| 1. |
- Craddock, Nick, et al.
(author)
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Genome-wide association study of CNVs in 16,000 cases of eight common diseases and 3,000 shared controls
- 2010
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In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 464:7289, s. 713-720
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Journal article (peer-reviewed)abstract
- Copy number variants (CNVs) account for a major proportion of human genetic polymorphism and have been predicted to have an important role in genetic susceptibility to common disease. To address this we undertook a large, direct genome-wide study of association between CNVs and eight common human diseases. Using a purpose-designed array we typed,19,000 individuals into distinct copy-number classes at 3,432 polymorphic CNVs, including an estimated similar to 50% of all common CNVs larger than 500 base pairs. We identified several biological artefacts that lead to false-positive associations, including systematic CNV differences between DNAs derived from blood and cell lines. Association testing and follow-up replication analyses confirmed three loci where CNVs were associated with disease-IRGM for Crohn's disease, HLA for Crohn's disease, rheumatoid arthritis and type 1 diabetes, and TSPAN8 for type 2 diabetes-although in each case the locus had previously been identified in single nucleotide polymorphism (SNP)-based studies, reflecting our observation that most common CNVs that are well-typed on our array are well tagged by SNPs and so have been indirectly explored through SNP studies. We conclude that common CNVs that can be typed on existing platforms are unlikely to contribute greatly to the genetic basis of common human diseases.
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| 2. |
- Iwanycki Ahlstrand, Natalie, et al.
(author)
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Travel Tales of a Worldwide Weed : Genomic Signatures of Plantago major L. Reveal Distinct Genotypic Groups With Links to Colonial Trade Routes
- 2022
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In: Frontiers in Plant Science. - : Frontiers Media S.A.. - 1664-462X. ; 13
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Journal article (peer-reviewed)abstract
- Retracing pathways of historical species introductions is fundamental to understanding the factors involved in the successful colonization and spread, centuries after a species’ establishment in an introduced range. Numerous plants have been introduced to regions outside their native ranges both intentionally and accidentally by European voyagers and early colonists making transoceanic journeys; however, records are scarce to document this. We use genotyping-by-sequencing and genotype-likelihood methods on the selfing, global weed, Plantago major, collected from 50 populations worldwide to investigate how patterns of genomic diversity are distributed among populations of this global weed. Although genomic differentiation among populations is found to be low, we identify six unique genotype groups showing very little sign of admixture and low degree of outcrossing among them. We show that genotype groups are latitudinally restricted, and that more than one successful genotype colonized and spread into the introduced ranges. With the exception of New Zealand, only one genotype group is present in the Southern Hemisphere. Three of the most prevalent genotypes present in the native Eurasian range gave rise to introduced populations in the Americas, Africa, Australia, and New Zealand, which could lend support to the hypothesis that P. major was unknowlingly dispersed by early European colonists. Dispersal of multiple successful genotypes is a likely reason for success. Genomic signatures and phylogeographic methods can provide new perspectives on the drivers behind the historic introductions and the successful colonization of introduced species, contributing to our understanding of the role of genomic variation for successful establishment of introduced taxa.
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| 3. |
- Martinez-Sanz, Marta, et al.
(author)
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Advanced structural characterisation of agar-based hydrogels : Rheological and small angle scattering studies
- 2020
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In: Carbohydrate Polymers. - : Elsevier BV. - 0144-8617 .- 1879-1344. ; 236
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Journal article (peer-reviewed)abstract
- Agar-based extracts from Gelidium sesquipedale were generated by heat and combined heat-sonication, with and without the application of alkali pre-treatment. Pre-treatment yielded extracts with greater agar contents; however, it produced partial degradation of the agar, reducing its molecular weight. Sonication produced extracts with lower agar contents and decreased molecular weights. A gelation mechanism is proposed based on the rheological and small angle scattering characterization of the extracts. The formation of strong hydrogels upon cooling was caused by the association of agarose chains into double helices and bundles, the sizes of which depended on the agar purity and molecular weight. These different arrangements at the molecular scale consequently affected the mechanical performance of the obtained hydrogels. Heating of the hydrogels produced a gradual disruption of the bundles; weaker or smaller bundles were formed upon subsequent cooling, suggesting that the process was not completely reversible.
