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.
|Titolo della pubblicazione ospite||Functional Statistics and Related Fields|
|Editor||G. Aneiros, E. Bongiorno, R. Cao, P. Vieu|
|Numero di pagine||7|
|Stato di pubblicazione||Pubblicato - 2017|
- Human genome
- endogenous retroviruses
- functional data analysis