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Testing of Chromosomal Clumping of Gene Properties
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Luciano Fernandez-Ricaud
Published/Copyright:
February 26, 2009
Clumping of gene properties like expression or mutant phenotypes along chromosomes is commonly detected using completely random null-models where their location is equally likely across the chromosomes. Interpretation of statistical tests based on these assumptions may be misleading if dependencies exist that are unequal between chromosomes or in different chromosomal parts. One such regional dependency is the telomeric effect, observed in several studies of Saccharomyces cerevisiae, under which e.g. essential genes are less likely to reside near the chromosomal ends.In this study we demonstrate that standard randomisation test procedures are of limited applicability in the presence of telomeric effects. Several extensions of such standard tests are here suggested for handling clumping simultaneously with regional differences in essentiality frequencies in sub-telomeric and central gene positions. Furthermore, a general non-homogeneous discrete Markov approach for combining parametrically modelled position dependent probabilities of a dichotomous property with a simple single parameter clumping is suggested. This Markov model is adapted to the observed telomeric effects and then simulations are used to demonstrate properties of the suggested modified randomisation tests. The model is also applied as a direct alternative tool for statistical analysis of the S. cerevisiae genome for clumping of phenotypes.
Keywords: statistical tests; Markov chains; genome biology; S. cerevisiae; clumping of essential genes
Published Online: 2009-2-26
©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston
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Keywords for this article
statistical tests;
Markov chains;
genome biology;
S. cerevisiae;
clumping of essential genes
Articles in the same Issue
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- Orthology-Based Multilevel Modeling of Differentially Expressed Mouse and Human Gene Pairs
- Sequential Analysis for Microarray Data Based on Sensitivity and Meta-Analysis
- Dimension Reduction of Microarray Data in the Presence of a Censored Survival Response: A Simulation Study
- A Nonlinear Mixed-Effects Model for Estimating Calibration Intervals for Unknown Concentrations in Two-Color Microarray Data with Spike-Ins
- Composite Likelihood Modeling of Neighboring Site Correlations of DNA Sequence Substitution Rates
- A Multiple Testing Approach to High-Dimensional Association Studies with an Application to the Detection of Associations between Risk Factors of Heart Disease and Genetic Polymorphisms
- Hypothesis Tests for Point-Mass Mixture Data with Application to `Omics Data with Many Zero Values
- Inferring Dynamic Genetic Networks with Low Order Independencies
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- Modified FDR Controlling Procedure for Multi-Stage Analyses
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- Score Statistics for Mapping Quantitative Trait Loci
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- Balanced Gradient Boosting from Imbalanced Data for Clinical Outcome Prediction
- Univariate Shrinkage in the Cox Model for High Dimensional Data
- Multilevel Comparison of Dendrograms: A New Method with an Application for Genetic Classifications
- Weighted Multiple Hypothesis Testing Procedures
- Incorporating Duplicate Genotype Data into Linear Trend Tests of Genetic Association: Methods and Cost-Effectiveness
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