2018

Thanks! Will do.

On Sun, Aug 26, 2018 at 5:37 PM Bert Gunter <bgunter.4567 using gmail.com> wrote:

> You should probably post this on the Bioconductor list rather then here,
> as you would more likely find the expertise you seek there. You are using
> Bioconductor packages after all.
>
> https://support.bioconductor.org/
>
> Cheers,
> Bert
>
>
> On Sun, Aug 26, 2018 at 2:09 PM Spencer Brackett <
> spbrackett20 using saintjosephhs.com> wrote:
>
>> Good evening,
>>
>>   I am attempting to run the following analysis on TCGA data, however
>> something is being reported as an error in my arguments... any ideas as to
>> what is incorrect in the following? Thanks!
>>
>> 1 library(TCGAbiolinks)
>> 2
>> 3 # Download the DNA methylation data: HumanMethylation450 LGG and GBM.
>> 4 path <– "."
>> 5
>> 6 query.met <– TCGAquery(tumor = c("LGG","GBM"),"HumanMethylation450",
>> level = 3)
>> 7 TCGAdownload(query.met, path = path )
>> 8 met <– TCGAprepare(query = query.met,dir = path,
>> 9                      add.subtype = TRUE, add.clinical = TRUE,
>> 10                    summarizedExperiment = TRUE,
>> 11                      save = TRUE, filename = "lgg_gbm_met.rda")
>> 12
>> 13 # Download the expression data: IlluminaHiSeq_RNASeqV2 LGG and GBM.
>> 14 query.exp <– TCGAquery(tumor = c("lgg","gbm"), platform =
>> "IlluminaHiSeq_
>> RNASeqV2",level = 3)
>> 15
>> 16 TCGAdownload(query.exp,path = path, type = "rsem.genes.normalized_
>> results")
>> 17
>> 18 exp <– TCGAprepare(query = query.exp, dir = path,
>> 19                    summarizedExperiment = TRUE,
>> 20                      add.subtype = TRUE, add.clinical = TRUE,
>> 21                    type = "rsem.genes.normalized_results",
>> 22                      save = T,filename = "lgg_gbm_exp.rda")
>>
>> To download data on DNA methylation and gene expression…
>>
>> 1 library(summarizedExperiment)
>> 2 # get expression matrix
>> 3 data <– assay(exp)
>> 4
>> 5 # get sample information
>> 6 sample.info <– colData(exp)
>> 7
>> 8 # get genes information
>> 9 genes.info <– rowRanges(exp)
>>
>> Following stepwise procedure for obtaining GBM and LGG clinical data…
>>
>> 1 # get clinical patient data for GBM samples
>> 2 gbm_clin <– TCGAquery_clinic("gbm","clinical_patient")
>> 3
>> 4 # get clinical patient data for LGG samples
>> 5 lgg_clin <– TCGAquery_clinic("lgg","clinical_patient")
>> 6
>> 7 # Bind the results, as the columns might not be the same,
>> 8 # we will plyr rbind.fill , to have all columns from both files
>> 9 clinical <– plyr::rbind.fill(gbm_clin ,lgg_clin)
>> 10
>> 11 # Other clinical files can be downloaded,
>> 12 # Use ?TCGAquery_clinic for more information
>> 13 clin_radiation <– TCGAquery_clinic("lgg","clinical_radiation")
>> 14
>> 15 # Also, you can get clinical information from different tumor types.
>> 16 # For example sample 1 is GBM, sample 2 and 3 are TGCT
>> 17 data <– TCGAquery_clinic(clinical_data_type = "clinical_patient",
>> 18    samples = c("TCGA-06-5416-01A-01D-1481-05",
>> 19  "TCGA-2G-AAEW-01A-11D-A42Z-05",
>> 20  "TCGA-2G-AAEX-01A-11D-A42Z-05"))
>>
>>
>> # Searching idat file for DNA methylation
