Package 'chevreulPlot'

Cyclone cell cycle pairs by symbol

Description

cell cycle genes with paired expression represented by HGNC symbol

Usage

cc.genes.cyclone

Format

a list of dataframes with G1, G2, and S gene expression

G1

G1 gene symbols

G2

G2 gene symbols

S

S gene symbols

...

Source

cyclone

---

Enframe Cluster Markers

Description

Enframe Cluster Markers

Usage

enframe_markers(tbl)

Arguments

tbl	a tibble of marker genes

Value

a pivoted tibble of marker genes

---

Ensembl version used for build

Description

Ensembl version used for build

Usage

ensembl_version

Format

An object of class character of length 1.

Source

http://www.ensembl.org/

Examples

# ensembl_version

---

Human annotation data

Description

Human (Homo sapiens) annotations based on genome assembly GRCH38 from Ensembl.

Usage

grch38

Format

An object of class tbl_df (inherits from tbl, data.frame) with 76062 rows and 9 columns.

Details

Variables:

• ensgene

• entrez

• symbol

• chr

• start

• end

• strand

• biotype

• description

Source

http://ensembl.org/homo_sapiens

Examples

data("grch38")
head(grch38)

---

Human transcripts to genes

Description

Lookup table for converting Human (Homo sapiens) Ensembl transcript IDs to gene IDs based on genome assembly GRCH38 from Ensembl.

Usage

grch38_tx2gene

Format

An object of class tbl_df (inherits from tbl, data.frame) with 277081 rows and 2 columns.

Details

Variables:

• enstxp

• ensgene

Source

http://ensembl.org/homo_sapiens

Examples

data(grch38_tx2gene)
head(grch38_tx2gene)

---

Gene Homologs Between Human and Mouse

Description

Homologs drawn from Biomart

Usage

human_to_mouse_homologs

Format

A data frame with 23188 rows and 2 columns

HGNC.symbol

human gene symbols

MGI.symbol

mouse gene symbols

...

Source

bioMart

---

Plot Annotated Complexheatmap from SingleCellExperiment object

Description

Plot Annotated Complexheatmap from SingleCellExperiment object

Usage

make_complex_heatmap(
  object,
  features = NULL,
  group.by = "ident",
  cells = NULL,
  assayName = "logcounts",
  experiment = NULL,
  group.bar.height = 0.01,
  column_split = NULL,
  col_arrangement = "ward.D2",
  mm_col_dend = 30,
  ...
)

Arguments

object	A SingleCellExperiment object
features	Vector of features to plot. Features can come
group.by	Name of one or more metadata columns to annotate columns by (for example, orig.ident)
cells	Cells to retain
assayName	"counts" for raw data "scale.data" for log-normalized data
experiment	experiment to display
group.bar.height	height for group bars
column_split	whether to split columns by metadata value
col_arrangement	how to arrange columns whether with a dendrogram (Ward.D2, average, etc.) or exclusively by metadata category
mm_col_dend	height of column dendrogram
...	additional arguments passed to Heatmap

Value

a complexheatmap

Examples

data("tiny_sce")
make_complex_heatmap(tiny_sce)

---

Plot All Transcripts

Description

plot expression all transcripts for an input gene superimposed on embedding

Usage

plot_all_transcripts(
  object,
  features,
  embedding = "UMAP",
  from_gene = TRUE,
  ...
)

Arguments

object	A object
features	gene or vector of transcripts
embedding	umap
from_gene	whether to look up transcripts for an input gene
...	additional arguments passed to plot_feature_on_embedding

Value

a list of embedding plots colored by a feature of interest

Examples

data("tiny_sce")
plot_all_transcripts(tiny_sce, "NRL", from_gene = TRUE)

---

Plot Read Count

Description

Draw a box plot for read count data of a metadata variable

Usage

plot_colData_histogram(
  object,
  group_by = NULL,
  fill_by = NULL,
  yscale = "linear",
  return_plotly = FALSE
)

Arguments

object	A object
group_by	Metadata variable to plot. Default set to "nCount_RNA"
fill_by	Variable to color bins by. Default set to "batch"
yscale	Scale of y axis. Default set to "linear"
return_plotly	whether to return an interactive plotly plot

Value

a histogram of read counts

Examples

data(small_example_dataset)
small_example_dataset <- sce_calcn(small_example_dataset)
# static plot
plot_colData_histogram((small_example_dataset), return_plotly = FALSE)

---

Plot Metadata Variables

Description

Plots static or interactive plot where each point represents a cell metadata variable whose position on the map depends on cell embeddings determined by the reduction technique used

Usage

plot_colData_on_embedding(
  object,
  group = "batch",
  embedding = "UMAP",
  dims = c(1, 2),
  highlight = NULL,
  return_plotly = FALSE,
  ...
)

Arguments

object	A SingleCellExperiment object
group	Name of one or more metadata columns to group (color) cells by
embedding	The dimensional reduction technique to be used
dims	Dimensions to plot, must be a two-length numeric vector
highlight	A list of vectors of cells to highlight
return_plotly	Convert plot to interactive web-based graph
...	extra parameters passed to ggplot

Value

a ggplot

Examples

data(small_example_dataset)

# static mode
plot_colData_on_embedding(small_example_dataset, "Mutation_Status", return_plotly = FALSE)

---

Plot Feature

Description

Plots gene or transcript expression overlaid on a given embedding.

