DNA Microarray Data Processing

This website provides a set of software tools to quantitate, process, and combine data from a set of experiments performed with a two-color DNA microarray. DNA microarrays provide an extremely powerful method for comparing mRNA abundances in one cell population relative to another and are now used pervasively throughout the molecular biology and genomics communities (background and more information may be found here or at gene-chips.com).

These tools are arranged in a pipeline. Starting with a set of scanned microarray images, tools may be invoked consecutively to ultimately produce an expression matrix, listing the mRNA ratio for each gene (matrix rows) in each experiment (matrix columns). Also provided is a statistic lambda for each gene and experiment, reflecting how likely it is that the gene is expressed differently between the two cell populations compared.

These tools are most useful when two or more replicate microarray experiments are available, providing two or more samples of expression (per gene per condition). In fact, lambda values are calculated only if replicate samples are available. In our own laboratory, we typically perform all experiments in quadruplicate (at the least), generating four microarray images per pair of conditions compared.

The tool pipeline, summarized in processOverview.README, is:

Microarray quantitation
see Usage
Background subtraction, normalization, and gene lookup
Combining data from replicated experiments
Assessment of variability and significance
Web page
see Usage
Combining data from multiple conditions


(1) These tools are distributed with ABSOLUTELY NO WARRANTY. However, we hope that they are useful, and you are welcome to augment the source code yourself.

(2) These tools have been developed for the UNIX platform. Preprocess, mergeReps, and mergeConds are implemented as Perl scripts, while Dapple, Vera, and Sam are implemented as C++/C code. Vera and Sam are in addition available for Windows operating systems.

Please contact webmaster@systemsbiology.org with any additions or corrections