Heatmap plot for dynamic features along lineages

Heatmap plot for dynamic features along lineages

Usage

DynamicHeatmap(
  srt,
  lineages,
  features = NULL,
  use_fitted = FALSE,
  border = TRUE,
  flip = FALSE,
  min_expcells = 20,
  r.sq = 0.2,
  dev.expl = 0.2,
  padjust = 0.05,
  num_intersections = NULL,
  cell_density = 1,
  cell_bins = 100,
  order_by = c("peaktime", "valleytime"),
  layer = "counts",
  assay = NULL,
  exp_method = c("zscore", "raw", "fc", "log2fc", "log1p"),
  exp_legend_title = NULL,
  limits = NULL,
  lib_normalize = identical(layer, "counts"),
  libsize = NULL,
  family = NULL,
  cluster_features_by = NULL,
  cluster_rows = FALSE,
  cluster_row_slices = FALSE,
  cluster_columns = FALSE,
  cluster_column_slices = FALSE,
  show_row_names = FALSE,
  show_column_names = FALSE,
  row_names_side = ifelse(flip, "left", "right"),
  column_names_side = ifelse(flip, "bottom", "top"),
  row_names_rot = 0,
  column_names_rot = 90,
  row_title = NULL,
  column_title = NULL,
  row_title_side = "left",
  column_title_side = "top",
  row_title_rot = 0,
  column_title_rot = ifelse(flip, 90, 0),
  feature_split = NULL,
  feature_split_by = NULL,
  n_split = NULL,
  split_order = NULL,
  split_method = c("mfuzz", "kmeans", "kmeans-peaktime", "hclust", "hclust-peaktime"),
  decreasing = FALSE,
  fuzzification = NULL,
  anno_terms = FALSE,
  anno_keys = FALSE,
  anno_features = FALSE,
  terms_width = grid::unit(4, "in"),
  terms_fontsize = 8,
  keys_width = grid::unit(2, "in"),
  keys_fontsize = c(6, 10),
  features_width = grid::unit(2, "in"),
  features_fontsize = c(6, 10),
  IDtype = "symbol",
  species = "Homo_sapiens",
  db_update = FALSE,
  db_version = "latest",
  db_combine = FALSE,
  convert_species = FALSE,
  Ensembl_version = NULL,
  mirror = NULL,
  db = "GO_BP",
  TERM2GENE = NULL,
  TERM2NAME = NULL,
  minGSSize = 10,
  maxGSSize = 500,
  GO_simplify = FALSE,
  GO_simplify_cutoff = "p.adjust < 0.05",
  simplify_method = "Wang",
  simplify_similarityCutoff = 0.7,
  pvalueCutoff = NULL,
  padjustCutoff = 0.05,
  topTerm = 5,
  show_termid = FALSE,
  topWord = 20,
  words_excluded = NULL,
  nlabel = 20,
  features_label = NULL,
  label_size = 10,
  label_color = "black",
  pseudotime_label = NULL,
  pseudotime_label_color = "black",
  pseudotime_label_linetype = 2,
  pseudotime_label_linewidth = 3,
  heatmap_palette = "viridis",
  heatmap_palcolor = NULL,
  pseudotime_palette = "cividis",
  pseudotime_palcolor = NULL,
  feature_split_palette = "simspec",
  feature_split_palcolor = NULL,
  cell_annotation = NULL,
  cell_annotation_palette = "Paired",
  cell_annotation_palcolor = NULL,
  cell_annotation_params = if (flip) {
     list(width = grid::unit(5, "mm"))
 } else {
 
       list(height = grid::unit(5, "mm"))
 },
  feature_annotation = NULL,
  feature_annotation_palette = "Dark2",
  feature_annotation_palcolor = NULL,
  feature_annotation_params = if (flip) {
     list(height = grid::unit(5, "mm"))
 } else
    {
     list(width = grid::unit(5, "mm"))
 },
  separate_annotation = NULL,
  separate_annotation_palette = "Paired",
  separate_annotation_palcolor = NULL,
  separate_annotation_params = if (flip) {
     list(width = grid::unit(10, "mm"))
 }
    else {
     list(height = grid::unit(10, "mm"))
 },
  reverse_ht = NULL,
  use_raster = NULL,
  raster_device = "png",
  raster_by_magick = FALSE,
  height = NULL,
  width = NULL,
  units = "inch",
  seed = 11,
  ht_params = list()
)

