Editorial: Statistical genetics \& statistical genomics: where biology, epistemology, statistics, and computation collide
DOI10.1016/j.csda.2009.01.005zbMath1279.62020OpenAlexW1988560779WikidataQ57242438 ScholiaQ57242438MaRDI QIDQ961300
Peter M. Visscher, Christopher I. Amos, David B. Allison, Guilherme J. M. Rosa
Publication date: 30 March 2010
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.csda.2009.01.005
Applications of statistics to biology and medical sciences; meta analysis (62P10) Proceedings, conferences, collections, etc. pertaining to statistics (62-06) Collections of articles of miscellaneous specific interest (00B15) Proceedings, conferences, collections, etc. pertaining to biology (92-06)
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- A heavy-tailed empirical Bayes method for replicated microarray data
- Bayesian models for two-sample time-course microarray experiments
- A mixture model approach for the analysis of small exploratory microarray experiments
- A robust ratio estimator of gene expression via inverse-variance weighting for cDNA microarray images
- Survival prediction using gene expression data: a review and comparison
- Assumption adequacy averaging as a concept for developing more robust methods for differential gene expression analysis
- On the glog-normal distribution and its application to the gene expression problem
- Balancing type one and two errors in multiple testing for differential expression of genes
- A structural mixed model to shrink covariance matrices for time-course differential gene expression studies
- Optimizing design of two-stage experiments for transcriptional profiling
- Distribution modeling and simulation of gene expression data
- Combining quantitative trait loci analyses and microarray data: an empirical likelihood approach
- Modified linear discriminant analysis approaches for classification of high-dimensional microarray data
- The beta-binomial distribution for estimating the number of false rejections in microarray gene expression studies
- A robust unified approach to analyzing methylation and gene expression data
- Complexity control in a mixture model by the Hardy-Weinberg equilibrium
- Statistically appraising process quality of affinity isolation experiments
- Informative transcription factor selection using support vector machine-based generalized approximate cross validation criteria
- Selecting marker genes for cancer classification using supervised weighted kernel clustering and the support vector machine
- Simple Bayesian binary framework for discovering significant genes and classifying cancer diagnosis
- The use of plasmodes as a supplement to simulations: a simple example evaluating individual admixture estimation methodologies
- Excess false positive rate caused by population stratification and disease rate heterogeneity in case-control association studies
- Optimal designs to select individuals for genotyping conditional on observed binary or survival outcomes and non-genetic covariates
- Fast implementation of a scan statistic for identifying chromosomal patterns of genome wide association studies
- Utilizing identity-by-descent probabilities for genetic fine-mapping in population based samples, via spatial smoothing of haplotype effects
- Estimation of graphical models whose conditional independence graphs are interval graphs and its application to modelling linkage disequilibrium
- The power of linkage analysis of a disease-related endophenotype using asymmetrically ascertained sib pairs
- Parametric and semiparametric methods for mapping quantitative trait loci
- Deviance information criterion (DIC) in Bayesian multiple QTL mapping
- Application of information-theoretic tests for the analysis of DNA sequences based on Markov chain models
- Bayesian hidden Markov model for DNA sequence segmentation: a prior sensitivity analysis
- Transmission disequilibrium test (TDT) for a pair of linked marker loci
- Tests for Gaussian graphical models
- Exploration of distributional models for a novel intensity-dependent normalization procedure in censored gene expression data
- A semi-parametric approach for mixture models: application to local false discovery rate estimation
- Use of SVD-based probit transformation in clustering gene expression profiles
- Class prediction and gene selection for DNA microarrays using regularized sliced inverse regression
- High-dimensional pseudo-logistic regression and classification with applications to gene expression data
- Testing the significance of cell-cycle patterns in time-course microarray data using nonparametric quadratic inference functions
- Identify LD blocks based on hierarchical spatial data
- Classification of gene functions using support vector machine for time-course gene expression data
- New normalization methods using support vector machine quantile regression approach in microarray analysis
- Assessing agreement of clustering methods with gene expression microarray data
- Reproducibility of genotypes as measured by the affymetrix GeneChip\(^{\circledR}\) 100K human mapping array set
- EPISTEMOLOGY OF COMPUTATIONAL BIOLOGY: MATHEMATICAL MODELS AND EXPERIMENTAL PREDICTION AS THE BASIS OF THEIR VALIDITY
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