Open AccessspatialTIME and iTIME: R package and Shiny application for visualization and analysis of immunofluorescence data
Author(s) -
Jordan H. Creed,
Christopher M. Wilson,
Alex C. Soupir,
Christelle Colin,
Gregory J. Kimmel,
Oscar E. Ospina,
Nicholas H. Chakiryan,
Joseph Markowitz,
Lauren C. Peres,
Anna E. Coghill,
Brooke L. Fridley
Publication year - 2021
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btab757
Subject(s) - computer science , univariate , web application , multiplex , r package , sample (material) , bivariate analysis , visualization , source code , data mining , multivariate statistics , bioinformatics , world wide web , biology , computational science , programming language , machine learning , chromatography , chemistry
Multiplex immunofluorescence (mIF) staining combined with quantitative digital image analysis is a novel and increasingly used technique that allows for the characterization of the tumor immune microenvironment (TIME). Generally, mIF data is used to examine the abundance of immune cells in the TIME; however, this does not capture spatial patterns of immune cells throughout the TIME, a metric increasingly recognized as important for prognosis. To address this gap, we developed an R package spatialTIME that enables spatial analysis of mIF data, as well as the iTIME web application that provides a robust but simplified user interface for describing both abundance and spatial architecture of the TIME. The spatialTIME package calculates univariate and bivariate spatial statistics (e.g. Ripley's K, Besag's L, Macron's M and G or nearest neighbor distance) and creates publication quality plots for spatial organization of the cells in each tissue sample. The iTIME web application allows users to statistically compare the abundance measures with patient clinical features along with visualization of the TIME for one tissue sample at a time.