Arguments

srt

A Seurat object.

lineages

A character vector specifying the lineages to plot.

features

A character vector specifying the features to plot. By default, this parameter is set to NULL, and the dynamic features will be determined by the parameters min_expcells, r.sq, dev.expl, padjust and num_intersections.

use_fitted

Whether to use fitted values. Default is FALSE.

border

Whether to add a border to the heatmap. Default is TRUE.

flip

Whether to flip the heatmap. Default is FALSE.

min_expcells

The minimum number of expected cells. Default is 20.

r.sq

The R-squared threshold. Default is 0.2.

dev.expl

The deviance explained threshold. Default is 0.2.

padjust

The p-value adjustment threshold. Default is 0.05.

num_intersections

This parameter is a numeric vector used to determine the number of intersections among lineages. It helps in selecting which dynamic features will be used. By default, when this parameter is set to NULL, all dynamic features that pass the specified threshold will be used for each lineage.

cell_density

The cell density within each cell bin. By default, this parameter is set to 1, which means that all cells will be included within each cell bin.

cell_bins

The number of cell bins. Default is 100.

order_by

The order of the heatmap. Default is "peaktime".

layer

A character vector specifying the layer in the Seurat object to use. Default is "counts".

assay

A character vector specifying the assay in the Seurat object to use. Default is NULL.

exp_method

A character vector specifying the method for calculating expression values. Options are "zscore", "raw", "fc", "log2fc", or "log1p". Default is "zscore".

exp_legend_title

A character vector specifying the title for the legend of expression value. Default is NULL.

limits

A two-length numeric vector specifying the limits for the color scale. Default is NULL.

lib_normalize

Whether to normalize the data by library size.

libsize

A numeric vector specifying the library size for each cell. Default is NULL.

family

The model used to calculate the dynamic features if needed. By default, this parameter is set to NULL, and the appropriate family will be automatically determined.

cluster_features_by

Which lineage to use when clustering features. By default, this parameter is set to NULL, which means that all lineages will be used.

cluster_rows

Whether to cluster rows in the heatmap. Default is FALSE.

cluster_row_slices

Whether to cluster row slices in the heatmap. Default is FALSE.

cluster_columns

Whether to cluster columns in the heatmap. Default is FALSE.

cluster_column_slices

Whether to cluster column slices in the heatmap. Default is FALSE.

show_row_names

Whether to show row names in the heatmap. Default is FALSE.

show_column_names

Whether to show column names in the heatmap. Default is FALSE.

row_names_side

A character vector specifying the side to place row names.

column_names_side

A character vector specifying the side to place column names.

row_names_rot

The rotation angle for row names. Default is 0.

column_names_rot

The rotation angle for column names. Default is 90.

row_title

A character vector specifying the title for rows. Default is NULL.

column_title

A character vector specifying the title for columns. Default is NULL.

row_title_side

A character vector specifying the side to place row title. Default is "left".

column_title_side

A character vector specifying the side to place column title. Default is "top".

row_title_rot

The rotation angle for row title. Default is 0.

column_title_rot

The rotation angle for column title.

feature_split

A factor specifying how to split the features. Default is NULL.

feature_split_by

A character vector specifying which group.by to use when splitting features (into n_split feature clusters). Default is NULL.

n_split

A number of feature splits (feature clusters) to create. Default is NULL.

split_order

A numeric vector specifying the order of splits. Default is NULL.

split_method

A character vector specifying the method for splitting features. Options are "kmeans", "hclust", or "mfuzz". Default is "kmeans".

decreasing

Whether to sort feature splits in decreasing order. Default is FALSE.

fuzzification

The fuzzification coefficient. Default is NULL.

anno_terms

Whether to include term annotations. Default is FALSE.

anno_keys

Whether to include key annotations. Default is FALSE.

anno_features

Whether to include feature annotations. Default is FALSE.

terms_width

A unit specifying the width of term annotations. Default is unit(4, "in").

terms_fontsize

A numeric vector specifying the font size(s) for term annotations. Default is 8.

keys_width

A unit specifying the width of key annotations. Default is unit(2, "in").

keys_fontsize

A two-length numeric vector specifying the minimum and maximum font size(s) for key annotations. Default is c(6, 10).

features_width

A unit specifying the width of feature annotations. Default is unit(2, "in").

features_fontsize

A two-length numeric vector specifying the minimum and maximum font size(s) for feature annotations. Default is c(6, 10).

