Package: Battlefield 1.1.0

Jean-Philippe Villemin

Battlefield: Swiss-army toolkit for selecting niche fronts and invasive margins in spatial transcriptomics data

Battlefield is a Swiss-army toolkit originally developed to define and extract spatial spots from specific tissue regions—such as front regions, niche borders, invasive margins, and cluster interfaces—using spatial transcriptomics data or clustered tissue maps. It has since been extended to support trajectory selection and layer inspection, and now provides a collection of low-level utilities for spatial transcriptomics analysis. These utilities are primarily intended to be reused within higher-level analytical packages. It is designed to work with sequencing-based platforms such as Visium at several resolutions and Visium HD(binned).

Authors:Jean-Philippe Villemin [aut, cre], European Research Council [fnd]

Battlefield_1.1.0.tar.gz
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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
Battlefield/json (API)

# Install 'Battlefield' in R:

install.packages('Battlefield', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/zhefrench/battlefield/issues

Pkgdown/docs site:https://zhefrench.github.io

Datasets:

visium_simulated_spe - Simulated Visium SpatialExperiment dataset
visiumHD_16um_simulated_spe - Simulated VisiumHD 16 µm binned SpatialExperiment dataset
visiumHD_8um_simulated_spe - Simulated VisiumHD 8 µm binned SpatialExperiment dataset

On BioConductor:Battlefield-1.1.0(bioc 3.24)Battlefield-1.0.0(bioc 3.23)

sequencing software transcriptomics spatial

4.68 score 12 scripts 88 downloads 31 exports 32 dependencies

Last updated from:69a79b679b. Checks:1 NOTE, 9 OK. Indexed: yes.

Target	Result	Time
bioc-checks	NOTE	193
linux-devel-x86_64	OK	338
source / vignettes	OK	333
linux-release-x86_64	OK	376
macos-release-arm64	OK	273
macos-oldrel-arm64	OK	186
windows-devel	OK	376
windows-release	OK	384
windows-oldrel	OK	345
wasm-release	OK	189

Exports:add_borders_to_spe add_layers_to_spe add_trajectories_to_spe adjacent_endpoint bresenham_line build_all_borders build_all_cores build_one_line build_one_trajectory build_similar_trajectories closest_spot compute_centroids count_all_inlaids count_all_neighborhoods count_inlaid count_neighborhood create_all_layers create_cluster_layers detect_grid_type directed_cluster_interface_pairs estimate_spot_spacing filter_out_by_endpoint_clusters get_inlaid_spots get_neighborhood_params get_neighborhood_spots point_segment_distance_vec remove_used_points select_border_spots select_core_spots shift_point unit_normal_left

Dependencies:abind Biobase BiocGenerics cli DelayedArray dplyr generics GenomicRanges glue IRanges lattice lifecycle magrittr Matrix MatrixGenerics matrixStats pillar pkgconfig R6 RANN rlang S4Arrays S4Vectors Seqinfo SparseArray SummarizedExperiment tibble tidyselect utf8 vctrs withr XVector

Battlefield

Rendered fromBattlefield-Main.Rmdusingknitr::rmarkdown

Last update: 2026-02-27
Started: 2026-01-02

Help page	Topics
Add border or core spot selections to SpatialExperiment colData	add_borders_to_spe
Add layer classifications to SpatialExperiment colData	add_layers_to_spe
Add trajectory information to SpatialExperiment colData	add_trajectories_to_spe
Pick a point adjacent to a selected endpoint, on a given side of a segment	adjacent_endpoint
Rasterize a line between two points using Bresenham's algorithm	bresenham_line
Build border spots for all oriented cluster pairs	build_all_borders
Build core spots for all oriented cluster pairs	build_all_cores
Build a single line of spots along a segment	build_one_line
Select spots near a segment and order them along the segment	build_one_trajectory
Build parallel spot lines around a central segment	build_similar_trajectories
Find the closest spot to a target point	closest_spot
Compute cluster centroids (mean x/y per cluster)	compute_centroids
Count inlaid composition for all clusters	count_all_inlaids
Count neighborhood composition for all clusters	count_all_neighborhoods
Count inlaid composition within a source cluster	count_inlaid
Count annotated spot types in the neighborhood of a cluster or point	count_neighborhood
Create and visualize layers for multiple clusters	create_all_layers
Create layer classification for spots in a cluster	create_cluster_layers
Detect the grid type (square vs hexagonal) from spatial coordinates	detect_grid_type
Build all oriented cluster pairs (A -> B) and their directed_pair labels	directed_cluster_interface_pairs
Estimate spot spacing from nearest-neighbor distances	estimate_spot_spacing
Filter lines by endpoint cluster membership	filter_out_by_endpoint_clusters
Get inlaid spots within a source cluster	get_inlaid_spots
Suggest neighborhood parameters based on detected grid type	get_neighborhood_params
Get neighborhood spots around a target cluster or point	get_neighborhood_spots
Point-to-segment distance (vectorized)	point_segment_distance_vec
Remove rows whose rounded (x, y) coordinates have already been used	remove_used_points
Select border spots from cluster A that touch cluster B (and flag junctions)	select_border_spots
Select core (non-interface) spots for a directed pair	select_core_spots
Shift a point along a given direction vector	shift_point
Compute the left unit normal of the directed segment A->B	unit_normal_left
Simulated Visium SpatialExperiment dataset	visium_simulated_spe
Simulated VisiumHD 16 µm binned SpatialExperiment dataset	visiumHD_16um_simulated_spe
Simulated VisiumHD 8 µm binned SpatialExperiment dataset	visiumHD_8um_simulated_spe

Package: Battlefield 1.1.0

Battlefield: Swiss-army toolkit for selecting niche fronts and invasive margins in spatial transcriptomics data

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