Summary Research in the familial aggregation of diseases and traits utilise information on probands, and their relevant health information enriched with similar information for their family members of interest. The genealogy is typically generated from trio information in registers and biobanks. However it can be tedious and error prone to identify family members other than first-degree relatives. Here, we present a graph-based approach to effectively identify family members of arbitrary degree of relatedness, as well as the means to attach any desired information to each individual for downstream analysis and a function to efficiently calculate a kinship matrix for the identified family members and convert identified family members from a graph back into trio information.

BJV is a member of the scientific advisory board for Allelica. The other authors have no conflicts of interest.

This work was supported by Danish Data Science Academy, which is funded by the Novo Nordisk Foundation (NNF21SA0069429)

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Software is the product of this application note. The LTFHPlus package can be downloaded from GitHub at github.com/EmilMiP/LTFHPlus or installed directly from CRAN. Vignettes for usage with example data can be found on the associated pkgdown website (see github).

https://github.com/EmilMiP/LTFHPlus