IDtype

A character vector specifying the type of IDs for features. Default is "symbol".

species

A character vector specifying the species for features. Default is "Homo_sapiens".

db_update

Whether to update the database. Default is FALSE.

db_version

A character vector specifying the version of the database. Default is "latest".

db_combine

Whether to use a combined database. Default is FALSE.

convert_species

Whether to use a species-converted database if annotation is missing for species. Default is FALSE.

Ensembl_version

An integer specifying the Ensembl version. Default is 103.

mirror

A character vector specifying the mirror for the Ensembl database. Default is NULL.

db

A character vector specifying the database to use. Default is "GO_BP".

TERM2GENE

A data.frame specifying the TERM2GENE mapping for the database. Default is NULL.

TERM2NAME

A data.frame specifying the TERM2NAME mapping for the database. Default is NULL.

minGSSize

An integer specifying the minimum gene set size for the database. Default is 10.

maxGSSize

An integer specifying the maximum gene set size for the database. Default is 500.

GO_simplify

Whether to simplify gene ontology terms. Default is FALSE.

GO_simplify_cutoff

A character vector specifying the cutoff for GO simplification. Default is "p.adjust < 0.05".

simplify_method

A character vector specifying the method for GO simplification. Default is "Wang".

simplify_similarityCutoff

The similarity cutoff for GO simplification. Default is 0.7.

pvalueCutoff

A numeric vector specifying the p-value cutoff(s) for significance. Default is NULL.

padjustCutoff

The adjusted p-value cutoff for significance. Default is 0.05.

topTerm

A number of top terms to include. Default is 5.

show_termid

Whether to show term IDs. Default is FALSE.

topWord

A number of top words to include. Default is 20.

words_excluded

A character vector specifying the words to exclude. Default is NULL.

nlabel

A number of labels to include. Default is 0.

features_label

A character vector specifying the features to label. Default is NULL.

label_size

The size of labels. Default is 10.

label_color

A character vector specifying the color of labels. Default is "black".

pseudotime_label

The pseudotime label. Default is NULL.

pseudotime_label_color

The pseudotime label color. Default is "black".

pseudotime_label_linetype

The pseudotime label line type. Default is 2.

pseudotime_label_linewidth

The pseudotime label line width. Default is 3.

heatmap_palette

A character vector specifying the palette to use for the heatmap. Default is "RdBu".

heatmap_palcolor

A character vector specifying the heatmap color to use. Default is NULL.

pseudotime_palette

The color palette to use for pseudotime. Default is "cividis".

pseudotime_palcolor

The colors to use for the pseudotime in the heatmap. Default is NULL.

feature_split_palette

A character vector specifying the palette to use for feature splits. Default is "simspec".

feature_split_palcolor

A character vector specifying the feature split color to use. Default is NULL.

cell_annotation

A character vector specifying the cell annotation(s) to include. Default is NULL.

cell_annotation_palette

A character vector specifying the palette to use for cell annotations. The length of the vector should match the number of cell_annotation. Default is "Paired".

cell_annotation_palcolor

A list of character vector specifying the cell annotation color(s) to use. The length of the list should match the number of cell_annotation. Default is NULL.

cell_annotation_params

A list specifying additional parameters for cell annotations. Default is a list with width = unit(1, "cm") if flip is TRUE, else a list with height = unit(1, "cm").

feature_annotation

A character vector specifying the feature annotation(s) to include. Default is NULL.

feature_annotation_palette

A character vector specifying the palette to use for feature annotations. The length of the vector should match the number of feature_annotation. Default is "Dark2".

feature_annotation_palcolor

A list of character vector specifying the feature annotation color to use. The length of the list should match the number of feature_annotation. Default is NULL.

feature_annotation_params

A list specifying additional parameters for feature annotations. Default is list().

