pagoda.reduce.loading.redundancy {scde} | R Documentation

## Collapse aspects driven by the same combinations of genes

### Description

Examines PC loading vectors underlying the identified aspects and clusters aspects based on a product of loading and score correlation (raised to corr.power). Clusters of aspects driven by the same genes are determined based on the distance.threshold and collapsed.

### Usage

    pagoda.reduce.loading.redundancy(tam, pwpca, clpca = NULL, plot = FALSE,
      cluster.method = "complete", distance.threshold = 0.01, corr.power = 4,
      n.cores = detectCores(), abs = TRUE, ...)

### Arguments

`tam` | output of pagoda.top.aspects()
`pwpca` | output of pagoda.pathway.wPCA()
`clpca` | output of pagoda.gene.clusters() (optional)
`plot` | whether to plot the resulting clustering
`cluster.method` | one of the standard clustering methods to be used (fastcluster::hclust is used if available or stats::hclust)
`distance.threshold` | similarity threshold for grouping interdependent aspects
`corr.power` | power to which the product of loading and score correlation is raised
`n.cores` | number of cores to use during processing
`abs` | Boolean of whether to use absolute correlation
`...` | additional arguments are passed to the pagoda.view.aspects() method during plotting

### Value

a list structure analogous to that returned by pagoda.top.aspects(), but with addition of a $cnam element containing a list of aspects summarized by each row of the new (reduced) $xv and $xvw

### Examples

    data(pollen)
    cd <- clean.counts(pollen)

    knn <- knn.error.models(cd, k=ncol(cd)/4, n.cores=10, min.count.threshold=2, min.nonfailed=5, max.model.plots=10)
    varinfo <- pagoda.varnorm(knn, counts = cd, trim = 3/ncol(cd), max.adj.var = 5, n.cores = 1, plot = FALSE)
    pwpca <- pagoda.pathway.wPCA(varinfo, go.env, n.components=1, n.cores=10, n.internal.shuffles=50)
    tam <- pagoda.top.aspects(pwpca, return.table = TRUE, plot=FALSE, z.score=1.96)  # top aspects based on GO only
    tamr <- pagoda.reduce.loading.redundancy(tam, pwpca)

[Package scde version 2.20.0 Index]