R/gene-relevance-plotting-differential-map.r
, R/gene-relevance-plotting-gr-map.r
, R/gene-relevance-plotting-rank.r
, and 2 more
Gene-Relevance-plotting.Rd
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 matrix,matrix plot_differential_map(coords, exprs, ..., genes, dims = 1:2, pal = hcl.colors, faceter = facet_wrap(~Gene)) # S4 method for DiffusionMap,missing plot_differential_map(coords, exprs, ..., genes, dims = 1:2, pal = hcl.colors, faceter = facet_wrap(~Gene)) # S4 method for 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 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 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 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 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 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 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 GeneRelevance,character plot(x, y, ...) # S4 method for GeneRelevance,numeric plot(x, y, ...) # S4 method for 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 $ids
containing the gene IDs used.
data(guo_norm) dm <- DiffusionMap(guo_norm) gr <- gene_relevance(dm) plot(gr) # or plot_gene_relevance(dm)guo_norm_mat <- t(Biobase::exprs(guo_norm)) pca <- prcomp(guo_norm_mat)$x plot_gene_relevance(pca, guo_norm_mat, dims = 2:3)