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MOTIVATION This paper presents a global test to be used for the analysis of microarray data. Using this test it can be determined whether the global expression pattern of a group of genes is significantly related to some clinical outcome of interest. Groups of genes may be any size from a single gene to all genes on the chip (e.g. known pathways, specific(More)
MOTIVATION Many statistical tests have been proposed in recent years for analyzing gene expression data in terms of gene sets, usually from Gene Ontology. These methods are based on widely different methodological assumptions. Some approaches test differential expression of each gene set against differential expression of the rest of the genes, whereas(More)
This article presents a novel algorithm that efficiently computes L(1) penalized (lasso) estimates of parameters in high-dimensional models. The lasso has the property that it simultaneously performs variable selection and shrinkage, which makes it very useful for finding interpretable prediction rules in high-dimensional data. The new algorithm is based on(More)
In genome-wide association studies (GWAS) of complex traits, single SNP analysis is still the most applied approach. However, the identified SNPs have small effects and provide limited biological insight. A more appropriate approach to interpret GWAS data of complex traits is to analyze the combined effect of a SNP set grouped per pathway or gene region. We(More)
MOTIVATION A recent surge of interest in survival as the primary clinical endpoint of microarray studies has called for an extension of the Global Test methodology to survival. RESULTS We present a score test for association of the expression profile of one or more groups of genes with a (possibly censored) survival time. Groups of genes may be pathways,(More)
BACKGROUND Respiratory syncytial virus (RSV) is a common cause of severe lower respiratory tract infection in infants. Only a proportion of children infected with RSV require hospitalization. Because known risk factors for severe disease, such as premature birth, cannot fully explain differences in disease severity, genetic factors have been implicated. (More)
MicroRNAs (miRNAs), non-coding RNAs regulating gene expression, are frequently aberrantly expressed in human cancers. Next-generation deep sequencing technology enables genome-wide expression profiling of known miRNAs and discovery of novel miRNAs at unprecedented quantitative and qualitative accuracy. Deep sequencing was performed on 11 fresh frozen clear(More)
Owing to our lack of understanding of the factors that constitute protective immunity during natural infection with Mycobacterium tuberculosis (Mtb), there is an urgent need to identify host biomarkers that predict long-term outcome of infection in the absence of therapy. Moreover, the identification of host biomarkers that predict (in)adequate response to(More)
OBJECTIVE Identify gene expression profiles associated with OA processes in articular cartilage and determine pathways changing during the disease process. METHODS Genome wide gene expression was determined in paired samples of OA affected and preserved cartilage of the same joint using microarray analysis for 33 patients of the RAAK study. Results were(More)
The choice for a polyadenylation site determines the length of the 3'-untranslated region (3'-UTRs) of an mRNA. Inclusion or exclusion of regulatory sequences in the 3'-UTR may ultimately affect gene expression levels. Poly(A) binding protein nuclear 1 (PABPN1) is involved in polyadenylation of pre-mRNAs. An alanine repeat expansion in PABPN1 (exp-PABPN1)(More)