An application of logistic regression model to the study of constitutional imbalances in human chromosomal fragile sites

Abstract

Chromosomal fragile sites (CFSs) are loci or regions susceptible to spontaneous or induced occurrence of breaks and rearrangements. They are classified in two main categories, rare and common, depending on their frequency in the population. In order to identify which CFSs are influential or significant in the occurrence of deletions and duplications (chromosomal constitutional imbalances), we propose a logistic regression analysis for the CFS data set, since the underlying response variable is categorical, specifically binary (deletion or duplication). Some results are presented here as an informative preliminary contribution to understand the frailty of these CFS in increasing/decreasing of the deletion odds. This study has implications for our comprehension of human pathogenesis.

KEYWORDS:

• Chromosomal fragile sites
• deletions
• duplications
• logistic regression model

Acknowledgments

This study makes use of data generated by the DECIPHER community. A full list of centers who contributed to the generation of the data is available from http://decipher.sanger.ac.uk and via email from [email protected]. We also thank two anonymous referees and the editor for their helpful comments and suggestions that have substantially improved the presentation of this article.

Data availability statement

The data that support the findings of this study are available from the corresponding author, [Prata Gomes], upon reasonable request.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work is funded by national funds through the FCT - Fundação para a Ciência e a Tecnologia, I.P., under the scope of the projects UIDB/00297/2020 (https://doi.org/10.54499/UIDB/00297/2020) and UIDP/00297/2020 (https://doi.org/10.54499/UIDP/00297/2020) (Center for Mathematics and Applications), UIDB/00006/2020 (https://doi.org/10.54499/UIDB/00006/2020) and UIDP/00006/2020 (https://doi.org/10.54499/UIDP/00006/2020) (CEAUL - Centre of Statistics and its Applications) and UID/BIM/00009/2016 (Centre for Toxicogenomics and Human Health (TOXOMICS)).