Open AccessObjective method of comparing DNA microarray image analysis systems
Author(s) -
Edward L. Korn,
Jens K. Habermann,
Madhvi B. Upender,
Thomas Ried,
Lisa M. McShane
Publication year - 2004
Publication title -
biotechniques/biotechniques
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.617
H-Index - 131
eISSN - 1940-9818
pISSN - 0736-6205
DOI - 10.2144/04366bi01
Subject(s) - dna microarray , image processing , pixel , replicate , computer science , artificial intelligence , image (mathematics) , data mining , set (abstract data type) , complementary dna , pattern recognition (psychology) , computational biology , computer vision , biology , gene expression , genetics , gene , mathematics , statistics , programming language
Many image analysis systems are available for processing the images produced by laser scanning of DNA microarrays. The image processing system takes pixel-level intensity data and converts it to a set of gene-level expression or copy number summaries that will be used in further analyses. Image analysis systems currently in use differ with regard to the specific algorithms they implement, ease of use, and cost. Thus, it would be desirable to have an objective means of comparing systems. Here we describe a systematic method of comparing image processing results produced by different image analysis systems using a series of replicate microarray experiments. We demonstrate the method with a comparison of cDNA microarray data generated by the UCSF Spot and the GenePix ® image processing systems.