Genetic epidemiology aims at identifying biological mechanisms responsible for human diseases. Genome-wide association studies, made possible by recent improvements in genotyping technologies, are now promisingly investigated. In these studies, common first-stage strategies focus on marginal...

In the exploding field of gene expression techniques such as DNA microarrays, there are still few general probabilistic methods for analysis of variance. Linear models and ANOVA are heavily used tools in many other disciplines of scientific research. The usual F-statistic is unsatisfactory for...

We present a novel, cost efficient two-phase design for predictive clinical gene expression studies: early marker panel determination (EMPD). In Phase-1, genome-wide microarrays are used only for a small number of individual patient samples. From this Phase-1 data a panel of marker genes is...

Inferring large-scale covariance matrices from sparse genomic data is an ubiquitous problem in bioinformatics. Clearly, the widely used standard covariance and correlation estimators are ill-suited for this purpose. As statistically efficient and computationally fast alternative we propose a...

Liquid Chromatography - Mass Spectrometry (LC-MS) is a powerful method for sensitive detection and quantification of proteins and peptides in complex biological fluids like serum. LC-MS produces complex data sets, consisting of some hundreds of millions of data points per sample at a resolution...

For situations where the number of tested hypotheses is increasingly large, the power to detect statistically significant multiple treatment effects decreases. As is the case with microarray technology, often researchers are interested in identifying differentially expressed genes for more than...

For testing multiple null hypotheses, the classical approach to dealing with the multiplicity problem is to restrict attention to procedures that control the familywise error rate (FWER), the probability of even one false rejection. In many applications, one might be willing to tolerate more...

The problem of relating genotype (as represented by amino acid sequence) to phenotypes is distinguished from standard regression problems by the nature of sequence data. Here we investigate an instance of such a problem where the phenotype of interest is HIV-1 replication capacity and contiguous...

Gene co-expression networks are increasingly used to explore the system-level functionality of genes. The network construction is conceptually straightforward: nodes represent genes and nodes are connected if the corresponding genes are significantly co-expressed across appropriately chosen...

Under the assumption that a significant motivation for sequencing the genomes of mammals is the resulting ability to help us locate and characterize functional DNA segments shared with humans, we have developed a statistical analysis to quantify the expected advantage. Examining uncertainty in...