@inbook{b17b6291f6094f78b96b8fb23735a64a,
title = "Computational Approaches for the Investigation of Intra-tumor Heterogeneity and Clonal Evolution from Bulk Sequencing Data in Precision Oncology Applications",
abstract = "While the clonal model of cancer evolution was first proposed over 40 years ago, only recently next-generation sequencing has allowed a more precise and quantitative assessment of tumor clonal and subclonal landscape. Consequently, a plethora of computational approaches and tools have been developed to analyze this data with the goal of inferring the clonal landscape of a tumor and characterize its temporal or spatial evolution. This chapter introduces intra-tumor heterogeneity (ITH) in the context of precision oncology applications and provides an overview of the basic concepts, algorithms, and tools for the dissection, analysis, and visualization of ITH from bulk DNA sequencing.",
keywords = "Cancer, Clonal expansion, Clonality, Clone, DNA sequencing, ITH, NGS, Subclone, Tumor, Tumor evolution, Tumor phylogeny",
author = "Alessandro Lagan{\`a}",
note = "Publisher Copyright: {\textcopyright} 2022, Springer Nature Switzerland AG.",
year = "2022",
doi = "10.1007/978-3-030-91836-1_6",
language = "English",
series = "Advances in Experimental Medicine and Biology",
publisher = "Springer",
pages = "101--118",
booktitle = "Advances in Experimental Medicine and Biology",
address = "Germany",
}