R/gene-relevance-plotting-differential-map.r
, R/gene-relevance-plotting-gr-map.r
, R/gene-relevance-plotting.r
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, ..., gene, dims = 1:2, pal = hcl.colors, faceter = facet_wrap(~Gene)) # S4 method for matrix,matrix plot_differential_map(coords, exprs, ..., gene, dims = 1:2, pal = hcl.colors, faceter = facet_wrap(~Gene)) # S4 method for DiffusionMap,missing plot_differential_map(coords, exprs, ..., gene, dims = 1:2, pal = hcl.colors, faceter = facet_wrap(~Gene)) # S4 method for GeneRelevance,missing plot_differential_map(coords, exprs, ..., gene, dims = 1:2, pal = hcl.colors, faceter = facet_wrap(~Gene)) plot_gene_relevance(coords, exprs, ..., iter_smooth = 2L, n_top = 10L, genes = 5L, dims = 1:2, pal = palette()) # S4 method for matrix,matrix plot_gene_relevance(coords, exprs, ..., iter_smooth = 2L, n_top = 10L, genes = 5L, dims = 1:2, pal = palette()) # S4 method for DiffusionMap,missing plot_gene_relevance(coords, exprs, ..., iter_smooth = 2L, n_top = 10L, genes = 5L, dims = 1:2, pal = palette()) # S4 method for GeneRelevance,missing plot_gene_relevance(coords, exprs, ..., iter_smooth = 2L, n_top = 10L, genes = 5L, dims = 1:2, pal = palette()) # 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 |
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. |
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) |
x |
|
y, gene | 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 $ids
containing the gene IDs used.
data(guo_norm) dm <- DiffusionMap(guo_norm) gr <- gene_relevance(dm) plot(gr) # or plot_gene_relevance(dm)#> Warning: Removed 227 rows containing missing values (geom_point).guo_norm_mat <- t(Biobase::exprs(guo_norm)) pca <- prcomp(guo_norm_mat)$x plot_gene_relevance(pca, guo_norm_mat, dims = 2:3)#> Warning: Removed 134 rows containing missing values (geom_point).