АНАЛИЗ ЭКСПРЕССИИ ГЕНОВ В РЕЗУЛЬТАТЕ ВОЗДЕЙСТВИЯ ИНТЕРФЕРОНА IFN-γ НА КЛЕТКУ С ИСПОЛЬЗОВАНИЕМ ПРОГРАММНОГО ПАКЕТА GeneExpressionAnalyser
Предлагается программный пакет GeneExpressionAnalyser для анализа данных, полученных в ходе проведения экспериментов с использованием биочипов ДНК. Детально рассмотрены алгоритмы предварительного анализа данных, выделения дифференциально-выраженных генов и анализа биологических функций клетки. Работоспособность пакета исследуется на примере опубликованных экспериментальных данных, представляющих результаты эксперимента по ис-следованию изменений экспрессии генов в клетке меланомы под воздействием интерферона IFN-? с течением времени.
1. Свешникова, А.Н. Экспрессия генов и микрочипы: проблемы качественного анализа / А. Н. Свешникова, П.С. Иванов // Рос. хим. ж. – 2007. – Т. 51 (1). – C. 127–135.
2. Maciejewski, H. Gene set analysis methods: statistical models and methodological differ-ences / H. Maciejewski // Brief Bioinform. – 2013. – Feb. 14. – P. 1–15.
3. Assessment of gene set analysis methods based on microarray data / H.A. Majd [et al.] // Gene. – 2013. – Vol. 534. – P. 383–389.
4. SplicerEX: a tool for the automated detection and classification of mRNA changes from con-ventional and splice-sensitive microarray expression data / T.J. Robinson [et al.] // RNA. – 2012. – Vol. 18(8). – P. 1435–1445.
5. BEAT: Bioinformatics Exon Array Tool to store, analyze and visualize Affymetrix GeneChip Human Exon Array data from disease experiments / A. Consiglio [et al.] // BMC Bioinformatics. – 2012 – 13(Suppl 4): S21. – P. 1–14.
6. Bar-Joseph, Z. Studying and modelling dynamic biological processes using time-series gene expression data / Z. Bar-Joseph, A. Gitter, A. Simon // Nature Reviews Genetics. – 2012. – Vol. 13. – P. 552–564.
7. Mehta, J.P. Software and tools for microarray data analysis / J.P. Mehta, S. Rani // Methods Mol Biol. – 2011. – Vol. 784. – P. 41–53.
8. Pathway analysis software: annotation errors and solutions / N.K. Henderson-Maclennan [et al.] // Mol Genet Metab. – 2010. – Vol. 101(2–3) – P. 134–140.
9. Brian, S. E. Handbook of Statistical Analyses Using R / S.E. Brian, T.A. Hothorn. – Chap-man and Hall/CRC, 2009. – 376 p.
10. Bioconductor: open software development for computational biology and bioinformatics / R.G. Gentleman [et al.] // Genome Biology – 2004. – Feb. 14. – P. 80.1–80.16
11. Count-based differential expression analysis of RNA sequencing data using R and Biocon-ductor / S. Anders [et al.] // Nat Protoc. – 2013. – № 8(9). – P. 1765–1786.
12. BeadArray Expression Analysis Using Bioconductor / M. Dunning [et al.] // PLoSComput Biol. – 2011. – № 7(12). – P. 1–39.
13. Coral: an integrated suite of visualizations for comparing clusterings/ D. Filippova, A. Gadani, C. Kingsford // BMC Bioinformatics – 2012. – Vol. 13:276. – P. 1–13.
14. DMET-Analyzer: automatic analysis of Affymetrix DMET Data / P.N. Guzzi [et al.] // BMC Bioinformatics – 2012. – Vol. 13:258. – P. 1–10.
15. eXframe: reusable framework for storage, analysis and visualization of genomics experi-ments/ A.U. Sinha [et al.] // BMC Bioinformatics – 2011. – Vol. 12:452. – P. 1–13.
16. Next Generation Sequencing & Microarray Data Analysis Software | Partek Incorporated [Electronic resource]. – 2013. – Mode of access : http://www.partek.com. – Date of access : 15.11.2013.
17. Ingenuity IPA – Integrate and understand complex omnics data [Electronic resource]. – 2013. – Mode of access : http://www.ingenuity.com/products/ipa. – Date of access : 16.11.2013.
18. GoMiner: a resource for biological interpretation of genomic and proteomic data / B.R. Zeeberg [et al.] // Genome Biol. – 2003. – Vol. 4 (4). – Art. R28. – P. 1–8.
19. Interplay of microRNAs, transcription factors and target genes: linking dynamic expression changes to function / P.V. Nazarov [et al.] // Nucleic Acids Research. – 2013. – Vol. 41(5). – P. 2817–2831.
