Abstract
Family-based genetic studies often require the identification of relatives up to a specified degree, but existing tools are either restricted to second-degree relatives, return entire connected pedigrees, or require multiple pre- or post-processing steps. We implemented five new functions, namely, prepare_graph, get_kinship, graph_to_trio, get_relations, and Relation_per_proband_plot, in the R package LTFHPlus to address these limitations. prepare_graph constructs a directed graph from population-level trio data using the igraph package and supports attaching additional attributes to individuals. From this graph, relatives of arbitrary degree can be identified efficiently. get_kinship calculates a kinship matrix for all individuals in a (sub)graph, and graph_to_trio reconstructs trio information from identified families, enabling downstream use with other pedigree tools. In addition, familial relations can be labelled from the graph using the function get_relations, and the total and average of each relation per proband can be plotted using Relation_per_proband_plot. Using the publicly available minnbreast dataset, we constructed a graph containing 28,081 individuals and 30,720 familial edges. Across 1,000 repetitions, the median run-time for identifying all relatives up to the third degree for 500 randomly selected individuals was 0.03 s, and kinship matrix calculation had a median run-time of 1.57 s (single-threaded execution). These functions provide a reproducible, scalable, and interoperable solution for integrating family information into genetic analyses.