separate_annotation

Names of the annotations to be displayed in separate annotation blocks. Each name should match a column name in the metadata of the Seurat object.

separate_annotation_palette

The color palette to use for separate annotations. Default is "Paired".

separate_annotation_palcolor

The colors to use for each level of the separate annotations. Default is NULL.

separate_annotation_params

Other parameters to ComplexHeatmap::HeatmapAnnotation when creating a separate annotation blocks.

reverse_ht

Whether to reverse the heatmap. Default is NULL.

use_raster

Whether to use a raster device for plotting. Default is NULL.

raster_device

A character vector specifying the raster device to use. Default is "png".

raster_by_magick

Whether to use the 'magick' package for raster. Default is FALSE.

height

A numeric vector specifying the height(s) of the heatmap body. Default is NULL.

width

A numeric vector specifying the width(s) of the heatmap body. Default is NULL.

units

A character vector specifying the units for the height and width. Default is "inch".

seed

An integer specifying the random seed. Default is 11.

ht_params

A list specifying additional parameters passed to the ComplexHeatmap::Heatmap function. Default is list().

See also

RunDynamicFeatures, RunDynamicEnrichment

Examples

options(log_message.verbose = FALSE)
data(pancreas_sub)
pancreas_sub <- standard_scop(pancreas_sub)
#> StandardPC_ 1 
#> Positive:  Aplp1, Cpe, Gnas, Fam183b, Map1b, Hmgn3, Pcsk1n, Chga, Tuba1a, Bex2 
#> 	   Syt13, Isl1, 1700086L19Rik, Pax6, Chgb, Scgn, Rbp4, Scg3, Gch1, Camk2n1 
#> 	   Cryba2, Pcsk2, Pyy, Tspan7, Mafb, Hist3h2ba, Dbpht2, Abcc8, Rap1b, Slc38a5 
#> Negative:  Spp1, Anxa2, Sparc, Dbi, 1700011H14Rik, Wfdc2, Gsta3, Adamts1, Clu, Mgst1 
#> 	   Bicc1, Ldha, Vim, Cldn3, Cyr61, Rps2, Mt1, Ptn, Phgdh, Nudt19 
#> 	   Smtnl2, Smco4, Habp2, Mt2, Col18a1, Rpl12, Galk1, Cldn10, Acot1, Ccnd1 
#> StandardPC_ 2 
#> Positive:  Rbp4, Tagln2, Tuba1b, Fkbp2, Pyy, Pcsk2, Iapp, Tmem27, Meis2, Tubb4b 
#> 	   Pcsk1n, Dbpht2, Rap1b, Dynll1, Tubb2a, Sdf2l1, Scgn, 1700086L19Rik, Scg2, Abcc8 
#> 	   Atp1b1, Hspa5, Fam183b, Papss2, Slc38a5, Scg3, Mageh1, Tspan7, Ppp1r1a, Ociad2 
#> Negative:  Neurog3, Btbd17, Gadd45a, Ppp1r14a, Neurod2, Sox4, Smarcd2, Mdk, Pax4, Btg2 
#> 	   Sult2b1, Hes6, Grasp, Igfbpl1, Gpx2, Cbfa2t3, Foxa3, Shf, Mfng, Tmsb4x 
#> 	   Amotl2, Gdpd1, Cdc14b, Epb42, Rcor2, Cotl1, Upk3bl, Rbfox3, Cldn6, Cer1 
#> StandardPC_ 3 
#> Positive:  Nusap1, Top2a, Birc5, Aurkb, Cdca8, Pbk, Mki67, Tpx2, Plk1, Ccnb1 
#> 	   2810417H13Rik, Incenp, Cenpf, Ccna2, Prc1, Racgap1, Cdk1, Aurka, Cdca3, Hmmr 
#> 	   Spc24, Kif23, Sgol1, Cenpe, Cdc20, Hist1h1b, Cdca2, Mxd3, Kif22, Ska1 
#> Negative:  Anxa5, Pdzk1ip1, Acot1, Tpm1, Anxa2, Dcdc2a, Capg, Sparc, Ttr, Pamr1 
#> 	   Clu, Cxcl12, Ndrg2, Hnf1aos1, Gas6, Gsta3, Krt18, Ces1d, Atp1b1, Muc1 
#> 	   Hhex, Acadm, Spp1, Enpp2, Bcl2l14, Sat1, Smtnl2, 1700011H14Rik, Tgm2, Fam159a 
#> StandardPC_ 4 
#> Positive:  Glud1, Tm4sf4, Akr1c19, Cldn4, Runx1t1, Fev, Pou3f4, Gm43861, Pgrmc1, Arx 
#> 	   Cd200, Lrpprc, Hmgn3, Ppp1r14c, Pam, Etv1, Tsc22d1, Slc25a5, Akap17b, Pgf 
#> 	   Fam43a, Emb, Jun, Krt8, Dnajc12, Mid1ip1, Ids, Rgs17, Uchl1, Alcam 
#> Negative:  Ins2, Ins1, Ppp1r1a, Nnat, Calr, Sytl4, Sdf2l1, Iapp, Pdia6, Mapt 
#> 	   G6pc2, C2cd4b, Npy, Gng12, P2ry1, Ero1lb, Adra2a, Papss2, Arhgap36, Fam151a 
#> 	   Dlk1, Creld2, Gip, Tmem215, Gm27033, Cntfr, Prss53, C2cd4a, Lyve1, Ociad2 
#> StandardPC_ 5 
#> Positive:  Pdx1, Nkx6-1, Npepl1, Cldn4, Cryba2, Fev, Jun, Chgb, Gng12, Adra2a 
#> 	   Mnx1, Sytl4, Pdk3, Gm27033, Nnat, Chga, Ins2, 1110012L19Rik, Enho, Krt7 
#> 	   Mlxipl, Tmsb10, Flrt1, Pax4, Tubb3, Prrg2, Gars, Frzb, BC023829, Gm2694 
#> Negative:  Irx2, Irx1, Gcg, Ctxn2, Tmem27, Ctsz, Tmsb15l, Nap1l5, Pou6f2, Gria2 
#> 	   Ghrl, Peg10, Smarca1, Arx, Lrpap1, Rgs4, Ttr, Gast, Tmsb15b2, Serpina1b 
#> 	   Slc16a10, Wnk3, Ly6e, Auts2, Sct, Arg1, Dusp10, Sphkap, Dock11, Edn3 

