Recovering Filter-Based Microarray Data for Pathways Analysis Using a Multipoint Alignment Strategy

Abstract

The use of commercial microarrays is rapidly becoming the method of choice for profiling gene expression and assessing various disease states. Research Genetics has provided a series of biological and software tools to the research community for these analyses. The fidelity of data analysis using these tools is dependent on a series of welldefined reference control points in the array. During the course of our investigations, it became apparent that in some instances the reference control points that are required for analysis became lost in background noise. This effectively halted the analysis and the recovery of any information contained within that experiment. To recover this data and to increase analytical veracity, the simple strategy of superimposing a template of reference control points onto the experimental array was developed. The utility of this tool is established in this communication.