Multi-driver gene prioritization based on hitting time

Resource type
Thesis type
(Thesis) M.Sc.
Date created
2014-08-22
Authors/Contributors
Abstract
A key challenge in cancer genomics is the identification and prioritization of genomic aberrations that potentially act as drivers of cancer. HIT’nDRIVE is a combinatorial method to identify aberrant genes that can collectively influence possibly distant “outlier” genes based on the “random-walk facility location” (RWFL) problem on an interaction network. RWFL uses “multi-hitting time”, the expected minimum length of a random walk originating from any aberrant gene towards an outlier. HIT’nDRIVE aims to find the smallest set of aberrant genes from which one can reach outliers within desired multi-hitting time. It estimates multi-hitting time based on the independent hitting times and reduces the RWFL to a weighted multi-set cover problem, which it solves as an integer linear program (ILP). We apply HIT’nDRIVE to identify aberrant genes that potentially act as drivers in a cancer data set and make phenotype predictions using only the potential drivers, more accurately than alternative approaches.
Document
Identifier
etd8610
Copyright statement
Copyright is held by the author.
Permissions
The author granted permission for the file to be printed and for the text to be copied and pasted.
Scholarly level
Supervisor or Senior Supervisor
Thesis advisor: Sahinalp, Cenk
Member of collection
Attachment Size
etd8610_EHodzic.pdf 1.8 MB