Multifactorial Dimensionality Reduction for Disordered Trait

Alexander Rakitko

2015

Abstract

We develop our recent works concerning the identification of the factors associated with a certain complex disease. The case of disordered discrete trait is studied. We build two models (3D and 2D) for the range of response variable indicating the state of the health of a patient. In this work we consider the problem of optimal forecast for response variable depending on a finite collection of factors with values in arbitrary finite set. The quality of prediction is described by the error function involving a penalty function. The estimation of the error requires some cross-validation procedure. The developed approach provides the basis to identify the set of significant factors. Such problem arises naturally, e.g., in the genome-wide association study. Using simulated data we illustrate the efficiency of our method.

Paper Citation

in Harvard Style

Rakitko A. (2015). Multifactorial Dimensionality Reduction for Disordered Trait . In Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2015) ISBN 978-989-758-070-3, pages 232-236. DOI: 10.5220/0005285302320236

in Bibtex Style

@conference{bioinformatics15,
author={Alexander Rakitko},
title={Multifactorial Dimensionality Reduction for Disordered Trait},
booktitle={Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2015)},
year={2015},
pages={232-236},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005285302320236},
isbn={978-989-758-070-3},
}

in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2015)
TI - Multifactorial Dimensionality Reduction for Disordered Trait
SN - 978-989-758-070-3
AU - Rakitko A.
PY - 2015
SP - 232
EP - 236
DO - 10.5220/0005285302320236