Title: Spatial Transcriptomics Distance Calculation and Visualization
Version: 0.6.4
Description: Analysis of spatial relationships between cell types in spatial transcriptomics data. Spatial proximity is a critical factor in cell-cell communication. The package calculates nearest neighbor distances between specified cell types and provides visualization tools to explore spatial patterns. Applications include studying cell-cell interactions, immune microenvironment characterization, and spatial organization of tissues.
License: GPL (≥ 3)
Encoding: UTF-8
RoxygenNote: 7.3.2
Depends: R (≥ 4.0.0)
Imports: dplyr, ggplot2, Hmisc, scales, stats, RColorBrewer, tidyr,
Suggests: testthat, knitr, rmarkdown
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-06-17 11:41:36 UTC; wzx
Author: Zixiang Wang ORCID iD [aut, cre], Lei Yang [aut], Zhaojian Liu [aut]
Maintainer: Zixiang Wang <wangzixiang@sdu.edu.cn>
Repository: CRAN
Date/Publication: 2025-06-18 11:50:10 UTC

Perform correlation analysis between spatial features and distance metrics with visualization

Description

Perform correlation analysis between spatial features and distance metrics with visualization

Usage

calculate_correlations(
  spatial_data,
  distance_results,
  spatial_feature,
  distance_metric,
  method = "pearson",
  plot = TRUE,
  plot_title = NULL
)

Arguments

spatial_data

Spatial data containing feature columns and Newbarcode identifier

distance_results

Distance results containing distance metrics and Newbarcode identifier

spatial_feature

Column name from spatial_data to use for correlation (e.g., "gen2_SPLIz_numeric")

distance_metric

Column name from distance_results to use for correlation (e.g., "Epithelial_cells_A")

method

Correlation method ("pearson", "spearman", "kendall")

plot

Logical, whether to generate a scatter plot

plot_title

Title for the scatter plot (optional)

Value

A list containing correlation results and ggplot object (if plot=TRUE)

Examples

calculate_correlations(spatial_data = posi,
             distance_results = distance_results,
             spatial_feature = "gen2_SPLIz_numeric",
             distance_metric = "Epithelial_cells_A",
             method = "pearson",
             plot = TRUE,
             plot_title = "Correlation between Gene Expression and Distance")

Calculate nearest distances between cell types

Description

Calculate nearest distances between cell types

Usage

calculate_nearest_distances(
  spatial_data,
  reference_type,
  target_types,
  x_col = "pxl_row_in_fullres",
  y_col = "pxl_col_in_fullres",
  id_col = "barcode",
  type_col = "Epi_strom"
)

Arguments

spatial_data

A data frame containing spatial coordinates and cell type info

reference_type

The reference cell type to calculate distances from

target_types

Vector of target cell types to calculate distances to

x_col

Column name for x-coordinates

y_col

Column name for y-coordinates

id_col

Column name for cell identifiers

type_col

Column name for cell type information

Value

A data frame with nearest distances for each reference cell

Examples

calculate_nearest_distances(posi, reference_type="Macrophage",
                 target_types=c("Epithelial_cells_A","Epithelial_cells_B",
                 "Epithelial_cells_C","Epithelial_cells_D"),
                 id_col = "Newbarcode",
                 type_col = "celltype_ABCDepi")

distance_results

Description

A data frame with nearest distances for each reference cell

Usage

data("distance_results")

Format

A data frame with 18 observations on the following 5 variables.

Newbarcode

a character vector

Epithelial_cells_A

a numeric vector

Epithelial_cells_B

a numeric vector

Epithelial_cells_C

a numeric vector

Epithelial_cells_D

a numeric vector

Details

A data frame with nearest distances for each reference cell.

Source

This study.

References

Wang, Z., Yang, L., Yang, S., Li, G., Xu, M., Kong, B., Shao, C., & Liu, Z. (2025). Isoform switch of CD47 provokes macrophage-mediated pyroptosis in ovarian cancer. bioRxiv, 2025.2004.2017.649282. https://doi.org/10.1101/2025.04.17.649282

Examples

data(distance_results)
## maybe str(distance_results) ; plot(distance_results) ...

