Skip to Main content Skip to Navigation
Preprints, Working Papers, ...

Statistical estimation of genomic alterations of tumors

Abstract : Recent research reveals that personalized medicine is one major way to treat cancer. In order to develop personalized medicine, characterizing the genomic alterations is a vital component. Several methods have been proposed to this end. One of the rst methods is the Genome Alteration Print (GAP) by Popova et al, which uses a deterministic approach. We follow this approach and develop a parametric probabilistic model for GAP, together with its statistical estimation, based on a preliminary segmentation of SNP measurements obtained from microarray experiments. For estimation, we implement the expectation-maximization (EM) algorithm to maximize the likelihood of this model and get the parameter estimation which characterizes the genomic alterations. In our approach, the tumoral ploidy is deduced from penalized model selection. Our model is tested on simulated data and real data.
Complete list of metadata

Cited literature [13 references]  Display  Hide  Download
Contributor : Christine Keribin Connect in order to contact the contributor
Submitted on : Friday, January 19, 2018 - 6:38:10 PM
Last modification on : Tuesday, October 19, 2021 - 11:00:23 AM
Long-term archiving on: : Thursday, May 24, 2018 - 8:15:35 AM


Files produced by the author(s)


  • HAL Id : hal-01688885, version 1


Yi Liu, Christine Keribin, Tatiana Popova, Yves Rozenholc. Statistical estimation of genomic alterations of tumors. 2018. ⟨hal-01688885⟩



Record views


Files downloads