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Phenotyping Genetic Diseases Using an Extension of µ-Scores for Multivariate Data
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José F. Morales
Published/Copyright:
June 30, 2008
As the field of genomics matures, more complex genotypes and phenotypes are being studied. Fanconi anemia (FA), for example, is an inherited chromosome instability syndrome with a complex array of variable disease phenotypes including congenital malformations, hematological manifestations, and cancer. To better understand specific aspects of the genetic etiology of FA and other rare diseases with complex phenotypes, it is often necessary to reduce the dimensions of the disease phenotype information. Towards this end, we extend a novel non-parametric approach to include information about a hierarchical structure among disease phenotypes. The proposed extension increases information content of the phenotype scores obtained and, thereby, the power of genotype-phenotype relationships studies.
Published Online: 2008-6-30
©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston
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Keywords for this article
multidimensional;
ranking;
Fanconi anemia;
censoring;
genotype;
phenotype;
non-parametric
Articles in the same Issue
- Article
- Self-Organizing Maps with Statistical Phase Synchronization (SOMPS) for Analyzing Cell Cycle-Specific Gene Expression Data
- Coalescent Time Distributions in Trees of Arbitrary Size
- Quantifying the Association between Gene Expressions and DNA-Markers by Penalized Canonical Correlation Analysis
- Nonparametric Functional Mapping of Quantitative Trait Loci Underlying Programmed Cell Death
- Accommodating Uncertainty in a Tree Set for Function Estimation
- Drifting Markov Models with Polynomial Drift and Applications to DNA Sequences
- Comparing the Characteristics of Gene Expression Profiles Derived by Univariate and Multivariate Classification Methods
- Calculating Confidence Intervals for Prediction Error in Microarray Classification Using Resampling
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- A SNP Streak Model for the Identification of Genetic Regions Identical-by-descent
- Detecting Two-Locus Gene-Gene Effects Using Monotonisation of the Penetrance Matrix
- Modeling DNA Methylation in a Population of Cancer Cells
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- Statistical Methods in Integrative Analysis for Gene Regulatory Modules
- Reducing Spatial Flaws in Oligonucleotide Arrays by Using Neighborhood Information
- Pattern Classification of Phylogeny Signals
- A Unification of Multivariate Methods for Meta-Analysis of Genetic Association Studies
- Importance Sampling for the Infinite Sites Model
- Supervised Distance Matrices
- Addressing the Shortcomings of Three Recent Bayesian Methods for Detecting Interspecific Recombination in DNA Sequence Alignments
- A Sparse PLS for Variable Selection when Integrating Omics Data
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