aheatmat: annotated heatmap using heatmat engine
In nickytong/GenAnalysis: Genomic Analysis

annotated heatmap using heatmat engine

aheatmat(mat, pheno = NULL, gSel = NULL, sSel0 = NULL, sSel1 = NULL,
  colOrderIndex = NULL, rowOrderIndex = NULL, scale = "row",
  clusterWithScaledData = FALSE, cluster_rows = TRUE, cluster_cols = TRUE,
  clustering_distance_rows = "correlation",
  clustering_distance_cols = "correlation", clustering_method = "ward.D",
  truncate = NA, q1 = 0.01, q2 = 0.99, Lower = NULL, Upper = NULL,
  cexRow = NULL, cexCol = NULL, labCol = NULL, labRow = NULL,
  colbar = NULL, rowbar = NULL, color = colorpalette2colvec("bluered"),
  ncolor = 60, colBarSel = NULL, y0 = 1, x0 = 0.8, yd = 0.17,
  oma = c(0, 1, 3, 11) + 0.1, plot = TRUE, colpal = NULL, rowpal = NULL,
  gpheno = NULL, plotLegend = TRUE, labRowcolor = NULL, ...)

`mat`	matrix for heatmap
`pheno`	a data frame where columns represent different column bars (in a heatmap) notice: always do not subset pheno!
`gSel`	gene selection. This can be index or gene names. Internally, both will be converted to integer based index (global or local)
`sSel0`	sample selection filter 0; by default, this deals with augMat to remove all NA columns the user can override this by supplying a vector of indeces or sample names.
`sSel1`	sample selection (index or sample names). This is useful to select a subset of samples based on phenotype, i.e. some mutation, like ++ to be removed
`colOrderIndex`	index/sample names to order column; The actual number of samples surviving is an intersect between colOrderIndex and sSel (from sSel0 and sSel1). if not specified, column clustering will be instructed to construct; otherwise, no clumn clustering will be done later on
`rowOrderIndex`	index (integer or gene names) to order rows; The actual genes surviving is an intersect between rowOrderIndex and gSel. if not specified, row clustering will be instructed to construct; otherwise, no row clustering will be done later on. To disable row clustering, need to specify rowOrderIndex and cluster_rows=FALSE simultaneously
`scale`	selection from c("none", "row", "column")
`clusterWithScaledData`	logical indicating if use scaled data for clustering; default is FALSE
`cluster_rows`	whether to cluster rows
`cluster_cols`	whether to cluster columns
`clustering_distance_rows`	distance metric for rows
`clustering_distance_cols`	distance metric for cols
`clustering_method`	clustering method
`truncate`	logical indicating if truncation is needed; default is NA will enable truncate if scale!='none'
`q1`	parameter q1 to truncByLimit
`q2`	parameter q2 to truncByLimit
`Lower`	parameter Lower to truncByQuantile()
`Upper`	parameter Upper to truncByQuantile()
`colbar`	column bar object as returned by prepcolbar(): need to add option for colbar=NULL, no colbar case
`rowbar`	row bar object as returned by prepcolbar(). Default is NULL, meaning no rowbar
`color`	color vector for expression data
`ncolor`	number of colors to be interpolated based on color parameter
`colBarSel`	a vector to select a subset of column bars; this should be a subset of colnames of pheno data (also colnames of colbar)
`oma`	oma passed to par()
`plot`	whether to plot the heatmap
`colpal`	user specified column-wise color palette (a named list of color vector); only shared names will be used to update default colpal. Default is NULL thus no updates at all, only focusing on default
`rowpal`	user specified row-wise color palette (a named list of color vector); only shared names will be used to update default rowpal. Default is NULL thus no updates at all, only focusing on default
`gpheno`	a one-column gene annotation data frame. (need more work to include multiple row bars and check indexing)
`plotLegend`	whether to plot color legend
`...`	additional parameters to heatmat