| 1. |
- Fontes, Eduardo, et al.
(author)
-
A heterogeneous model for the MCFC cathode
- 1995
-
In: Electrochimica Acta. - 0013-4686. ; 40:11, s. 1641-1651
-
Journal article (peer-reviewed)abstract
- A steady state agglomerate model for the MCFC cathode which takes into account the heterogeneous structure of this porous electrode is presented. The resulting model equations are solved by means of the finite element method. Calculations have been performed on two different test structures and include the influence of kinetics, porosity, outer surface area and distribution of electrolyte film. Comparisons with the filmed agglomerate model show that it is possible to obtain excellent agreement between the polarisation curves predicted by the two different models if a uniform film is used in the simulations. The tortuosity in the filmed agglomerate model is used as a fitting parameter. Other effects that evolve in the heterogeneous model due to variations in the local structure are not revealed in the pseudohomogeneous model. The effect of a non-uniform electrolyte film thickness was investigated by solving the problem for a structure with pore mouths filled by an electrolyte meniscus. Also the effect of an electrolyte meniscus between spherical agglomerates was investigated.
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| 2. |
- Fontes, Eduardo, et al.
(author)
-
Effects of different design parameters on the performance of MCFC cathodes
- 1996
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In: Electrochimica Acta. - 0013-4686. ; 41:1, s. 1-13
-
Journal article (peer-reviewed)abstract
- The effects of electrode thickness, electrolyte filling and current collector geometry on the performance of MCFC cathodes are investigated by using a steady state mathematical model. A two-dimensional pseudo-homogeneous model for the three-phase system in the cathode is used, which includes the polarisation curves from the heterogeneous agglomerate model[1] as local source functions. The model takes into account the potential distribution in the electrolyte and catalyst phase but neglects mass transport limitations in the gas phase. The simulations show that, for cathodes with a finite electronic conductivity, there is a substantial potential distribution perpendicular to the depth of the electrode depending on the size of the gas holes in the current collector.
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| 3. |
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| 4. |
- Johnsson, Kerstin, et al.
(author)
-
What is a “unimodal” cell population? Using statistical tests as criteria for unimodality in automated gating and quality control
- 2017
-
In: Cytometry Part A. - : Wiley. - 1552-4922. ; 91:9, s. 908-916
-
Journal article (peer-reviewed)abstract
- Many automated gating algorithms for flow cytometry data are based on the concept of unimodal cell populations. However, in this article, we show that criteria previously used to make decisions on unimodality cannot adequately distinguish unimodal from bimodal densities. We show that dip and bandwidth tests for unimodality, taken from the statistics literature, can do this with consistent and low error rates. These tests also have the possibility to adjust the significance level to handle the trade-off between failing to detect a second mode and seeing a second mode when there is none. The differences between the dip and bandwidth tests are elucidated using real data from the FlowCAP I challenge, also guidelines for flow cytometry data preprocessing are given.
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| 5. |
- Yeung, Edwina, et al.
(author)
-
Maternal age is related to offspring DNA methylation : a meta-analysis of results from the pace consortium
- 2024
-
In: Aging Cell. - : John Wiley & Sons. - 1474-9718 .- 1474-9726.
-
Journal article (peer-reviewed)abstract
- Worldwide trends to delay childbearing have increased parental ages at birth. Older parental age may harm offspring health, but mechanisms remain unclear. Alterations in offspring DNA methylation (DNAm) patterns could play a role as aging has been associated with methylation changes in gametes of older individuals. We meta-analyzed epigenome-wide associations of parental age with offspring blood DNAm of over 9500 newborns and 2000 children (5–10 years old) from the Pregnancy and Childhood Epigenetics consortium. In newborns, we identified 33 CpG sites in 13 loci with DNAm associated with maternal age (PFDR < 0.05). Eight of these CpGs were located near/in the MTNR1B gene, coding for a melatonin receptor. Regional analysis identified them together as a differentially methylated region consisting of 9 CpGs in/near MTNR1B, at which higher DNAm was associated with greater maternal age (PFDR = 6.92 × 10−8) in newborns. In childhood blood samples, these differences in blood DNAm of MTNR1B CpGs were nominally significant (p < 0.05) and retained the same positive direction, suggesting persistence of associations. Maternal age was also positively associated with higher DNA methylation at three CpGs in RTEL1-TNFRSF6B at birth (PFDR < 0.05) and nominally in childhood (p < 0.0001). Of the remaining 10 CpGs also persistent in childhood, methylation at cg26709300 in YPEL3/BOLA2B in external data was associated with expression of ITGAL, an immune regulator. While further study is needed to establish causality, particularly due to the small effect sizes observed, our results potentially support offspring DNAm as a mechanism underlying associations of maternal age with child health.