pancreas_sub <- RunSlingshot(
  pancreas_sub,
  group.by = "SubCellType",
  reduction = "UMAP"
)
#> Error in loadNamespace(x): there is no package called ‘slingshot’
pancreas_sub <- RunDynamicFeatures(
  pancreas_sub,
  lineages = c("Lineage1", "Lineage2"),
  n_candidates = 200
)
#>  
#> → Will update 1 package.
#> → The package (0 B) is cached.
#> + mgcv 1.9-3 → 1.9-4 
#>   
#> ℹ No downloads are needed, 1 pkg is cached
#> ✔ Got mgcv 1.9-4 (x86_64-pc-linux-gnu-ubuntu-24.04) (3.63 MB)
#> ✔ Installed mgcv 1.9-4  (1s)
#> ✔ 1 pkg + 5 deps: kept 5, upd 1, dld 1 (3.63 MB) [2.4s]
#> Error in subset(srt, cell = rownames(srt@meta.data)[is.finite(srt@meta.data[[l]])]): No cells found

ht1 <- DynamicHeatmap(
  pancreas_sub,
  lineages = "Lineage1",
  n_split = 5,
  split_method = "kmeans-peaktime",
  cell_annotation = "SubCellType"
)
#> Error in DynamicHeatmap(pancreas_sub, lineages = "Lineage1", n_split = 5,     split_method = "kmeans-peaktime", cell_annotation = "SubCellType"): Lineages: Lineage1 is not in the meta data of the Seurat object
ht1$plot
#> Error: object 'ht1' not found

thisplot::panel_fix(ht1$plot, raster = TRUE, dpi = 50)
#> Error: object 'ht1' not found

