A deep learning framework for characterization of genotype data.

ABSTRACT: Dimensionality reduction is a data transformation technique widely used in various fields of genomics research. The application of dimensionality reduction to genotype data is known to capture genetic similarity between individuals, and is used for visualization of genetic variation, identification of population structure as well as ancestry mapping. Among frequently used methods are principal component analysis, which is a linear transform that often misses more fine-scale structures, and neighbor-graph based methods which focus on local relationships rather than large-scale patterns. Deep learning models are a type of nonlinear machine learning method in which the features used in data transformation are decided by the model in a data-driven manner, rather than by the researcher, and hav

SUBMITTER: Ausmees K 

PROVIDER: S-EPMC8896001 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature