On integrating multi-experiment microarray data

On integrating multi-experiment microarray data.

With the extensive use of microarray technology as a potential prognostic and diagnostic tool, the comparison and reproducibility of results obtained from the use of different platforms is of interest. The integration of those datasets can yield more informative results corresponding to numerous datasets and microarray platforms. We developed a novel integration technique for microarray gene-ex...

cDNA Microarray Data Normalization

Integrating data from heterogeneous DNA microarray platforms

DNA microarrays are one of the most used technologies for gene expression measurement. However, there are several distinct microarray platforms, from different manufacturers, each with its own measurement protocol, resulting in data that can hardly be compared or directly integrated. Data integration from multiple sources aims to improve the assertiveness of statistical tests, reducing the data...

Integrating Microarray Data by Consensus Clustering

With the exploding volume of microarray experiments comes increasing interest in mining repositories of such data. Meaningfully combining results from varied experiments on an equal basis is a challenging task. Here we propose a general method for integrating heterogeneous data sets based on the consensus clustering formalism. Our method analyzes source-specific clusterings and identifies a con...

DATA MINING cDNA MICROARRAY EXPERIMENT WITH A GEE APPROACH

The use of microarray technology provides access to the simultaneous expression of thousands of genes and is revolutionizing the scientific community of functional genomics. This thesis investigates a cDNA microarray experiment with the goal of discovering differentially expressed genes across several factors. The analysis first ”normalizes” the data through the VSN package which is a robust ca...