Metadata

Description

Metadata of a Seurat Object.

Usage

data("metadata")

Format

A data frame with 293 observations on the following 9 variables.

orig.ident

a character vector

nCount_Spatial

a numeric vector

nFeature_Spatial

a numeric vector

nCount_SCT

a numeric vector

nFeature_SCT

a numeric vector

integrated_snn_res.0.8

a numeric vector

seurat_clusters

a numeric vector

celltype_ABCDepi

a character vector

gen2_SPLIz_numeric

a numeric vector

Details

Metadata dataframe can be exported from Seurat Object as follows. The Seurat Object should be fully annotated and the metadata dataframe should included: orig.ident, celltype, the target gene expression, splicing index (SpliZ), etc.

Source

This study.

References

Wang, Z., Yang, L., Yang, S., Li, G., Xu, M., Kong, B., Shao, C., & Liu, Z. (2025). Isoform switch of CD47 provokes macrophage-mediated pyroptosis in ovarian cancer. bioRxiv, 2025.2004.2017.649282. https://doi.org/10.1101/2025.04.17.649282

Examples

data(metadata)
## maybe str(metadata) ; plot(metadata) ...

Normalize spatial coordinates

Description

Normalize spatial coordinates

Usage

normalize_spatial(
  data,
  sample_col = "Sample",
  x_col = "pxl_row_in_fullres",
  y_col = "pxl_col_in_fullres",
  min_value = 1,
  max_value = 10000
)

Arguments

data

A data frame containing spatial coordinates

sample_col

Column name specifying sample IDs

x_col

Column name for x-coordinates

y_col

Column name for y-coordinates

min_value

Minimum value for normalization range

max_value

Maximum value for normalization range

Value

A data frame with normalized coordinates

Examples

tissue_posi_normalized<-normalize_spatial(tissue_posi)

Visualize Nearest Neighbor Distances with Boxplot and Mean ± SEM

Description

Creates a boxplot visualization of distance metrics with overlaid mean points and SEM error bars. Suitable for comparing multiple groups with potentially skewed distributions.

Usage

plot_distance_boxplot(
  distance_result,
  id_col = "barcode",
  show_points = FALSE,
  y_scale = c("original", "log10"),
  palette = "Set2"
)

Arguments

distance_result

A data.frame generated by calculate_nearest_distances(), containing distance measurements with columns: id_col + target_types.

id_col

Name of the column containing cell IDs (default: "barcode").

show_points

Logical, whether to overlay individual data points (default: FALSE).

y_scale

Method for y-axis scaling: "original" or "log10" (default: "original").

palette

Color palette name from RColorBrewer (default: "Set2").

Value

A ggplot2 object. Additional customization can be done using ggplot2 functions.

Examples

plot_distance_boxplot(distance_results,id_col = "Newbarcode")

Radial Distance Visualization with Collision Avoidance

Description

Creates a radial plot with automatic label placement to prevent overlaps between nodes and text labels.

Usage

plot_radial_distance(
  distance_result,
  reference_type,
  id_col = "barcode",
  scale_radius = 1,
  show_labels = TRUE,
  palette = "Set2",
  label_padding = 0.15,
  center_label_expansion = 1.5
)

Arguments

distance_result

Data.frame from calculate_nearest_distances()

reference_type

Name of the reference cell type (center node)

id_col

Name of ID column (default: "barcode")

scale_radius

Scaling factor for layout (default: 1)

show_labels

Whether to show distance labels (default: TRUE)

palette

Color palette name (default: "Set2")

label_padding

Radial padding for labels (default: 0.15)

center_label_expansion

Center expansion for labels (default: 1.5)

Value

A ggplot2 object

Examples

plot_radial_distance(distance_results,id_col = "Newbarcode",
                     reference_type = "Macrophages",label_padding = 0.3,
                     show_labels = TRUE,palette = "Dark2")

posi

Description

Merged spatial location and metadata information.

Usage

data("posi")

Format

A data frame with 293 observations on the following 18 variables.

