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.
| Lingua originale | Inglese |
|---|---|
| Titolo della pubblicazione ospite | Functional Statistics and Related Fields |
| Editor | G. Aneiros, E. Bongiorno, R. Cao, P. Vieu |
| Pagine | 87-93 |
| Numero di pagine | 7 |
| DOI | |
| Stato di pubblicazione | Pubblicato - 2017 |
Keywords
- Genomics
- Human genome
- endogenous retroviruses
- functional data analysis