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Transcriptograms: a genome-wide gene expression analysis method. (English) Zbl 1478.92060

Da Silva, Fabrício Alves Barbosa (ed.) et al., Networks in systems biology. Applications for disease modeling. Translated contributions of the 3rd international course on theoretical and applied aspects of systems biology, Rio de Janeiro, Brazil 2019. Cham: Springer. Comput. Biol. 32, 69-91 (2020).
Summary: In this chapter, we discuss the transcriptogram method for statistically analyzing differential gene expression in a genome-wide profile. This technique suggests a method to hierarchically interrogate the data and, subsequently, narrow down to gene level. We present the method, discuss its reproducibility and enhanced signal-to-noise ratio, and discuss its application in investigating time series data as in cell cycle, therapy gene target identification, lineage and tissue classification and as a powerful test to identify error and assess the quality of normalization procedures. We finally present the software ready for download and discuss the R-plugin for BioConductor.
For the entire collection see [Zbl 1470.92007].

MSC:

92C40 Biochemistry, molecular biology
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