pheatmap.type: Plots heatmap with clustering only within types.

In Pigengene: Infers biological signatures from gene expression data

Description

This function first performs hierarchical clustering on samples (rows of data) within each condition. Then, plots a heatmap without further clustering of rows.

Usage

pheatmap.type(Data, annRow, type = colnames(annRow)[1],
doTranspose=FALSE, conditions="Auto",...)

Arguments

Data	A matrix with samples on rows and features (genes) on columns.
annRow	A data frame with 1 column or more. Row names must be the same as row names of Data.
type	The column of annRow used for determining the condition
doTranspose	If TRUE, the matrix will be transposed for the final plot. E.g., if the genes are on the columns of Data, they will be shown on rows of the heatmap.
conditions	A character vector that determines the conditions, and their order, to be included in the heatmap. By default ("Auto"), an alphabetical order of all available conditions in annRow will be used.
...	Additional arguments passed to pheatmap function.

Value

A list of:

pheatmapS	The results of pheatmap function for each condition
pheat	The output of final pheatmap function applied on all data
ordering	The ordering of the rows in the final heatmap
annRowAll	The row annotation used in the final heatmap

Note

If type is not determined, by default the first column of annRow is used.

Author(s)

Habil Zare

See Also

eigengenes33

Examples

     data(eigengenes33)
     d1 <- eigengenes33$aml
     d2 <- eigengenes33$mds
     Disease <- c(rep("AML",nrow(d1)), rep("MDS",nrow(d2)))
     Disease <- as.data.frame(Disease)
     rownames(Disease) <- c(rownames(d1), rownames(d2))
     p1 <- pheatmap.type(Data=rbind(d1,d2),annRow=Disease,show_rownames=FALSE)

Example output

Loading required package: graph
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: ‘BiocGenerics’

The following objects are masked from ‘package:parallel’:

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from ‘package:stats’:

    IQR, mad, sd, var, xtabs

The following objects are masked from ‘package:base’:

    anyDuplicated, append, as.data.frame, basename, cbind, colnames,
    dirname, do.call, duplicated, eval, evalq, Filter, Find, get, grep,
    grepl, intersect, is.unsorted, lapply, Map, mapply, match, mget,
    order, paste, pmax, pmax.int, pmin, pmin.int, Position, rank,
    rbind, Reduce, rownames, sapply, setdiff, sort, table, tapply,
    union, unique, unsplit, which.max, which.min

Pigengene documentation built on Nov. 8, 2020, 6:47 p.m.