In XTH1114/NBFvis: Visualization of Neighborhood-Based Features

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NBFvis

Dimensionality reduction of spatial omic data can reveal shared, spatially structured patterns of expression across a collection of genomic features. We study strategies for discovering and interactively visualizing low-dimensional structure in spatial omic data based on the construction of neighborhood features. We design quantile and network-based spatial features that result in spatially consistent embeddings. A simulation compares embeddings made with and without neighborhood-based featurization, and a re-analysis of [Keren et al., 2019] illustrates the overall workflow. We provide an R package, NBFvis, to support computation and interactive visualization for the proposed dimensionality reduction approach.

Installation

You can install the released version of NBFvis from GitHub.

devtools::install_github("XTH1114/NBFvis")

XTH1114/NBFvis documentation built on Sept. 14, 2022, 1:13 p.m.