Newbarcode

a character vector

barcode

a character vector

in_tissue

a numeric vector

array_row

a numeric vector

array_col

a numeric vector

pxl_row_in_fullres

a numeric vector

pxl_col_in_fullres

a numeric vector

Sample

a character vector

Sampleid

a numeric vector

orig.ident

a character vector

nCount_Spatial

a numeric vector

nFeature_Spatial

a numeric vector

nCount_SCT

a numeric vector

nFeature_SCT

a numeric vector

integrated_snn_res.0.8

a numeric vector

seurat_clusters

a numeric vector

celltype_ABCDepi

a character vector

gen2_SPLIz_numeric

a numeric vector

Details

Merged spatial location and metadata information.

Source

This study.

References

Wang, Z., Yang, L., Yang, S., Li, G., Xu, M., Kong, B., Shao, C., & Liu, Z. (2025). Isoform switch of CD47 provokes macrophage-mediated pyroptosis in ovarian cancer. bioRxiv, 2025.2004.2017.649282. https://doi.org/10.1101/2025.04.17.649282

Examples

data(posi)
## maybe str(posi) ; plot(posi) ...

tissue_posi

Description

Position of the spots from spatial transcriptome data.

Usage

data("tissue_posi")

Format

A data frame with 9984 observations on the following 9 variables.

barcode

a character vector

in_tissue

a numeric vector

array_row

a numeric vector

array_col

a numeric vector

pxl_row_in_fullres

a numeric vector

pxl_col_in_fullres

a numeric vector

Sample

a character vector

Sampleid

a numeric vector

Newbarcode

a character vector

Details

Please find the tissue_positions.csv from the spaceranger output files: ./out/spatial/tissue_positions.csv Multiple samples should be merged together, adding "samples" and "Newbarcode" columns.

Source

This study.

References

Wang, Z., Yang, L., Yang, S., Li, G., Xu, M., Kong, B., Shao, C., & Liu, Z. (2025). Isoform switch of CD47 provokes macrophage-mediated pyroptosis in ovarian cancer. bioRxiv, 2025.2004.2017.649282. https://doi.org/10.1101/2025.04.17.649282

Examples

data(tissue_posi)
## maybe str(tissue_posi) ; plot(tissue_posi) ...

tissue_posi_normalized

Description

Normalized tissue spots position.

Usage

data("tissue_posi_normalized")

Format

A data frame with 9984 observations on the following 9 variables.

barcode

a character vector

in_tissue

a numeric vector

array_row

a numeric vector

array_col

a numeric vector

pxl_row_in_fullres

a numeric vector

pxl_col_in_fullres

a numeric vector

Sample

a character vector

Sampleid

a numeric vector

Newbarcode

a character vector

Details

Normalized tissue spots position.

Source

This study.

References

Wang, Z., Yang, L., Yang, S., Li, G., Xu, M., Kong, B., Shao, C., & Liu, Z. (2025). Isoform switch of CD47 provokes macrophage-mediated pyroptosis in ovarian cancer. bioRxiv, 2025.2004.2017.649282. https://doi.org/10.1101/2025.04.17.649282

Examples

data(tissue_posi_normalized)
## maybe str(tissue_posi_normalized) ; plot(tissue_posi_normalized) ...

Visualize spatial network with expression gradient

Description

Visualize spatial network with expression gradient

Usage

visualize_spatial_gradient(
  spatial_data,
  sample,
  gradient_type,
  fixed_type,
  expression_col = "gen2_SPLIz_numeric",
  x_col = "pxl_row_in_fullres",
  y_col = "pxl_col_in_fullres",
  type_col = "Epi_strom",
  fixed_color = "#A9C6D9",
  line_color = "#666666",
  gradient_palette = "C",
  point_size = 1,
  point_alpha = 0.8,
  line_width = 0.3,
  line_alpha = 0.6,
  show_legend = TRUE,
  legend_title = "Expression",
  grid_major_color = "gray90",
  grid_minor_color = "gray95",
  border_color = "black",
  background_color = "white"
)

