Microarray data quality control

Quality Assurance/Quality Control parameter and metrics to ensure data reproducibility, e.g. the establishment of calibrated RNA samples and reference datasets to objectively assess the performance of different microarray platforms (see also MAQC project http //w w w.nature. com/nbt/focus/maqc/). 

Hessner, M.J., Wang, X., Khan, S., Meyer, L., Schlicht, M., Tackjes, J., Datta, M.W, Jacob, H.J., and Ghosh, S., Use of a three-color cDNA microarray platform to measure and control support-bound probe for improved data quality and reproducibility. Nucleic Acid Res., 31(11), 1-9, 2003b. 

Wang, X., Ghosh, S., and Guo, S.W., Quantitative quality control in microarray image processing and data acquistion, Nucleic Acid Res., 29(15), 1-8, 2001. 

Shi Letal(2008) Reproducible and reliable microarray results through quality control good laboratory proficiency and appropriate data analysis practices are essential. Curr Opin Biotechnol 19 10-18. doi S0958-1669(07)00145-0 (pii)10.1016/j.copbio.2007.11.003... 

Chen JJ et al (2007) Reproducibility of microarray data a fiu-ther analysis of microarray quality control (MAQC) data. BMC Bioinformatics 8 412. doi 1471-2105-8-412 (pii) 10.1186/1471-2105-8-412... 

Analysis of microarray experiments spans many subjects including study design, quality control, normalization, data filtering, and result interpretation as depicted in Figure 6. 

We focus on the combination of transcriptomics and metabolomics and more specifically on microarray data, which is currently the most used method for gene expression profiling and is used on a routine basis. In the first paragraphs, we briefly revise the extraction of mRNA or metabolites, their measurement, quality control of data, and analysis methods. Afterward two different types of data fusion and recent tools and publications are reviewed, followed by visualization methods for obtained data. Lastly, the metabolite annotation Web server MassTRIX is presented. This Web server allows combined analysis of transcriptomic and metabolomic data in the context of metabolic pathways. We compared the metabolomics part against similar tools and give a short outlook on the next version of MassTRIX, MassTRIX 4. 

Several projects and consortia were established in order to solve the above-mentioned problems, e.g., the Micro Array Quality Control (MAQC) project, led by US FDA, which main goal is to assess microarray study variability and to develop standards and quality measures for transcriptomics data [50, 51], Another research project, the human embryonic stem cell-derived novel alternative test systems (ESNATS) recently published a paper to address similar questions using human embryonic stem cell-based in vitro test systems for reproductive toxicity by transcriptomics analysis [52], The strong aspect of this study, that it transparently presents difficulties, such as batch effects, and provides analysis strategies including overrepresented transcription factors. It can be used as basis for further development of reproductive toxicity assays based on transcriptomics analysis. 

Fig. 3 RNA interference screens using cell arrays. siRNAs are spotted using a spotting robot at a high density on a microscopic slide (A). The quality of the generated microarray can be controlled by detection of the fluorescence from rhodamine-labeled siRNA (B). Efficiency of siRNA transfection can be monitored on a single-cell level using DAPl-counter-staining of nuclei (D). (Vanhecke et at, unpublished data)...

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