Kresimir Bestak

Abstract Studying the spatial distribution of cell types in tissues is essential for understanding their function in health and disease. A widely applied measure in spatial omics analysis is the pairwise neighbor preference of cell types, indicating whether two cell types frequently occur in close proximity to each other. While various neighbor preference methods exist, there is no clear guidance for selecting one over another.

Abstract Studying the spatial distribution of cell types in tissues is essential for understanding their function in health and disease. A widely used spatial feature for quantifying tissue organization is the pairwise neighbor preference (NEP) of cell types, commonly referred to as co-occurrence or colocalization. Various methods to infer NEP have proved their utility in spatial omics studies, but despite their broad usage, no clear guidelines exist for selecting one method over the other.

Published March 6, 2025 | Version 1.1.0 Software Open What's Changed Sync dev to master by @kbestak in https://github.com/nf-core/molkart/pull/58 Merging template updates by @kbestak in https://github.com/nf-core/molkart/pull/71 Important! Template update for nf-core/tools v2.14.1 by @nf-core-bot in https://github.com/nf-core/molkart/pull/65 Fixed multiqc report by @kbestak in https://github.com/nf-core/molkart/pull/76 Mindagap skip by @kbestak in https://github.com/nf-core/molkart/pull/78...