Fast and scalable inference of multi-sample cancer lineages. Academic Article uri icon

Overview

MeSH

  • Algorithms
  • Carcinoma, Renal Cell
  • Computational Biology
  • Computer Simulation
  • Disease Progression
  • Female
  • High-Throughput Nucleotide Sequencing
  • Humans
  • Kidney Neoplasms
  • Ovarian Neoplasms
  • Phylogeny
  • Software
  • Xenograft Model Antitumor Assays

MeSH Major

  • Cell Lineage
  • Genetic Variation
  • Neoplasms

abstract

  • Somatic variants can be used as lineage markers for the phylogenetic reconstruction of cancer evolution. Since somatic phylogenetics is complicated by sample heterogeneity, novel specialized tree-building methods are required for cancer phylogeny reconstruction. We present LICHeE (Lineage Inference for Cancer Heterogeneity and Evolution), a novel method that automates the phylogenetic inference of cancer progression from multiple somatic samples. LICHeE uses variant allele frequencies of somatic single nucleotide variants obtained by deep sequencing to reconstruct multi-sample cell lineage trees and infer the subclonal composition of the samples. LICHeE is open source and available at http://viq854.github.io/lichee .

publication date

  • May 6, 2015

has subject area

  • Algorithms
  • Carcinoma, Renal Cell
  • Cell Lineage
  • Computational Biology
  • Computer Simulation
  • Disease Progression
  • Female
  • Genetic Variation
  • High-Throughput Nucleotide Sequencing
  • Humans
  • Kidney Neoplasms
  • Neoplasms
  • Ovarian Neoplasms
  • Phylogeny
  • Software
  • Xenograft Model Antitumor Assays

Research

keywords

  • Journal Article

Identity

Language

  • eng

PubMed Central ID

  • PMC4501097

Digital Object Identifier (DOI)

  • 10.1186/s13059-015-0647-8

PubMed ID

  • 25944252

Additional Document Info

start page

  • 91

volume

  • 16