References of "Van Steen, Kristel"
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See detailIPCAPS: an R package for iterative pruning to capture population structure
Chaichoompu, Kridsadakorn ULiege; Abegaz Yazew, Fentaw; Tongsima, Sissades et al

in Bioinformatics : Application Notes (in press)

Resolving population genetic structure is challenging, especially when dealing with closely related populations. Although Principal Component Analysis (PCA)-based methods and genomic var- iation with ... [more ▼]

Resolving population genetic structure is challenging, especially when dealing with closely related populations. Although Principal Component Analysis (PCA)-based methods and genomic var- iation with single nucleotide polymorphisms (SNPs) are widely used to describe shared genetic an- cestry, improvements can be made targeting fine-level population structure. This work presents an R package called IPCAPS, which uses SNP information for resolving possibly fine-level population structure. The IPCAPS routines are built on the iterative pruning Principal Component Analysis (ipP- CA) framework to systematically assign individuals to genetically similar subgroups. Our tool is able to detect and eliminate outliers in each iteration to avoid misclassification. It can be extended to de- tect subtle subgrouping in patients as well. In addition, IPCAPS supports different measurement scales for variables used to identify substructure. Hence, panels of gene expression and methylation data can be accommodated. [less ▲]

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See detailHaplotype information combined with iterative pruning PCA (ipPCA) to improve population clustering
Chaichoompu, Kridsadakorn ULiege; Fouladi, Ramouna; Wangkumhang, Pongsakorn et al

Scientific conference (2014, April 01)

Single Nucleotide Polymorphisms (SNPs) are commonly used to capture variations between populations. Often genome-wide SNP data are pruned based on linkage disequilibrium (LD) patterns or small subsets of ... [more ▼]

Single Nucleotide Polymorphisms (SNPs) are commonly used to capture variations between populations. Often genome-wide SNP data are pruned based on linkage disequilibrium (LD) patterns or small subsets of SNPs are selected (e.g. PCA-correlated SNPs) to reproduce the genomic structure of the complete data set. Identifying and differentiating between subpopulations using such a reduced set can become challenging, especially when similar geographic regions are involved or when spurious patterns are likely to exist. Although PCA-based methods can resolve structure, they cannot infer ancestry. On the other hand, the structure of haplotypes in unrelated individuals can reveal useful information about genetic ancestry. Notably, haplotype composition and the pattern of LD between markers may vary between larger populations but may also play a role within more confined geographic regions. In addition, iterative pruning principal component analysis (ipPCA) has been shown to be a powerful tool to cluster subpopulations based on SNP profiles. Despite the complexities that are associated with haplotype inference, we argue that added value can be obtained when the LD structure between SNPs is exploited in the search for relevant population strata. In this work, we propose to combine an LD-based novel haplotype encoding scheme with the ipPCA machinery to retrieve fine population substructures. The approach is compared to state-of-the-art methods in the context of population substructure and admixture analysis. [less ▲]

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See detailModel-Based Multifactor Dimensionality Reduction to detect epistasis for quantitative traits in the presence of error-free and noisy data
Mahachie John, Jestinah ULiege; Van Lishout, François; Van Steen, Kristel

Poster (2010, October)

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See detailAnalysis of the high affinity IgE receptor genes reveals epistatic effects of FCER1A variants on eczema risk
Mahachie John, Jestinah ULiege; Baurecht, H.; Rodriguez, E. et al

in Allergy (2010), 65(7), 875-882

To cite this article: Mahachie John JM, Baurecht H, Rodriguez E, Naumann A, Wagenpfeil S, Klopp N, Mempel M, Novak N, Bieber T, Wichmann H-E, Ring J, Illig T, Cattaert T, Van Steen K, Weidinger S ... [more ▼]

To cite this article: Mahachie John JM, Baurecht H, Rodriguez E, Naumann A, Wagenpfeil S, Klopp N, Mempel M, Novak N, Bieber T, Wichmann H-E, Ring J, Illig T, Cattaert T, Van Steen K, Weidinger S. Analysis of the high-affinity IgE receptor genes reveals epistatic effects of FCER1A variants on total IgE levels and eczema risk. Allergy 2009; DOI: 10.1111/j.1398-9995.2009.02297.x. Abstract Background: High levels of total and allergen-specific IgE levels are a key feature in allergic diseases. The high-affinity receptor for IgE, which is composed of one alpha (FCER1A), one beta (FCER1B), and two gamma (FCER1G) subunits, represents the central receptor of IgE-induced reactions. In a genome-wide association scan, we recently identified associations between functional FCER1A variants and total serum IgE levels. Previous studies had reported linkage and association of FCER1B variants with IgE and atopic traits. The FCER1G gene has not yet been investigated with regard to atopy. Filaggrin (FLG) is the strongest known risk gene for eczema, in particular the allergic subtype of eczema. Methods: We investigated the association of FCER1A, FCER1B, and FCER1G variants with IgE in a large population-based cohort (n = 4261) and tested for epistatic effects using the model-based multifactor dimensionality reduction (MB-MDR) method. In addition, we investigated a potential interaction between FLG and FCER1A variants in a large collection of eczema cases (n = 1018) and population controls. Results: Three strongly correlated FCER1A polymorphisms were significantly associated with total and specific IgE levels as well as allergic sensitization. No associations were seen for FCER1B and FCER1G. After adjustment for FLG effects, a significant epistatic effect of the FCER1A variants rs10489854 and rs2511211 on eczema risk was detected. Conclusions: These results suggest that FCER1A variants by themselves and in combination influence IgE levels and act synergistically to influence eczema risk. [less ▲]

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