Machine learning in low-level microarray analysis
ACM SIGKDD Explorations Newsletter
Bioinformatics
Micro-Analyzer: Automatic preprocessing of Affymetrix microarray data
Computer Methods and Programs in Biomedicine
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DNA microarrays are used to efficiently measure levels of expression of genes by enabling the scan of the whole genome in a single experiment, through the use of a single chip. In Human specie, a microarray analysis allows the measurement of up to 30000 different genes expressions for each sample. Data extracted from chips are preprocessed and annotated using vendor provided tools and then mined. Many algorithms and tools have been introduced to extract biological information from microarray data, nevertheless, they often are not able to automatically import raw data generated by recent arrays, such as the Affymetrix ones. The paper presents a software tool for the automatic summarization and annotation of Affymetrix binary data. It is provided as an extension of TIGR M4 (TM4), a popular software suite for microarray data analysis, and enables the operator to directly load, summarize and annotate binary microarray data avoiding manual preprocessing. Preprocessed data is organized in annotated matrices suitable for TM4 analysis and visualization.