Introduction

Understanding the mutational heterogeneity within tumors is a keystone for the development of efficient cancer therapies. Here, we present SCITE, a stochastic search algorithm to identify the evolutionary history of a tumor from noisy and incomplete mutation profiles of single cells. SCITE comprises a flexible Markov chain Monte Carlo sampling scheme that allows the user to compute the maximum-likelihood mutation history, to sample from the posterior probability distribution, and to estimate the error rates of the underlying sequencing experiments. Evaluation on real cancer data and on simulation studies shows the scalability of SCITE to present-day single-cell sequencing data and improved reconstruction accuracy compared to existing approaches.

Publications

  1. Tree inference for single-cell data.
    Cite this
    Jahn K, Kuipers J, Beerenwinkel N, 2016-05-01 - Genome biology

Credits

  1. Katharina Jahn
    Developer

    SIB, Swiss Institute of Bioinformatics, Switzerland

  2. Jack Kuipers
    Developer

    SIB, Swiss Institute of Bioinformatics, Switzerland

  3. Niko Beerenwinkel
    Investigator

    SIB, Swiss Institute of Bioinformatics, Switzerland

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Summary
AccessionBT000360
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesC, C++
User InterfaceTerminal Command Line
Download Count0
Country/RegionSwitzerland
Submitted ByNiko Beerenwinkel