Paper Info
Title
Numerical reconstruction of gene expression measurements from mixed cell populations
Abstract
We propose a procedure for numerically decomposing gene expression measurements obtained from a mixed cell population into estimates of the expression levels for the biologically distinct components of the mixture. The motivating application is the problem of obtaining the tumor cell expression signal from a tissue sample that contains tumor cells as well as various types of normal cells. We propose that a numerical restoration procedure may partially substitute for a physical fractionation when the latter is not feasible. The procedure is based on a hierarchical probability model that reflects the relationship between the underlying chemical mixture and the observable aggregate measurements. Using a Monte Carlo procedure, reconstructions of the latent signal components are obtained, along with estimates of the normal and tumor expression distributions, and estimates of the fraction of normal cells in each tissue sample. Among other uses, these values can be used to diagnose differential expression between the tumor and normal cell populations. We demonstrate the procedure using simulated data and a microarray dataset from a colon cancer study.
Year
DOI
Venue
2002
10.1109/ISBI.2002.1029189
ISBI
Keywords
DocType
ISBN
Monte Carlo methods,arrays,cancer,cellular biophysics,genetics,physiological models,probability,signal reconstruction,tumours,Monte Carlo procedure,biologically distinct components,colon cancer study,microarray dataset,normal cells,physical fractionation,simulated data,tissue sample,tumor cell expression signal
Conference
0-7803-7584-X
Citations 
PageRank 
References 
1
0.40
1
Authors
1
Name
Order
Citations
PageRank
Kerby Shedden113417.42