Description Usage Arguments Value
annotated heatmap using heatmat engine
1 2 3 4 5 6 7 8 9 10 11 | 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 |
mapL list with additional attributes to reconstruct heatmap (returned by plotHeatmap, a phm class)
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