I would like to create a dataframe in R that has colon adenocarcinoma tumors pulled from tcga. I want to specify that they do not exhibit low APC mRNA expression and that they do exhibit BRAF V600E point mutations. I have not had a problem creating a suitable dataframe for the APC mRNA expression using the samples.mRNASeq function. Is there an equivalent function available to identify the tumors with BRAF mutations?
This is something that is not covered within the Firebrowse API and since FirebrowseR is just an API client, it's not within there as well. When you have your data.frame of your desired mRNA / APC samples at hand, just use the their "tcga_participant_barcode" column and run the "Analyses.Mutation.MAF" function. However you define "do not exhibit low APC mRNA expression" this could look like something shown below.
require(FirebrowseR)
# retrieve expression from the colon adeno cohort and gene APC
# sample_type = "TP" indicates that only primary tumor samples are retrieved
expression.data = Samples.mRNASeq(gene = "APC", cohort = "COAD",
page_size = 2000, sample_type = "TP")
# extract the desired tcga barcodes, based on a z.score threshold of 1.96
# However this is just a basic example and depends on your analysis
# expression.samples will hold your list of barcodes
my.threshold = 1.96
expression.samples = subset(expression.data, z.score < my.threshold,
tcga_participant_barcode)
expression.samples = unlist(expression.samples)
# using your list of barcodes query the colon adeno cohort for BRAF and V600E
# and your determined barcodes
mutation.data = Analyses.Mutation.MAF(cohort = "COAD", gene = "BRAF",
tcga_participant_barcode = expression.samples)
dim(mutation.data)
Thank you that certainly would have worked. I ended up using ucsc xena to obtain the tumors with the Braf v600e and merging with the apc data by particpant barcode.
Thank you that certainly would have worked. I ended up using ucsc xena to obtain the tumors with the Braf v600e and merging with the apc data by particpant barcode.