Phillip B. Nicol, Dániel L. Barabási, Kevin R. Coombes, Amir Asiaee
{"title":"SITH: An R package for visualizing and analyzing a spatial model of intratumor heterogeneity","authors":"Phillip B. Nicol, Dániel L. Barabási, Kevin R. Coombes, Amir Asiaee","doi":"10.1002/cso2.1033","DOIUrl":null,"url":null,"abstract":"<p>Cancer progression, including the development of intratumor heterogeneity, is inherently a spatial process. Mathematical models of tumor evolution may be a useful starting point for understanding the patterns of heterogeneity that can emerge in the presence of spatial growth. A commonly studied spatial growth model assumes that tumor cells occupy sites on a lattice and replicate into neighboring sites. Our R package <i>SITH</i> provides a convenient interface for exploring this model. Our efficient simulation algorithm allows for users to generate 3D tumors with millions of cells in under a minute. For the distribution of mutations throughout the tumor, <i>SITH</i> provides interactive graphics and summary plots. Additionally, <i>SITH</i> can produce synthetic bulk and single-cell DNA-seq datasets by sampling from the simulated tumor. A streamlined application programming interface (API) makes <i>SITH</i> a useful tool for investigating the relationship between spatial growth and intratumor heterogeneity. <i>SITH</i> is a part of <span>CRAN</span> and can be installed by running <span>install.packages(“SITH”)</span> from the R console. See https://CRAN.R-project.org/package=SITH for the user manual and package vignette.</p>","PeriodicalId":72658,"journal":{"name":"Computational and systems oncology","volume":"2 2","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9374116/pdf/nihms-1801946.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational and systems oncology","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cso2.1033","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Cancer progression, including the development of intratumor heterogeneity, is inherently a spatial process. Mathematical models of tumor evolution may be a useful starting point for understanding the patterns of heterogeneity that can emerge in the presence of spatial growth. A commonly studied spatial growth model assumes that tumor cells occupy sites on a lattice and replicate into neighboring sites. Our R package SITH provides a convenient interface for exploring this model. Our efficient simulation algorithm allows for users to generate 3D tumors with millions of cells in under a minute. For the distribution of mutations throughout the tumor, SITH provides interactive graphics and summary plots. Additionally, SITH can produce synthetic bulk and single-cell DNA-seq datasets by sampling from the simulated tumor. A streamlined application programming interface (API) makes SITH a useful tool for investigating the relationship between spatial growth and intratumor heterogeneity. SITH is a part of CRAN and can be installed by running install.packages(“SITH”) from the R console. See https://CRAN.R-project.org/package=SITH for the user manual and package vignette.