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spatialTIME and iTIME: R package and Shiny application for visualization and analysis of immunofluorescence data
SUMMARY: 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...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8652029/ https://www.ncbi.nlm.nih.gov/pubmed/34734969 http://dx.doi.org/10.1093/bioinformatics/btab757 |
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author | Creed, Jordan H Wilson, Christopher M Soupir, Alex C Colin-Leitzinger, Christelle M Kimmel, Gregory J Ospina, Oscar E Chakiryan, Nicholas H Markowitz, Joseph Peres, Lauren C Coghill, Anna Fridley, Brooke L |
author_facet | Creed, Jordan H Wilson, Christopher M Soupir, Alex C Colin-Leitzinger, Christelle M Kimmel, Gregory J Ospina, Oscar E Chakiryan, Nicholas H Markowitz, Joseph Peres, Lauren C Coghill, Anna Fridley, Brooke L |
author_sort | Creed, Jordan H |
collection | PubMed |
description | SUMMARY: 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. AVAILABILITY AND IMPLEMENTATION: spatialTIME is implemented in R and can be downloaded from GitHub (https://github.com/FridleyLab/spatialTIME) or CRAN. An extensive vignette for using spatialTIME can also be found at https://cran.r-project.org/web/packages/spatialTIME/index.html. iTIME is implemented within a R Shiny application and can be accessed online (http://itime.moffitt.org/), with code available on GitHub (https://github.com/FridleyLab/iTIME). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-8652029 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-86520292021-12-08 spatialTIME and iTIME: R package and Shiny application for visualization and analysis of immunofluorescence data Creed, Jordan H Wilson, Christopher M Soupir, Alex C Colin-Leitzinger, Christelle M Kimmel, Gregory J Ospina, Oscar E Chakiryan, Nicholas H Markowitz, Joseph Peres, Lauren C Coghill, Anna Fridley, Brooke L Bioinformatics Applications Notes SUMMARY: 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. AVAILABILITY AND IMPLEMENTATION: spatialTIME is implemented in R and can be downloaded from GitHub (https://github.com/FridleyLab/spatialTIME) or CRAN. An extensive vignette for using spatialTIME can also be found at https://cran.r-project.org/web/packages/spatialTIME/index.html. iTIME is implemented within a R Shiny application and can be accessed online (http://itime.moffitt.org/), with code available on GitHub (https://github.com/FridleyLab/iTIME). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2021-11-04 /pmc/articles/PMC8652029/ /pubmed/34734969 http://dx.doi.org/10.1093/bioinformatics/btab757 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Applications Notes Creed, Jordan H Wilson, Christopher M Soupir, Alex C Colin-Leitzinger, Christelle M Kimmel, Gregory J Ospina, Oscar E Chakiryan, Nicholas H Markowitz, Joseph Peres, Lauren C Coghill, Anna Fridley, Brooke L spatialTIME and iTIME: R package and Shiny application for visualization and analysis of immunofluorescence data |
title | spatialTIME and iTIME: R package and Shiny application for visualization and analysis of immunofluorescence data |
title_full | spatialTIME and iTIME: R package and Shiny application for visualization and analysis of immunofluorescence data |
title_fullStr | spatialTIME and iTIME: R package and Shiny application for visualization and analysis of immunofluorescence data |
title_full_unstemmed | spatialTIME and iTIME: R package and Shiny application for visualization and analysis of immunofluorescence data |
title_short | spatialTIME and iTIME: R package and Shiny application for visualization and analysis of immunofluorescence data |
title_sort | spatialtime and itime: r package and shiny application for visualization and analysis of immunofluorescence data |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8652029/ https://www.ncbi.nlm.nih.gov/pubmed/34734969 http://dx.doi.org/10.1093/bioinformatics/btab757 |
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