Multiple testing has become an integral component in genomic analyses involving microarray experiments where a large number of hypotheses are tested simultaneously. However, before applying more computationally intensive methods, it is often desirable to complete an initial truncation of the...

Use of microarray technology often leads to high-dimensional and low-sample size (HDLSS) data settings. A variety of approaches have been proposed for variable selection in this context. However, only a small number of these have been adapted for time-to-event data where censoring is present....

Motivation: Transcriptomic studies using microarray technology have become a standard tool in life sciences in the last decade. Nevertheless the cost of these experiments remains high and forces scientists to work with small sample sizes at the expense of statistical power. In many cases, little...

Sequence data from a series of homologous DNA segments from related organisms are typically polymorphic at many sites, and these polymorphisms are the result of evolutionary processes. Such data may be used to estimate the substitution rates as well as the variability of these rates. Careful...

The problem of identifying differentially expressed genes in designed microarray experiments is considered. Lonnstedt and Speed (2002) derived an expression for the posterior odds of differential expression in a replicated two-color experiment using a simple hierarchical parametric model. The...

We describe a strategy for the analysis of experimentally derived gene expression signatures and their translation to human observational data. Sparse multivariate regression models are used to identify expression signature gene sets representing downstream biological pathway events following...

Proteomic mass spectrometry is gaining an increasing role in diagnostics and in studies on protein complexes and biological systems. This experimental technology is producing high-throughput data which is inherently noisy and may contain various errors. Mathematical processing can help in...

In this paper, we address the problem of detecting outlier samples with highly different expression patterns in microarray data. Although outliers are not common, they appear even in widely used benchmark data sets and can negatively affect microarray data analysis. It is important to identify...

Consider a sample of apparently unrelated individuals, for which marker genotype and phenotype data is available. When individuals are sampled on phenotypes, we propose an ascertained ancestral recombination graph (ARG) that models shared ancestry of the sample chromosomes given phenotype data...

We present an approach to association studies involving a dozen or so `response' variables and a few hundred `explanatory' variables which emphasizes transparency, simplicity, and protection against spurious results. The methods proposed are largely non-parametric, and they are systematically...