[catherineh1] stIHC 0.1.1

catherine.higgins@mu.ie (Catherine Higgins) — Wed, 21 Oct 2026 15:24:52 GMT

Spatial transcriptomics iterative hierarchical clustering ('stIHC'), is a method for identifying spatial gene co-expression modules, defined as groups of genes with shared spatial expression patterns. The method is applicable across spatial transcriptomics technologies with differing spatial resolution, and provides a framework for investigating the spatial organisation of gene expression in tissues. For further details, see Higgins C., Li J.J., Carey M. .

[catherineh1] funIHC 0.1.1

catherine.higgins@mu.ie (Catherine Higgins) — Tue, 20 Oct 2026 13:30:33 GMT

Functional clustering aims to group curves exhibiting similar temporal behaviour and to obtain representative curves summarising the typical dynamics within each cluster. A key challenge in this setting is class imbalance, where some clusters contain substantially more curves than others, which can adversely affect clustering performance. While class imbalance has been extensively studied in supervised classification, it has received comparatively little attention in unsupervised clustering. This package implements functional iterative hierarchical clustering ('funIHC'), an adaptation of the iterative hierarchical clustering method originally developed for multivariate data, to the functional data setting. For further details, please see Higgins and Carey (2024) .

catherineh1.r-universe.dev

[catherineh1] stIHC 0.1.1

[catherineh1] funIHC 0.1.1