Arguments

spatial_data

Spatial coordinates data frame containing cell types and expression values

sample

Sample name in the spatial transcriptome data

gradient_type

Cell type to show with expression gradient coloring

fixed_type

Cell type to show in fixed color (default gray)

expression_col

Column name containing expression values (default "gen2_SPLIz_numeric")

x_col

Column name for x-coordinates (default "pxl_row_in_fullres")

y_col

Column name for y-coordinates (default "pxl_col_in_fullres")

type_col

Column name for cell type information (default "Epi_strom")

fixed_color

Color for the fixed cell type (default "#A9C6D9" - light gray-blue)

line_color

Color for connection lines (default "#666666" - dark gray)

gradient_palette

Color palette for expression gradient (default viridis option "C")

point_size

Size of points (default 1)

point_alpha

Transparency of points (default 0.8)

line_width

Width of connection lines (default 0.3)

line_alpha

Transparency of connection lines (default 0.6)

show_legend

Logical whether to show legend (default TRUE)

legend_title

Title for the legend (default "Expression")

grid_major_color

Color for major grid lines (default "gray90")

grid_minor_color

Color for minor grid lines (default "gray95")

border_color

Color for plot border (default "black")

background_color

Color for plot background (default "white")

Value

A ggplot object showing the spatial relationships with expression gradient

Examples

visualize_spatial_gradient(spatial_data = posi,
                           sample="SP8",
                           gradient_type = "Epithelial_cells_A",
                           fixed_type = "Macrophage",
                           expression_col = "gen2_SPLIz_numeric",
                           type_col = "celltype_ABCDepi",
                           legend_title = "Expression",
                           background_color = "white")

Visualize spatial relationships between multiple cell types

Description

Visualize spatial relationships between multiple cell types

Usage

visualize_spatial_multinetwork(
  spatial_data,
  sample,
  reference_type,
  target_types,
  x_col = "pxl_row_in_fullres",
  y_col = "pxl_col_in_fullres",
  type_col = "Epi_strom",
  color_palette = NULL,
  point_alpha = 0.7,
  line_alpha = 0.5,
  point_size = 1.5,
  line_width = 0.3,
  show_legend = TRUE
)

Arguments

spatial_data

Spatial coordinates data frame

sample

Sample name in the spatial transcriptome data

reference_type

Reference cell type (character vector of length 1)

target_types

Target cell type(s) (character vector of 1 or more)

x_col

Column name for x-coordinates

y_col

Column name for y-coordinates

type_col

Column name for cell type information

color_palette

Named vector of colors for cell types

point_alpha

Transparency level for points

line_alpha

Transparency level for connection lines

point_size

Size of points in plot

line_width

Width of connection lines

show_legend

Logical, whether to show legend

Value

A ggplot object showing the spatial relationships

Examples

visualize_spatial_multinetwork(posi, sample="SP8",reference_type="Macrophage",
                     target_type=c("Epithelial_cells_A","Epithelial_cells_B"),
                     type_col = "celltype_ABCDepi")

Visualize spatial relationships between cell types

Description

Visualize spatial relationships between cell types

Usage

visualize_spatial_network(
  spatial_data,
  sample,
  reference_type,
  target_type,
  x_col = "pxl_row_in_fullres",
  y_col = "pxl_col_in_fullres",
  type_col = "Epi_strom",
  color_palette = c(Macrophage = "#90ee90", Epithelial_cells_A = "#377EB8"),
  alpha = 0.7
)

Arguments

spatial_data

Spatial coordinates data frame

sample

Sample name in the spatial transcriptome data

reference_type

Reference cell type

target_type

Target cell type

x_col

Column name for x-coordinates

y_col

Column name for y-coordinates

type_col

Column name for cell type information

color_palette

Named vector of colors for cell types

alpha

Transparency level for points and lines

Value

A ggplot object showing the spatial relationships

Examples

visualize_spatial_network(posi, sample="SP8", reference_type="Macrophage",
                          target_type="Epithelial_cells_A",
                          x_col = "pxl_row_in_fullres",
                          y_col = "pxl_col_in_fullres",
                          type_col = "celltype_ABCDepi",
                          color_palette = c("Macrophage" = "#90ee90",
                         "Epithelial_cells_A" = "#377EB8"))

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