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| 4. |
- Rennie, Adrian R., et al.
(author)
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Learning about SANS instruments and data reduction from round robin measurements on samples of polystyrene latex
- 2013
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In: Journal of applied crystallography. - 0021-8898 .- 1600-5767. ; 46:5, s. 1289-1297
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Journal article (peer-reviewed)abstract
- Measurements of a well-characterized `standard' sample can verify the performance of an instrument. Typically, small-angle neutron scattering instruments are used to investigate a wide range of samples and may often be used in a number of configurations. Appropriate `standard' samples are useful to test different aspects of the performance of hardware as well as that of the data reduction and analysis software. Measurements on a number of instruments with different intrinsic characteristics and designs in a round robin can not only better characterize the performance for a wider range of conditions but also, perhaps more importantly, reveal the limits of the current state of the art of small-angle scattering. The exercise, followed by detailed analysis, tests the limits of current understanding as well as uncovering often forgotten assumptions, simplifications and approximations that underpin the current practice of the technique. This paper describes measurements of polystyrene latex, radius 720 Å, with a number of instruments. Scattering from monodisperse, uniform spherical particles is simple to calculate and displays sharp minima. Such data test the calibrations of intensity, wavelength and resolution as well as the detector response. Smoothing due to resolution, multiple scattering and polydispersity has been determined. Sources of uncertainty are often related to systematic deviations and calibrations rather than random counting errors. The study has prompted development of software to treat modest multiple scattering and to better model the instrument resolution. These measurements also allow checks of data reduction algorithms and have identified how they can be improved. The reproducibility and the reliability of instruments and the accuracy of parameters derived from the data are described.
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| 5. |
- Romagnoni, A, et al.
(author)
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Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data
- 2019
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In: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 9:1, s. 10351-
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Journal article (peer-reviewed)abstract
- Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers.
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| 6. |
- Würth, Ines, et al.
(author)
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Minute-Scale Forecasting of Wind Power - Results from the Collaborative Workshop of IEA Wind Task 32 and 36
- 2019
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In: Energies. - : MDPI. - 1996-1073. ; 12:4
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Journal article (peer-reviewed)abstract
- The demand for minute-scale forecasts of wind power is continuously increasing with the growing penetration of renewable energy into the power grid, as grid operators need to ensure grid stability in the presence of variable power generation. For this reason, IEA Wind Tasks 32 and 36 together organized a workshop on Very Short-Term Forecasting of Wind Power in 2018 to discuss different approaches for the implementation of minute-scale forecasts into the power industry. IEA Wind is an international platform for the research community and industry. Task 32 tries to identify and mitigate barriers to the use of lidars in wind energy applications, while IEA Wind Task 36 focuses on improving the value of wind energy forecasts to the wind energy industry. The workshop identified three applications that need minute-scale forecasts: (1) wind turbine and wind farm control, (2) power grid balancing, (3) energy trading and ancillary services. The forecasting horizons for these applications range from around 1 s for turbine control to 60 min for energy market and grid control applications. The methods that can be applied to generate minute-scale forecasts rely on upstream data from remote sensing devices such as scanning lidars or radars, or are based on point measurements from met masts, turbines or profiling remote sensing devices. Upstream data needs to be propagated with advection models and point measurements can either be used in statistical time series models or assimilated into physical models. All methods have advantages but also shortcomings. The workshop's main conclusions were that there is a need for further investigations into the minute-scale forecasting methods for different use cases, and a cross-disciplinary exchange of different method experts should be established. Additionally, more efforts should be directed towards enhancing quality and reliability of the input measurement data.
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