clusterContrasts {clusterExperiment} | R Documentation

## Create contrasts for testing DE of a cluster

### Description

Uses clustering to create different types of contrasts to be tested that can then be fed into DE testing programs.

### Usage

    ## S4 method for signature 'ClusterExperiment'
    clusterContrasts(cluster, contrastType, ...)

    ## S4 method for signature 'vector'
    clusterContrasts(cluster, contrastType = c("Dendro",
      "Pairs", "OneAgainstAll"), dendro = NULL, pairMat = NULL,
      outputType = c("limma", "MAST"), removeUnassigned = TRUE)

### Arguments

`cluster` | Either a vector giving contrasts assignments or a ClusterExperiment object
`contrastType` | What type of contrast to create. ‘Dendro’ traverses the given dendrogram and does contrasts of the samples in each side, ‘Pairs’ does pair-wise contrasts based on the pairs given in pairMat (if pairMat=NULL, does all pairwise), and ‘OneAgainstAll’ compares each cluster to the average of all others.
`...` | arguments that are passed to from the `ClusterExperiment` version to the most basic numeric version.
`dendro` | The dendrogram to traverse if contrastType="Dendro". Note that this should be the dendrogram of the clusters, not of the individual samples, either of class "dendrogram" or "phylo4"
`pairMat` | matrix giving the pairs of clusters for which to do pair-wise contrasts (must match to elements of cl). If NULL, will do all pairwise of the clusters in `cluster` (excluding "-1" categories). Each row is a pair to be compared and must match the names of the clusters in the vector `cluster`.
`outputType` | character string. Gives format for the resulting contrast matrix. Currently the two options are the format appropriate for `limma` and `MAST` package.
`removeUnassigned` | logical, whether to remove negative valued clusters from the design matrix. Appropriate to pick TRUE (default) if design will be input into linear model on samples that excludes -1.

### Details

The input vector must be numeric clusters, but the external commands that make the contrast matrix (e.g. `makeContrasts`) require syntatically valid R names. For this reason, the names of the levels will be "X1" instead of "1". And negative values (if removeUnassigned=FALSE) will be "X.1","X.2", etc.

### Value

List with components:

- `contrastMatrix` Contrast matrix, the form of which depends on `outputType`. If `outputType=="limma"`, the result of running `makeContrasts`: a matrix with number of columns equal to the number of contrasts, and rows equal to the number of levels of the factor that will be fit in a linear model.

- `contrastNames`A vector of names for each of the contrasts. NULL if no such additional names.

### Author(s)

Elizabeth Purdom

### References

Ritchie, ME, Phipson, B, Wu, D, Hu, Y, Law, CW, Shi, W, and Smyth, GK (2015). limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Research 43, e47. http://nar.oxfordjournals.org/content/43/7/e47

Finak, et al. MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data. Genome Biology (2015).

### Examples

    data(simData)
    cl <- clusterMany(simData,nReducedDims=c(5,10,50),  reduceMethod="PCA",
    clusterFunction="pam", ks=2:4, findBestK=c(FALSE), removeSil=TRUE,
    subsample=FALSE)
    #Pairs:
    clusterContrasts(cl,contrastType="Pairs")
    #Dendrogram
    cl<-makeDendrogram(cl)
    clusterContrasts(cl,contrastType="Pairs")

[Package clusterExperiment version 2.7.2 Index]