Scoring multiple toxicological endpoints using a toxicogenomic database.
作者： Naoki Kiyosawa , Yosuke Ando , Kyoko Watanabe , Noriyo Niino , Sunao Manabe
DOI: 10.1016/J.TOXLET.2009.03.011
关键词: Data quality 、 Biology 、 Bioinformatics 、 Database 、 DNA microarray 、 Toxicogenomics 、 Set (abstract data type) 、 Biomarker (medicine) 、 Chemical treatment 、 Microarray 、 Microarray analysis techniques
摘要: Abstract As information regarding microarray data sets and toxicogenomic biomarkers grows rapidly, the process of analyzing interpreting results is increasingly complicated. To facilitate analysis, a simple expression ratio-based scoring method called TGP1 score was previously proposed [Kiyosawa, N., Shiwaku, K., Hirode, M., Omura, Uehara, T., Shimizu, Mizukawa, Y., Miyagishima, Ono, A., Nagao, Urushidani, 2006. Utilization one-dimensional for surveying chemical-induced changes in levels multiple biomarker gene using large-scale toxicogenomics database. J. Toxicol. Sci. 31, 433–448]. Although has demonstrated its efficacy rapid comprehension sets, inclusion low quality set produced flaws calculated score. overcome this shortcoming, we tested new differentially expressed (D-score), where Detection Call as well signal log ratios generated by MAS5 algorithm on Affymetrix GeneChip were considered calculation. Four prototypical toxicants, namely acetaminophen, phenobarbital, clofibrate acetamidofluorene, used detailed analysis. A database (TG-GATEs) utilized reference set. The D-score successfully alleviated effects calculation, captured overall direction magnitude change level genes, highlighting affected toxicological endpoints elicited chemical treatment. will be useful high-throughput toxicity screening biomarkers.
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