Visualisation of highly-multiplexed imaging data in R
Nils Eling University of Zurich, ETH Zurich
Abstract
Highly multiplexed imaging acquires the single-cell expression of selected proteins in a spatially-resolved fashion. These measurements can be visualised across multiple length-scales. First, pixel-level intensities represent the spatial distributions of feature expression with highest resolution. Second, after segmentation, expression values or cell-level metadata (e.g. cell-type information) can be visualised on segmented cell areas. Here, we have developed the cytomapper package for visualisation of multiplexed read-outs and cell-level information obtained by multiplexed imaging technologies. The main functions of this package allow 1. the visualisation of pixel-level information across multiple channels, 2. the display of cell-level information (expression and/or metadata) on segmentation masks and 3. gating and visualisation of single cells. Furthermore, we have extended the package by an on-disk representation framework to handle hundreds of images in parallel. As such, cytomapper stands at the intersection of single-cell and image analysis merging the unique strength of both read-outs.
Keywords: imaging data,data visualisation,single-cell