simplifyTCGA: Functions to convert rows annotations to ranges and...
In TCGAutils: TCGA utility functions for data management

Description Usage Arguments Details Value Author(s) Examples

This group of functions will convert row annotations as either gene symbols or miRNA symbols to row ranges based on database resources 'TxDB' and 'org.Hs' packages. It will also simplify the representation of RaggedExperiment objects to RangedSummarizedExperiment.

simplifyTCGA(obj, keep.assay = FALSE, unmapped = TRUE)

symbolsToRanges(obj, keep.assay = FALSE, unmapped = TRUE)

mirToRanges(obj, keep.assay = FALSE, unmapped = TRUE)

CpGtoRanges(obj, keep.assay = FALSE, unmapped = TRUE)

qreduceTCGA(obj, keep.assay = FALSE, suffix = "_simplified")

`obj`	A MultiAssayExperiment object obtained from curatedTCGAData
`keep.assay`	logical (default FALSE) Whether to keep the `SummarizedExperiment` assays that have been converted to `RangedSummarizedExperiment`
`unmapped`	logical (default TRUE) Include an assay of data that was not able to be mapped in reference database
`suffix`	character (default "_simplified") A character string to append to the newly modified assay for `qreduceTCGA`.

The original SummarizedExperiment containing either gene symbol or miR annotations is replaced or supplemented by a RangedSummarizedExperiment for those that could be mapped to GRanges, and optionally another SummarizedExperiment for annotations that could not be mapped to GRanges.

RaggedExperiment mutation objects become a genes by patients RangedSummarizedExperiment object containing '1' if there is a non-silent mutation somewhere in the gene, and '0' otherwise as obtained from the Variant_Classification column in the data.

"CNA" and "CNV" segmented copy number are reduced using a weighted mean in the rare cases of overlapping (non-disjoint) copy number regions.

These functions rely on 'TxDb.Hsapiens.UCSC.hg19.knownGene' and 'org.Hs.eg.db' to map to the 'hg19' NCBI build. Users should use the liftOver procedure for datasets that are provided against a different reference genome (usually 'hg18'). An example of this procedure is provided in the vignette.

A MultiAssayExperiment with any gene expression, miRNA, copy number, and mutations converted to RangedSummarizedExperiment objects

L. Waldron

library(curatedTCGAData)
library(GenomeInfoDb)

accmae <-
    curatedTCGAData(diseaseCode = "ACC",
    assays = c("CNASNP", "Mutation", "miRNASeqGene", "GISTICT"),
    dry.run = FALSE)

## update genome annotation
rex <- accmae[["ACC_Mutation-20160128"]]

## Translate build to "hg19"
tgenome <- vapply(genome(rex), translateBuild, character(1L))
genome(rex) <- tgenome

accmae[["ACC_Mutation-20160128"]] <- rex

simplifyTCGA(accmae)