setup_prev {crossmeta} | R Documentation

## Setup selections when many samples.

### Description

Function is useful when number of samples makes manual selection with `diff_expr` error prone and time-consuming. This is often true for large clinical data sets.

### Usage

    setup_prev(eset, contrasts)

### Arguments

`eset` | List containing one expression set with pData 'group' and 'pair' (optional) columns. Name of `eset` should be the GSE name.
`contrasts` | Character vector specifying contrasts to analyse. Each contrast must take the form "B-A" where both "B" and "A" are present in `eset` pData 'group' column. "B" is the treatment group and "A" is the control group.

### Value

List containing necessary information for `prev_anal` parameter of `diff_expr`.

### Examples

    library(lydata)
    library(Biobase)

    # location of raw data
    data_dir <- system.file("extdata", package = "lydata")

    # load eset
    gse_name  <- c("GSE34817")
    eset <- load_raw(gse_name, data_dir)

    # inspect pData of eset
    # View(pData(eset$GSE34817))  # if using RStudio
    head(pData(eset$GSE34817))    # otherwise

    # get group info from pData (differs based on eset)
    group <- pData(eset$GSE34817)$characteristics_ch1.1

    # make group names concise and valid
    group <- gsub("treatment: ", "", group)
    group <- make.names(group)

    # add group to eset pData
    pData(eset$GSE34817)$group <- group

    # setup selections
    sel <- setup_prev(eset, contrasts = "LY-DMSO")

    # run differential expression analysis
    # anal <- diff_expr(eset, data_dir, prev_anal = sel)

[Package crossmeta version 1.16.1 Index]