Gene Relevance plotting {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.
## 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, ...) plot_differential_map(coords, exprs, ..., gene, dims = 1:2, pal = cube_helix, faceter = facet_wrap(~Gene)) ## S4 method for signature 'matrix,matrix' plot_differential_map(coords, exprs, ..., gene, dims = 1:2, pal = cube_helix, faceter = facet_wrap(~Gene)) ## S4 method for signature 'DiffusionMap,missing' plot_differential_map(coords, exprs, ..., gene, dims = 1:2, pal = cube_helix, faceter = facet_wrap(~Gene)) ## S4 method for signature 'GeneRelevance,missing' plot_differential_map(coords, exprs, ..., gene, dims = 1:2, pal = cube_helix, faceter = facet_wrap(~Gene)) plot_gene_relevance(coords, exprs, ..., iter_smooth = 2L, genes = 5L, dims = 1:2, pal = palette()) ## S4 method for signature 'matrix,matrix' plot_gene_relevance(coords, exprs, ..., iter_smooth = 2L, genes = 5L, dims = 1:2, pal = palette()) ## S4 method for signature 'DiffusionMap,missing' plot_gene_relevance(coords, exprs, ..., iter_smooth = 2L, genes = 5L, dims = 1:2, pal = palette()) ## S4 method for signature 'GeneRelevance,missing' plot_gene_relevance(coords, exprs, ..., iter_smooth = 2L, genes = 5L, dims = 1:2, pal = palette())
x |
|
y, gene |
Gene name(s) or index/indices to create differential map for. (integer or character) |
... |
Passed to |
coords |
A |
exprs |
An cells \times 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. |
genes |
Genes to based relevance map on or number of genes to use. (vector of strings or one number) You can also pass an index into the gene names. (vector of numbers or logicals with length > 1) |
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, gene = c('Fgf4', 'Nanog'))