plot_differential_map {destiny} | R Documentation |
plot(gene_relevance, 'Gene')
plots the differential map of this/these gene(s),
plot(gene_relevance)
a relevance map of a selection of genes.
Alternatively, you can use plot_differential_map
or plot_gene_relevance
on a GeneRelevance
or DiffusionMap
object, or with two matrices.
plot_differential_map( coords, exprs, ..., genes, dims = 1:2, pal = hcl.colors, faceter = facet_wrap(~Gene) ) ## S4 method for signature 'matrix,matrix' plot_differential_map( coords, exprs, ..., genes, dims = 1:2, pal = hcl.colors, faceter = facet_wrap(~Gene) ) ## S4 method for signature 'DiffusionMap,missing' plot_differential_map( coords, exprs, ..., genes, dims = 1:2, pal = hcl.colors, faceter = facet_wrap(~Gene) ) ## S4 method for signature 'GeneRelevance,missing' plot_differential_map( coords, exprs, ..., genes, dims = 1:2, pal = hcl.colors, faceter = facet_wrap(~Gene) ) plot_gene_relevance( coords, exprs, ..., iter_smooth = 2L, n_top = 10L, genes = NULL, dims = 1:2, pal = palette(), col_na = "grey", limit = TRUE ) ## S4 method for signature 'matrix,matrix' plot_gene_relevance( coords, exprs, ..., iter_smooth = 2L, n_top = 10L, genes = NULL, dims = 1:2, pal = palette(), col_na = "grey", limit = TRUE ) ## S4 method for signature 'DiffusionMap,missing' plot_gene_relevance( coords, exprs, ..., iter_smooth = 2L, n_top = 10L, genes = NULL, dims = 1:2, pal = palette(), col_na = "grey", limit = TRUE ) ## S4 method for signature 'GeneRelevance,missing' plot_gene_relevance( coords, exprs, ..., iter_smooth = 2L, n_top = 10L, genes = NULL, dims = 1:2, pal = palette(), col_na = "grey", limit = TRUE ) plot_gene_relevance_rank( coords, exprs, ..., genes, dims = 1:2, n_top = 10L, pal = c("#3B99B1", "#F5191C"), bins = 10L, faceter = facet_wrap(~Gene) ) ## S4 method for signature 'matrix,matrix' plot_gene_relevance_rank( coords, exprs, ..., genes, dims = 1:2, n_top = 10L, pal = c("#3B99B1", "#F5191C"), bins = 10L, faceter = facet_wrap(~Gene) ) ## S4 method for signature 'DiffusionMap,missing' plot_gene_relevance_rank( coords, exprs, ..., genes, dims = 1:2, n_top = 10L, pal = c("#3B99B1", "#F5191C"), bins = 10L, faceter = facet_wrap(~Gene) ) ## S4 method for signature 'GeneRelevance,missing' plot_gene_relevance_rank( coords, exprs, ..., genes, dims = 1:2, n_top = 10L, pal = c("#3B99B1", "#F5191C"), bins = 10L, faceter = facet_wrap(~Gene) ) ## S4 method for signature 'GeneRelevance,character' plot(x, y, ...) ## S4 method for signature 'GeneRelevance,numeric' plot(x, y, ...) ## S4 method for signature 'GeneRelevance,missing' plot(x, y, ...)
coords |
A |
exprs |
An cells \times genes |
... |
Passed to |
genes |
Genes to base relevance map on (vector of strings). You can also pass an index into the gene names (vector of numbers or logicals with length > 1). The default NULL means all genes. |
dims |
Names or indices of dimensions to plot. When not plotting a |
pal |
Palette. Either A colormap function or a list of colors. |
faceter |
A ggplot faceter like |
iter_smooth |
Number of label smoothing iterations to perform on relevance map. The higher the more homogenous and the less local structure. |
n_top |
Number the top n genes per cell count towards the score defining which genes to return and plot in the relevance map. |
col_na |
Color for cells that end up with no most relevant gene. |
limit |
Limit the amount of displayed gene labels to the amount of available colors in |
bins |
Number of hexagonal bins for |
x |
|
y |
Gene name(s) or index/indices to create differential map for. (integer or character) |
ggplot2 plot, when plotting a relevance map with a list member $ids
containing the gene IDs used.
gene_relevance
, Gene Relevance methods
data(guo_norm) dm <- DiffusionMap(guo_norm) gr <- gene_relevance(dm) plot(gr) # or plot_gene_relevance(dm) plot(gr, 'Fgf4') # or plot_differential_map(dm, 'Fgf4') guo_norm_mat <- t(Biobase::exprs(guo_norm)) pca <- prcomp(guo_norm_mat)$x plot_gene_relevance(pca, guo_norm_mat, dims = 2:3) plot_differential_map(pca, guo_norm_mat, genes = c('Fgf4', 'Nanog'))