Optimizing pedigrees: a numerical approach
- Published
- Accepted
- Subject Areas
- Genetics, Mathematical Biology, Statistics
- Keywords
- Pedigree, Chi-Squared, Biasing System, Inheritance, Statistics, Algorithm
- Copyright
- © 2017 Ang
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2017. Optimizing pedigrees: a numerical approach. PeerJ Preprints 5:e2871v1 https://doi.org/10.7287/peerj.preprints.2871v1
Abstract
Pedigrees, though straightforward and versatile, lack the ability to tell us information about many individuals. For example, it is hard to distinguish carriers from unaffected individuals in pedigrees. In order to find such information, we must trace back and manually evaluate the tree, which is both cumbersome and inefficient. I have discovered a way to represent individuals in the pedigree using numbers, such that the probability of an individual inheriting a certain trait can be easily calculated from their parents.
Author Comment
Pedigrees are fundementally used to represent phenotypic data in a binary system. By using ’Black’ as affected and ’White’ as unaffected, the pedigree system is able to cover a wide range of inheritance systems. It also gives a general idea of the dispersion of the phenotype in question. A simple improvement to this existing model would be to assign scores instead of coloring. These scores would keep track of the chance that individuals hold certain traits which can be used to easily calculate the probability of child generations. This approach has many limitations, but the idea of such an implementation is very interesting and applicable.