We consider thousands of endogenous retrovirus detected in the human and mouse genomes, and quantify a large number of genomic landscape features at high resolution around their integration sites and in control regions. We propose to analyze this data employing a recently developed functional inferential procedure and func- tional logistic regression, with the aim of gaining insights on the effects of genomic landscape features on the integration and fixation of endogenous retroviruses.
Functional data analysis of omics data: how does the genomic landscape influence integration and fixation of endogenous retroviruses?
A. Pini;S. Vantini;
2017-01-01
Abstract
We consider thousands of endogenous retrovirus detected in the human and mouse genomes, and quantify a large number of genomic landscape features at high resolution around their integration sites and in control regions. We propose to analyze this data employing a recently developed functional inferential procedure and func- tional logistic regression, with the aim of gaining insights on the effects of genomic landscape features on the integration and fixation of endogenous retroviruses.File in questo prodotto:
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