Usage

plot_feature_on_embedding(
  object,
  embedding = c("UMAP", "PCA", "TSNE"),
  features,
  dims = c(1, 2),
  return_plotly = FALSE,
  ...
)

Arguments

object	A SingleCellExperiment object
embedding	Dimensional reduction technique to be used
features	Feature to plot
dims	Dimensions to plot, must be a two-length numeric vector
return_plotly	return plotly object
...	additional arguments passed to plotReduceDim

Value

an embedding colored by a feature of interest

Examples

data(small_example_dataset)
plot_feature_on_embedding(small_example_dataset, embedding = "UMAP", 
features = "Gene_0001")

---

Plot BigWig Coverage for Genes of Interest by a Given Variable

Description

Plot BigWig coverage for genes of interest colored by a given variable

Usage

plot_gene_coverage_by_var(
  genes_of_interest = "NRL",
  cell_metadata,
  bigwig_tbl,
  group_by = "batch",
  values_of_interest = NULL,
  organism = c("human", "mouse"),
  edb = NULL,
  heights = c(3, 1),
  scale_y = "log10",
  reverse_x = FALSE,
  start = NULL,
  end = NULL,
  summarize_transcripts = FALSE,
  ...
)

Arguments

genes_of_interest	Gene of interest
cell_metadata	a dataframe with cell metadata from object
bigwig_tbl	a tibble with colnames "name", "bigWig", and "sample_id" matching the filename, absolute path, and sample name of each cell in the cell_metadata
group_by	Variable to color by
values_of_interest	values of interest
organism	human (default) or mouse
edb	ensembldb object
heights	The heights of each row in the grid of plot
scale_y	whether to scale coverage
reverse_x	whether to reverse x axis
start	start coordinates
end	end coordinates
summarize_transcripts	whether to summarize transcript counts
...	extra arguments passed to plotCoverageFromEnsembldb

Value

a ggplot with coverage faceted by group_by

---

Plot Cluster Marker Genes

Description

Plot a dot plot of n marker features grouped by cell metadata available methods are wilcoxon rank-sum test

Usage

plot_marker_features(
  object,
  group_by = "batch",
  num_markers = 5,
  selected_values = NULL,
  return_plotly = FALSE,
  marker_method = "wilcox",
  experiment = "gene",
  hide_technical = NULL,
  unique_markers = FALSE,
  p_val_cutoff = 1,
  ...
)

Arguments

object	a object
group_by	the metadata variable from which to pick clusters
num_markers	default is 5
selected_values	selected values to display
return_plotly	whether to return an interactive plotly plot
marker_method	"wilcox"
experiment	experiment to plot default gene
hide_technical	whether to exclude mitochondrial or ribosomal genes
unique_markers	whether to plot only unique marker genes for group
p_val_cutoff	cutoff for p value display
...	extra parameters passed to ggplot2

Value

a ggplot with marker genes from group_by

Examples

data(small_example_dataset)
plot_marker_features(small_example_dataset, group_by = "gene_snn_res.1")

---

Plot Transcript Composition

Description

plot the proportion of reads of a given gene map to each transcript

Usage

plot_transcript_composition(
  object,
  gene_symbol,
  group.by = "batch",
  standardize = FALSE,
  drop_zero = FALSE
)

Arguments

object	A object
gene_symbol	Gene symbol of gene of interest
group.by	Name of one or more metadata columns to annotate columns by (for example, orig.ident)
standardize	whether to standardize values
drop_zero	Drop zero values

Value

a stacked barplot of transcript counts

Examples

data(tiny_sce)
plot_transcript_composition(tiny_sce, "NRL")

---

Plot Violin plot

Description

Plots a Violin plot of a single data (gene expression, metrics, etc.) grouped by a metadata variable

Usage

plot_violin(
  object,
  group_by = "batch",
  plot_vals = NULL,
  features = "NRL",
  experiment = "gene",
  ...
)

Arguments

object	A SingleCellExperiment object
group_by	Variable to group (color) cells by
plot_vals	plot values
features	Features to plot
experiment	Name of experiment to use, defaults to active experiment
...	extra parameters passed to ggplot2

Value

a violin plot

Examples

data("tiny_sce")
plot_violin(tiny_sce, "Prep.Method", features = "NRL")

---

Plotly settings

Description

Change settings of a plotly plot

Usage

plotly_settings(plotly_plot, width = 600, height = 700)

Arguments

plotly_plot	A plotly plot
width	Default set to '600'
height	Default set to '700'

Value

a plotly plot with altered settings

---

Small example SingleCellExperiment

Description

created with scuttle::mockSCE

Usage

small_example_dataset

Format

An SCE with 200 cells and 1000 genes

Source

scuttle::mockSCE

---

Tiny example SingleCellExperiment

Description

subset to only NRL from chevreuldata::human_gene_transcript_sce()

Usage

tiny_sce

Format

An SCE with only expression of NRL gene and NRL transripts

Source

chevreuldata::human_gene_transcript_sce()

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