ht2 <- DynamicHeatmap(
  pancreas_sub,
  lineages = "Lineage1",
  features = c(
    "Sox9",
    "Neurod2",
    "Isl1",
    "Rbp4",
    "Pyy", "S_score", "G2M_score"
  ),
  cell_annotation = "SubCellType"
)
#> Error in DynamicHeatmap(pancreas_sub, lineages = "Lineage1", features = c("Sox9",     "Neurod2", "Isl1", "Rbp4", "Pyy", "S_score", "G2M_score"),     cell_annotation = "SubCellType"): Lineages: Lineage1 is not in the meta data of the Seurat object
ht2$plot
#> Error: object 'ht2' not found

thisplot::panel_fix(
  ht2$plot,
  height = 5,
  width = 5,
  raster = TRUE,
  dpi = 50
)
#> Error: object 'ht2' not found

ht3 <- DynamicHeatmap(
  pancreas_sub,
  lineages = c("Lineage1", "Lineage2"),
  n_split = 5,
  split_method = "kmeans",
  cluster_rows = TRUE,
  cell_annotation = "SubCellType"
)
#> Error in DynamicHeatmap(pancreas_sub, lineages = c("Lineage1", "Lineage2"),     n_split = 5, split_method = "kmeans", cluster_rows = TRUE,     cell_annotation = "SubCellType"): Lineages: Lineage1 is not in the meta data of the Seurat object
ht3$plot
#> Error: object 'ht3' not found

ht4 <- DynamicHeatmap(
  pancreas_sub,
  lineages = c("Lineage1", "Lineage2"),
  reverse_ht = "Lineage1",
  cell_annotation = "SubCellType",
  n_split = 5,
  split_method = "mfuzz",
  species = "Mus_musculus",
  db = "GO_BP",
  anno_terms = TRUE,
  anno_keys = TRUE,
  anno_features = TRUE
)
#> Error in DynamicHeatmap(pancreas_sub, lineages = c("Lineage1", "Lineage2"),     reverse_ht = "Lineage1", cell_annotation = "SubCellType",     n_split = 5, split_method = "mfuzz", species = "Mus_musculus",     db = "GO_BP", anno_terms = TRUE, anno_keys = TRUE, anno_features = TRUE): Lineages: Lineage1 is not in the meta data of the Seurat object
ht4$plot
#> Error: object 'ht4' not found

if (FALSE) { # \dontrun{
pancreas_sub <- AnnotateFeatures(
  pancreas_sub,
  species = "Mus_musculus",
  db = c("CSPA", "TF")
)
ht5 <- DynamicHeatmap(
  pancreas_sub,
  lineages = c("Lineage1", "Lineage2"),
  reverse_ht = "Lineage1",
  use_fitted = TRUE,
  n_split = 6,
  split_method = "mfuzz",
  heatmap_palette = "viridis",
  cell_annotation = c(
    "SubCellType", "Phase", "G2M_score"
  ),
  cell_annotation_palette = c(
    "Paired", "simspec", "Purples"
  ),
  separate_annotation = list(
    "SubCellType", c("Arxes1", "Ncoa2")
  ),
  separate_annotation_palette = c(
    "Paired", "Set1"
  ),
  separate_annotation_params = list(
    height = grid::unit(10, "mm")
  ),
  feature_annotation = c("TF", "CSPA"),
  feature_annotation_palcolor = list(
    c("gold", "steelblue"),
    c("forestgreen")
  ),
  pseudotime_label = 25,
  pseudotime_label_color = "red"
)
ht5$plot

ht6 <- DynamicHeatmap(
  pancreas_sub,
  lineages = c("Lineage1", "Lineage2"),
  reverse_ht = "Lineage1",
  use_fitted = TRUE,
  n_split = 6,
  split_method = "mfuzz",
  heatmap_palette = "viridis",
  cell_annotation = c(
    "SubCellType", "Phase", "G2M_score"
  ),
  cell_annotation_palette = c(
    "Paired", "simspec", "Purples"
  ),
  separate_annotation = list(
    "SubCellType", c("Arxes1", "Ncoa2")
  ),
  separate_annotation_palette = c("Paired", "Set1"),
  separate_annotation_params = list(width = grid::unit(10, "mm")),
  feature_annotation = c("TF", "CSPA"),
  feature_annotation_palcolor = list(
    c("gold", "steelblue"),
    c("forestgreen")
  ),
  pseudotime_label = 25,
  pseudotime_label_color = "red",
  flip = TRUE, column_title_rot = 45
)
ht6$plot
} # }