Predicting tumor purity from methylation microarray data

Genome analysis Predicting tumor purity from methylation microarray data

Motivation: In cancer genomics research, one important problem is that the solid tissue sample obtained from clinical settings is always a mixture of cancer and normal cells. The sample mixture brings complication in data analysis and results in biased findings if not correctly accounted for. Estimating tumor purity is of great interest, and a number of methods have been developed using gene ex...

cDNA Microarray Data Normalization

Accurate genome-scale percentage DNA methylation estimates from microarray data.

DNA methylation is a key regulator of gene function in a multitude of both normal and abnormal biological processes, but tools to elucidate its roles on a genome-wide scale are still in their infancy. Methylation sensitive restriction enzymes and microarrays provide a potential high-throughput, low-cost platform to allow methylation profiling. However, accurate absolute methylation estimates ha...

Predicting survival from microarray data - a comparative study

MOTIVATION Survival prediction from gene expression data and other high-dimensional genomic data has been subject to much research during the last years. These kinds of data are associated with the methodological problem of having many more gene expression values than individuals. In addition, the responses are censored survival times. Most of the proposed methods handle this by using Cox's pro...

Empirical Bayes Identication of Tumor Progression Genes from Microarray Data

The use of microarray data has become quite commonplace in medical and scientific experiments. We focus here on microarray data generated from cancer studies. It is potentially important for the discovery of biomarkers to identify genes whose expression levels correlate with tumor progression. In this article, we propose a simple procedure for the identification of such genes, which we term tum...