Array Analysis Manager-An automated DNA microarray analysis tool simplifying microarray data filtering, bias recognition, normalization, and expression analysis

被引:3
|
作者
von der Haar, Marcel [1 ]
Lindner, Patrick [1 ]
Scheper, Thomas [1 ]
Stahl, Frank [1 ]
机构
[1] Leibniz Univ Hannover, Inst Tech Chem, Callinstr 5, D-30167 Hannover, Germany
来源
ENGINEERING IN LIFE SCIENCES | 2017年 / 17卷 / 08期
关键词
ANOVA; Artificial Neural Networks; DNA microarrays; Photobleaching; Transcriptomics; GENE-EXPRESSION; TECHNOLOGY; IMPACT;
D O I
10.1002/elsc.201700046
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
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.
引用
收藏
页码:841 / 846
页数:6
相关论文
共 50 条
  • [1] Analysis of DNA microarray expression data
    Simon, Richard
    [J]. BEST PRACTICE & RESEARCH CLINICAL HAEMATOLOGY, 2009, 22 (02) : 271 - 282
  • [2] GenePublisher: automated analysis of DNA microarray data
    Knudsen, S
    Workman, C
    Sicheritz-Ponten, T
    Friis, C
    [J]. NUCLEIC ACIDS RESEARCH, 2003, 31 (13) : 3471 - 3476
  • [3] The effect of normalization on microarray data analysis
    Ding, YY
    Wilkins, D
    [J]. DNA AND CELL BIOLOGY, 2004, 23 (10) : 635 - 642
  • [4] Control analysis of DNA microarray expression data
    Curtis, RK
    Brand, MD
    [J]. MOLECULAR BIOLOGY REPORTS, 2002, 29 (1-2) : 67 - 71
  • [5] Control Analysis of DNA Microarray Expression Data
    R. Keira Curtis
    Martin D. Brand
    [J]. Molecular Biology Reports, 2002, 29 : 67 - 71
  • [6] SED, a normalization free method for DNA microarray data analysis
    Wang, HJ
    Huang, H
    [J]. BMC BIOINFORMATICS, 2004, 5 (1)
  • [7] SED, a normalization free method for DNA microarray data analysis
    Huajun Wang
    Hui Huang
    [J]. BMC Bioinformatics, 5
  • [8] Microarray Data Analysis Toolbox (MDAT): for normalization, adjustment and analysis of gene expression data
    Knowlton, N
    Dozmorov, IM
    Centola, M
    [J]. BIOINFORMATICS, 2004, 20 (18) : 3687 - 3690
  • [9] Analysis of DNA microarray data
    Hackl, H
    Cabo, FS
    Sturn, A
    Wolkenhauer, O
    Trajanoski, Z
    [J]. CURRENT TOPICS IN MEDICINAL CHEMISTRY, 2004, 4 (13) : 1357 - 1370
  • [10] Development of a novel microarray data analysis tool without normalization for genotyping degraded forensic DNA
    Yagasaki, Kayoko
    Nishida, Nao
    Mabuchi, Akihiko
    Tokunaga, Katsushi
    Fujimoto, Akihiro
    [J]. FORENSIC SCIENCE INTERNATIONAL-GENETICS, 2023, 65