20. Exploration, Normalization, and Summaries of High Density Oligonucleotide Array Probe Level Data / R.A. Irizarry [et al.] // Biostatistics. – 2003. – Vol. 4(2). – P. 249–264.
21. Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation / S. Dudout [et al.] // Nucleic Acids Research. Oxford University Press. – 2002. – Vol. 30, 4 e15. – P. 1–10.
22. Comparison of Affymetrix data normalization methods using 6,926 experiments across five array generations / R. Autio [et al.] // BMC Bioinformatics. – 2009. – 10 (Suppl 1): S24. – P. 1–12.
23. Analysis of boutique arrays: A universal method for the selection of the optimal data nor-malization procedure / B. Uszczyńska [et al.] // Mol. Med. – 2013. – Sep. 32(3). – P. 668–684.
24. Bra´s, Lı´gia P. Improving cluster-based missing value estimation / Lı gia P. Br s, Jo-s C. Menezes // Biomolecular Engineering. – 2007. – Т. 24. – P. 273–282.
25. Tusher, V.G. Significance analysis of microarrays applied to the ionizing radiation response / V.G. Tusher, R. Tibshirani, G. Chu // PNAS. – 2001. – Vol. 98,9. – P. 5116–5121.
26. Speed, T. Statistical Analysis of Gene Expression Microarray Data: Clustering Microarray-Data / T. Speed // Chapman and Hall/CRC. – 2005. – 240 p.
27. Прикладная статистика: классификация и снижение размерности : справ. изд. / С.А. Айвазян [и др.]. – М. : Финансы и статистика, 1989. – 607 с.
28. The Gene Ontology [Electronic resource]. – 2013. – Mode of access : http://www.geneontology.org. – Date of access : 15.11.2013.
29. High-Throughput GoMiner, an 'industrial-strength' integrative gene ontology tool for interpre-tation of multiple-microarray experiments, with application to studies of Common Variable Immune De-ficiency (CVID) / B.R. Zeeberg [et al.] // BMC Bioinformatics. – 2005. – Vol. 6; 168. – P. 1–18.
30. Molecular Devices Launches the GenePix(R) SL50 Slide Loader and GenePix(R) Pro 7.2 Software // PR Newswire Europe Including UK Disclose [Electronic resource]. – 2011. – Mode of access : http://www.prnewswire.co.uk/news-releases/molecular-devices-launches-the-genepixr-sl50-slide-loader-and-genepixr-pro-72-software-145284555.html. – Date of access : 16.11.2013.
31. Home | Affymetrix [Electronic resource]. – 2013. – Mode of access : http://www.affymetrix.com. – Date of access : 13.11.2013.
32. Advanced spot quality analysis in two-colour microarray experiments / M. Yatskou [et al.] // BMC Research Notes. – 2008. – Vol. 1:80. – P. 1–13.
33. Dynamic regulation of microRNA expression following Interferon-γ-induced gene tran-scription / S. Reinsbach [et al.] // RNA Biology. – 2012. – Vol. 9:7. – P. 978–989.
34. Samr: SAM: Significance Analysis of Microarrays [Electronic resource]. – 2011. – Mode of access : http://cran.r-project.org/web/packages/samr/samr.pdf. – Date of access : 13.11.2013.
35. Data Mining Practical Machine Learning Tools and Techniques / Ian H. Witten [et al.]. – The Morgan Kaufmann Series in Data Management Systems, 2011. – 664 p.
36. Hyvarinen, F. Independent Component Analysis / F. Hyvarinen. – Wiley series, 2001. – 505 p.
37. Разработка метода главных компонент для анализа микрочипов ДНК / A.B. Саечни-ков // 69-я научная конф. студентов и аспирантов БГУ : тез. докл. – Минск, 2012. – C. 268–272.
38. Саечников, А.В. Программный пакет GeneExpressionAnalyser для анализа микрочи-пов ДНК / А.В. Саечников, Н.Н. Яцков, В.В. Апанасович // Медэлектроника 2012 : тез. докл. – Минск, 2012. – C. 79–81.
39. Novikov, E. An algorithm for automatic evaluation of the spot quality in two-color DNA mi-croarray experiments / E. Novikov, E. Barillot // BMC Bioinformatics. – 2005. – Vol. 6: 293. – P. 1–18.
40. Uragun, B. The discrimination of interaural level difference sensitivity functions: develop-ment of a taxonomic data template for modelling / B. Uragun, R. Rajan // BMC Neuroscience. – 2013. – Vol. 14: 144. – P. 1–19.