Array Analysis Manager—An automated DNA microarray analysis tool simplifying microarray data filtering, bias recognition, normalization, and expression analysis. Issue 8 (12th June 2017)

• Record Type: Journal Article
• Authors: von der Haar, Marcel; Lindner, Patrick; Scheper, Thomas; Stahl, Frank
• Is Part Of: Engineering in life sciences. Volume 17:Issue 8(2017)
• Page Start: 841
• Page End: 846
• Publication Date: 2017-06-12
• Subjects: ANOVA -- Artificial Neural Networks -- DNA microarrays -- Photobleaching -- Transcriptomics; Bioengineering -- Periodicals; 660.605
• DOI: 10.1002/elsc.201700046
• Languages: English
• ISSNs: 1618-0240

Abstract

Abstract : Desoxyribonucleic acid (DNA) microarray experiments generate big datasets. To successfully harness the potential information within, multiple filtering, normalization, and analysis methods need to be applied. An in‐depth knowledge of underlying physical, chemical, and statistical processes is crucial to the success of this analysis. However, due to the interdisciplinarity of DNA microarray applications and experimenter backgrounds, the published analyses differ greatly, for example, in methodology. This severely limits the comprehensibility and comparability among studies and research fields. In this work, we present a novel end‐user software, developed to automatically filter, normalize, and analyze two‐channel microarray experiment data. It enables the user to analyze single chip, dye‐swap, and loop experiments with an extended dynamic intensity range using a multiscan approach. Furthermore, to our knowledge, this is the first analysis software solution, that can account for photobleaching, automatically detected by an artificial neural network. The user gets feedback on the effectiveness of each applied normalization regarding bias minimization. Standardized methods for expression analysis are included as well as the possibility to export the results in the Gene Expression Omnibus (GEO) format. This software was designed to simplify the microarray analysis process and help the experimenter to make educated decisions about the analysis process to contribute to reproducibility and comparability.