miniACC {MultiAssayExperiment} | R Documentation

## Adrenocortical Carcinoma (ACC) MultiAssayExperiment

### Description

A `MultiAssayExperiment` object providing a reduced version of the TCGA ACC dataset for all 92 patients. RNA-seq, copy number, and somatic mutations are included only for genes whose proteins are included in the reverse-phase protein array. The MicroRNA-seq dataset is also included, with infrequently expressed microRNA removed. Clinical, pathological, and subtype information are provided by `colData(miniACC)`, and some additional details are provided by metadata(miniACC).

### Usage

    miniACC

### Format

A `MultiAssayExperiment` with 5 experiments, providing:

RNASeq2GeneNorm

  RNA-seq count data: an `ExpressionSet` with 198 rows and 79 columns

gistict

  Reccurent copy number lesions identified by GISTIC2: a `SummarizedExperiment` with 198 rows and 90 columns

RPPAArray

  Reverse Phase Protein Array: an `ExpressionSet` with 33 rows and 46 columns. Rows are indexed by genes, but protein annotations are available from `featureData(miniACC[["RPPAArray"]])`. The source of these annotations is noted in `abstract(miniACC[["RPPAArray"]])`

Mutations

  Somatic mutations: a `matrix` with 223 rows and 90 columns. 1 for any kind of non-silent mutation, zero for silent (synonymous) or no mutation.

miRNASeqGene

  microRNA sequencing: an `ExpressionSet` with 471 rows and 80 columns. Rows not having at least 5 counts in at least 5 samples were removed.

### Author(s)

Levi Waldron lwaldron.research@gmail.com

### Source

https://github.com/waldronlab/multiassayexperiment-tcga

### References

Zheng S *et al.*: Comprehensive Pan-Genomic Characterization of Adrenocortical Carcinoma. Cancer Cell 2016, 29:723-736.

### Examples

    miniACC
    metadata(miniACC)
    colnames(colData(miniACC))
    table(miniACC$vital_status)
    longFormat(miniACC["MAPK3", , ], colDataCols = c("vital_status", "days_to_death"))
    wideFormat(miniACC["MAPK3", , ], colDataCols = c("vital_status", "days_to_death"))

    ##
    ## The following is the code used to create this mini dataset from the full ACC dataset.
    ## The full ACC MultiAssayExperiment was created by the pipeline at
    ## https://github.com/waldronlab/multiassayexperiment-tcga.
    ## Not run:
        ## See www.tinyurl.com/MAEOurls for more pre-built TCGA MultiAssayExperiment objects
        download.file("http://s3.amazonaws.com/multiassayexperiments/accMAEO.rds",
                      destfile = "accMAEO.rds")
        library(MultiAssayExperiment)
        library(RaggedExperiment) #needed for RaggedExperiment objects by updateObject()
        library(Biobase)

        acc <- readRDS("accMAEO.rds")
        acc <- updateObject(acc)
        protmap <- read.csv(paste0("http://genomeportal.stanford.edu/",
                            "pan-tcga/target_selection_send_data",
                            "?filename=Allprotein.txt"), as.is = TRUE
            )

        RPPAgenes <- Filter(function(x) x != "", protmap$Genes)
        RPPAgenes <- unlist(strsplit(RPPAgenes, ","))
        RPPAgenes <- unique(RPPAgenes)

        miniACC <-
            acc[RPPAgenes, , c("RNASeq2GeneNorm", "gistict", "RPPAArray", "Mutations")]
        mut <- assay(miniACC[["Mutations"]], i = "Variant_Classification")
        mut <- ifelse(is.na(mut) | mut == "Silent", 0, 1)

        miniACC[["Mutations"]] <- mut
        colData(miniACC) <- colData(miniACC)[, c(1:17, 810:822)]

        rpparowData <-
            protmap[match(rownames(miniACC[["RPPAArray"]]), protmap$Genes),]
        rpparowData <- AnnotatedDataFrame(rpparowData)
        featureData(miniACC[["RPPAArray"]]) <- rpparowData

        md <-
            list(
                title = "Comprehensive Pan-Genomic Characterization of Adrenocortical Carcinoma",
                PMID = "27165744",
                sourceURL = "http://s3.amazonaws.com/multiassayexperiments/accMAEO.rds",
                RPPAfeatureDataURL = paste0("http://genomeportal.stanford.edu/",
                                            "pan-tcga/show_target_selection_file",
                                            "?filename=Allprotein.txt"),
                colDataExtrasURL = "http://www.cell.com/cms/attachment/2062093088/2063584534/mmc3.xlsx"
            )
        metadata(miniACC) <- md

        mirna <- acc[["miRNASeqGene"]]
        mirna <- mirna[rowSums(assay(mirna) >= 5) >= 5, ]
        experimentData(mirna)@abstract <-
            "Note: Rows not having at least 5 counts in at least 5 samples were removed."
        miniACC <- c(miniACC,
                     list(miRNASeqGene = mirna),
                     sampleMap = sampleMap(acc)[sampleMap(acc)$assay == "miRNASeqGene",])

         miniACC[["RNASeq2GeneNorm"]] <-
             as(miniACC[["RNASeq2GeneNorm"]], "SummarizedExperiment")
         miniACC[["RPPAArray"]] <-
             as(miniACC[["RPPAArray"]], "SummarizedExperiment")
         miniACC[["miRNASeqGene"]] <-
             as(miniACC[["miRNASeqGene"]], "SummarizedExperiment")

        save(miniACC, file = "data/miniACC.RData", compress = "bzip2")

    ## End(Not run)

[Package MultiAssayExperiment version 1.6.0 Index]