Caitlin, Forgive me, but I’m not quite sure exactly what your question is asking. The data is originally from the TCGA and I have it downloaded onto another R script. I opened a new script to perform the functions I posted to this forum because I was unable to input any other commands into the console.... due to the fact that the translated data filled the entirety of said consule. Perhaps overloaded it? Regardless, I was unable to input any further commands.
-Spencer Brackett On Sun, Aug 26, 2018 at 8:27 PM Caitlin <bioprogram...@gmail.com> wrote: > You're welcome Spencer :) > > The 4th line: > > path <– "." > > refers to the current directory (the dot in other words). Is the data > stored in the same directory where the code is being run? > > > > On Sun, Aug 26, 2018 at 5:22 PM Spencer Brackett < > spbracket...@saintjosephhs.com> wrote: > >> Thank you! I will make note of that. Unfortunately, lines 1 and 4 of the >> first portion of this analysis appear to be where the error begins... to >> which several subsequent lines also come up as ‘errored’. Perhaps this is >> an issue of the capitalization and/or spacing (something within the text)? >> The proposed method for methylation data extraction is based on the first >> third of the following TCGA workflow: >> https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5302158/#!po=0.0715308 >> >> Best, >> >> Spencer Brackett >> >> >> >> >> >> >> >> >> >> >> >> >> On Sun, Aug 26, 2018 at 8:07 PM Caitlin <bioprogram...@gmail.com> wrote: >> >>> Hi Spencer. >>> >>> Should you capitalize the following library import? >>> >>> library(summarizedExperiment) >>> >>> In other words, I think that line should be: >>> >>> library(SummarizedExperiment) >>> >>> Hope this helps. >>> >>> ~Caitlin >>> >>> >>> >>> >>> On Sun, Aug 26, 2018 at 2:09 PM Spencer Brackett < >>> spbracket...@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@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@GISTIC@AllByGene >>>> 6 gistic.thresholedbygene <− gistic@GISTIC@ThresholedByGene >>>> >>>> Repeat this procedure to obtain LGG GISTIC results. >>>> >>>> ***Please ignore the 'non-coded' text as they are procedural >>>> steps/classifications*** >>>> >>>> [[alternative HTML version deleted]] >>>> >>>> ______________________________________________ >>>> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see >>>> https://stat.ethz.ch/mailman/listinfo/r-help >>>> PLEASE do read the posting guide >>>> http://www.R-project.org/posting-guide.html >>>> and provide commented, minimal, self-contained, reproducible code. >>>> >>> [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
