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Matematicheskaya Biologiya i Bioinformatika, 2013, Volume 8, Issue 2, Pages 520–528
(Mi mbb159)
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Bioinformatics
Statistical Analysis of Radiation-Induced Dynamics of Cancer Cell Transcriptome Using Dna-Microarray Data
R. T. Sibatova, Ju. V. Saenkoa, V. V. Uchajkina, V. V. Saenkoa, E. V. Morozovaa, V. V. Shulezhkoa, E. V. Kozhemjakinaa, A. N. Byzykchia, G. G. Gusarova, D. A. Korobkoa, I. V. Jarovikovaa, K. V. Saltykovaa, I. I. Kozhemjakinb, V. M. Juravleva, A. V. Juravleva, N. K. Aynullovaa a Ulyanovsk State University, Ulyanovsk, Russia Federation, Ulyanovsk, Russia
b Lomonosov Moscow State University, Faculty of Computational Mathematics and Cybernetics MSU, Moscow, Russia
Abstract:
The DNA microarray data on radiation-induced dynamics of the transcriptome of cancer cell line HCT116 with normal and mutant gene TP53 is processed. Transcriptome is analyzed after 1, 12 and 24 hours after irradiation using the Affymetrix microarray HGU133A series. It was found that the probability characteristics of expression differences depend strongly on the intensities of the reference level, and this dependence is nonlinear in general case. We take this fact into account using the “noise envelope” algorithm in filtering, clustering and grouping. The effectiveness of the procedures can be estimated from the results of hierarchical clustering and using the method of group averages. For filtered genes, dendrograms are constructed, a preliminary comparison of gene dynamics in key signaling pathways associated with programmed cell death and DNA repair is provided.
Key words:
DNA microarray, gene expression, hierarchical clustering, method of group averages.
Received 03.09.2013, Published 31.10.2013
Citation:
R. T. Sibatov, Ju. V. Saenko, V. V. Uchajkin, V. V. Saenko, E. V. Morozova, V. V. Shulezhko, E. V. Kozhemjakina, A. N. Byzykchi, G. G. Gusarov, D. A. Korobko, I. V. Jarovikova, K. V. Saltykova, I. I. Kozhemjakin, V. M. Juravlev, A. V. Juravlev, N. K. Aynullova, “Statistical Analysis of Radiation-Induced Dynamics of Cancer Cell Transcriptome Using Dna-Microarray Data”, Mat. Biolog. Bioinform., 8:2 (2013), 520–528
Linking options:
https://www.mathnet.ru/eng/mbb159 https://www.mathnet.ru/eng/mbb/v8/i2/p520
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