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visPedigree: Tidying, Analyzing, and Visualizing Animal Pedigrees

Built on graph theory and the high-performance data.table framework, visPedigree provides a comprehensive suite of tools for processing animal pedigrees. By modeling pedigrees as Directed Acyclic Graphs (DAGs) using igraph, it ensures robust loop detection, efficient generation assignment, and flexible ancestry tracing.

Key Features

  • Pedigree Tidying: Robustly handles duplicate/bisexual individuals, pedigree loops, and missing founders.
  • High Performance: Optimized for massive datasets using data.table and Rcpp-based C++ implementations.
  • High-Throughput Matrix Calculation: Calculates Additive (A), Dominance (D), and Additive-by-Additive (AA) relationship matrices and their inverses.
  • Advanced Visualization: Generates professional vector-based pedigree graphs with a unique compaction algorithm for large full-sib families.
  • Pedigree Splitting: Efficiently detects and splits disconnected sub-populations.

Installation

Stable version from CRAN 

install.packages("visPedigree")

Development version from GitHub 

# install.packages("devtools")
devtools::install_github("luansheng/visPedigree", build_vignettes = TRUE)

Quick Start 

library(visPedigree)

# Example 1: Tidy and visualize a small pedigree
# Use compact = TRUE to condense full-sib groups into a single family node (square) 
# labeled with the group size (e.g., "2"), keeping the graph clean and legible.
cands <- c("Y", "Z1", "Z2")
small_ped |>
  tidyped(cand = cands) |>
  visped(compact = TRUE)

# Example 2: Relationship Matrices (v1.0.0+)
# Compute the additive relationship matrix (A) using high-performance C++ algorithms.
# Use compact = TRUE to accelerate calculation for pedigrees with large full-sib families.
mat_a <- simple_ped |> tidyped() |> pedmat(method = "A", compact = TRUE)
# Visualize the relationship matrix as a heatmap with histograms
vismat(mat_a)

# Example 3: Inbreeding & Highlighting
# Calculate inbreeding coefficients (f) and display them on the graph (e.g., "ID (0.05)").
# Specific individuals can be highlighted to track their inheritance paths.
simple_ped |>
  tidyped(inbreed = TRUE) |>
  visped(highlight = "J5X804", trace = "up", showf = TRUE, compact = TRUE)

# Example 4: Pedigree Splitting
# Automatically split the pedigree into independent sub-populations (connected groups).
# Each group is returned as a standalone tidyped object for separate analysis.
split_list <- simple_ped |> tidyped() |> splitped()
summary(split_list[[1]])

Citation

Luan Sheng (2026). visPedigree: Tidying and Visualizing Animal Pedigrees. R package version 1.0.0, https://github.com/luansheng/visPedigree.