>> query <- GDCquery(project = "TCGA-GBM",
>>                  data.category = "Raw microarray data",
>>                  data.type = "Raw intensities",
>>                  experimental.strategy = "Methylation array",
>>                  legacy = TRUE,
>>                  file.type = ".idat",
>>                  platform = "Illumina Human Methylation 450")
>>
>> **Repeat for LGG**
>>
>> To access mutational information concerning TMZ methylation…
>>
>> > mutation <– TCGAquery_maf(tumor = "lgg")
>> 2   Getting maf tables
>> 3   Source: https://wiki.nci.nih.gov/display/TCGA/TCGA+MAF+Files
>> 4   We found these maf files below:
>> 5       MAF.File.Name
>> 6   2             hgsc.bcm.edu_LGG.IlluminaGA_DNASeq.1.somatic.maf
>> 7
>> 8   3 LGG_FINAL_ANALYSIS.aggregated.capture.tcga.uuid.curated.somatic.maf
>> 9
>> 10       Archive.Name Deploy.Date
>> 11   2 hgsc.bcm.edu_LGG.IlluminaGA_DNASeq_automated.Level_2.1.0.0
>>   10-DEC-13
>> 12   3 broad.mit.edu_LGG.IlluminaGA_DNASeq_curated.Level_2.1.3.0
>>  24-DEC-14
>> 13
>> 14   Please, select the line that you want to download: 3
>>
>> **Repeat this for GBM***
>>
>> Selecting specified lines to download…
>>
>> 1 gbm.subtypes <− TCGAquery_subtype(tumor = "gbm")
>> 2 lgg.subtypes <− TCGAquery_subtype(tumor = "lgg”)
>>
>>
>>
>> Downloading data via the Bioconductor package RTCGAtoolbox…
>>
>> library(RTCGAToolbox)
>> 2
>> 3 # Get the last run dates
>> 4 lastRunDate <− getFirehoseRunningDates()[1]
>> 5 lastAnalyseDate <− getFirehoseAnalyzeDates(1)
>> 6
>> 7 # get DNA methylation data, RNAseq2 and clinical data for LGG
>> 8 lgg.data <− getFirehoseData(dataset = "LGG",
>> 9       gistic2_Date = getFirehoseAnalyzeDates(1), runDate = lastRunDate,
>> 10       Methylation = TRUE, RNAseq2_Gene_Norm = TRUE, Clinic = TRUE,
>> 11       Mutation = T,
>> 12       fileSizeLimit = 10000)
>> 13
>> 14 # get DNA methylation data, RNAseq2 and clinical data for GBM
>> 15 gbm.data <− getFirehoseData(dataset = "GBM",
>> 16       runDate = lastDate, gistic2_Date = getFirehoseAnalyzeDates(1),
>> 17       Methylation = TRUE, Clinic = TRUE, RNAseq2_Gene_Norm = TRUE,
>> 18       fileSizeLimit = 10000)
>> 19
>> 20 # To access the data you should use the getData function
>> 21 # or simply access with @ (for example gbm.data using Clinical)
>> 22 gbm.mut <− getData(gbm.data,"Mutations")
>> 23 gbm.clin <− getData(gbm.data,"Clinical")
>> 24 gbm.gistic <− getData(gbm.data,"GISTIC")
>>
>>
>>
>>
>>
>>
>> Genomic Analysis/Final data extraction:
>>
>> Enable “getData” to access the data
>>
>> Obtaining GISTIC results…
>>
>> 1 # Download GISTIC results
>> 2 gistic <− getFirehoseData("GBM",gistic2_Date ="20141017" )
>> 3
>> 4 # get GISTIC results
>> 5 gistic.allbygene <− gistic using GISTIC@AllByGene
>> 6 gistic.thresholedbygene <− gistic using GISTIC@ThresholedByGene
>>
>> Repeat this procedure to obtain LGG GISTIC results.
>>
>> ***Please ignore the 'non-coded' text as they are procedural
>> steps/classifications***
>>
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>>
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>>
>

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