Functional data analysis of “Omics” data: how does the genomic landscape influence integration and fixation of endogenous retroviruses?

Marzia A. Cremona; Rebeca Campos-Sánchez; Alessia Pini; Simone Vantini; Kateryna D. Makova; Francesca Chiaromonte

doi:10.1007/978-3-319-55846-2_12

Functional data analysis of “Omics” data: how does the genomic landscape influence integration and fixation of endogenous retroviruses?

Marzia A. Cremona
, Rebeca Campos-Sánchez
, Alessia Pini
, Simone Vantini
, Kateryna D. Makova
, Francesca Chiaromonte

Research output: Chapter in Book/Report/Conference proceeding › Chapter

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 functional logistic regression, with the aim of gaining insights on the effects of genomic landscape features on the integration and fixation of endogenous retroviruses.

Original language	English
Title of host publication	Functional Statistics and Related Fields
Editors	G. Aneiros, E. Bongiorno, R. Cao, P. Vieu
Pages	87-93
Number of pages	7
DOIs	https://doi.org/10.1007/978-3-319-55846-2_12
Publication status	Published - 2017

Keywords

Genomics
Human genome
endogenous retroviruses
functional data analysis

Access to Document

10.1007/978-3-319-55846-2_12

Cite this

Cremona, M. A., Campos-Sánchez, R., Pini, A., Vantini, S., Makova, K. D., & Chiaromonte, F. (2017). Functional data analysis of “Omics” data: how does the genomic landscape influence integration and fixation of endogenous retroviruses? In G. Aneiros, E. Bongiorno, R. Cao, & P. Vieu (Eds.), Functional Statistics and Related Fields (pp. 87-93) https://doi.org/10.1007/978-3-319-55846-2_12

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title = "Functional data analysis of “Omics” data: how does the genomic landscape influence integration and fixation of endogenous retroviruses?",

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 functional logistic regression, with the aim of gaining insights on the effects of genomic landscape features on the integration and fixation of endogenous retroviruses.",

keywords = "Genomics, Human genome, endogenous retroviruses, functional data analysis, Genomics, Human genome, endogenous retroviruses, functional data analysis",

author = "Cremona, \{Marzia A.\} and Rebeca Campos-S{\'a}nchez and Alessia Pini and Simone Vantini and Makova, \{Kateryna D.\} and Francesca Chiaromonte",

year = "2017",

doi = "10.1007/978-3-319-55846-2\_12",

language = "English",

isbn = "978-3-319-55845-5",

pages = "87--93",

editor = "G. Aneiros and E. Bongiorno and R. Cao and P. Vieu",

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