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| 6. |
- Alexandersson, Erik, et al.
(author)
-
Transcriptional regulation of aquaporins in accessions of Arabidopsis in response to drought stress.
- 2010
-
In: Plant Journal. - 1365-313X. ; 61, s. 650-660
-
Journal article (peer-reviewed)abstract
- Summary Aquaporins facilitate water transport over cellular membranes and are therefore believed to play an important role in water homeostasis. In higher plants aquaporin-like proteins, also called major intrinsic proteins (MIPs), are divided into 5 subfamilies. We have previously shown that MIP transcription in Arabidopsis thaliana generally is down-regulated in leaves upon drought stress, apart from two members of the Plasma membrane Intrinsic Protein (PIP) subfamily, AtPIP1;4 and AtPIP2;5, which are up-regulated. In order to assess if this regulation is general or accession-specific we monitored gene expression of all PIPs in five Arabidopsis accessions. Overall drought regulation of PIPs was well conserved for all five accessions tested suggesting a general and fundamental physiological role of this drought response. In addition, significant differences among accessions were identified for transcripts of three PIP genes. Principal component analysis showed that most of the PIP transcriptional variation during drought stress could be explained by one variable linked to leaf water content. Promoter-GUS constructs of AtPIP1;4, AtPIP2;5 and also AtPIP2;6, which is unresponsive to drought stress, had distinct expression patterns concentrated to the base of the leaf petioles and parts of the flowers. The presence of drought stress response elements within the 1.6 kb promoter regions of AtPIP1;4 and AtPIP2;5, was demonstrated by comparing transcription of the promoter reporter construct and the endogenous gene upon drought stress. Analysis by ATTED-II and other web-based bioinformatical tools showed that several of the MIPs down-regulated upon drought are strongly co-expressed, whereas AtPIP1;4, AtPIP2;5 and AtPIP2;6 are not co-expressed.
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| 7. |
- Andersson, Anna, et al.
(author)
-
Gene expression profiling of leukemic cell lines reveals conserved molecular signatures among subtypes with specific genetic aberrations
- 2005
-
In: Leukemia. - : Springer Science and Business Media LLC. - 1476-5551 .- 0887-6924. ; 19:6, s. 1042-1050
-
Journal article (peer-reviewed)abstract
- Hematologic malignancies are characterized by fusion genes of biological/clinical importance. Immortalized cell lines with such aberrations are today widely used to model different aspects of leukemogenesis. Using cDNA microarrays, we determined the gene expression profiles of 40 cell lines as well as of primary leukemias harboring 11q23/MLL rearrangements, t(1;19)[TCF3/PBX1], t(12;21)[ETV6/RUNX1], t(8;21)[RUNX1/CBFA2T1], t(8;14) [IGH@/MYC], t(8;14)[TRA@/MYC], t(9;22)[BCR/ABL1], t(10;11) [PICALM/MLLT10], t(15;17)[PML/RARA], or inv(16)[CBFB/MYH11]. Unsupervised classification revealed that hematopoietic cell lines of diverse origin, but with the same primary genetic changes, segregated together, suggesting that pathogenetically important regulatory networks remain conserved despite numerous passages. Moreover, primary leukemias cosegregated with cell lines carrying identical genetic rearrangements, further supporting that critical regulatory pathways remain intact in hematopoietic cell lines. Transcriptional signatures correlating with clinical subtypes/primary genetic changes were identified and annotated based on their biological/molecular properties and chromosomal localization. Furthermore, the expression profile of tyrosine kinase-encoding genes was investigated, identifying several differentially expressed members, segregating with primary genetic changes, which may be targeted with tyrosine kinase inhibitors. The identified conserved signatures are likely to reflect regulatory networks of importance for the transforming abilities of the primary genetic changes and offer important pathogenetic insights as well as a number of targets for future rational drug design.
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| 8. |
- Andersson, Anna, et al.
(author)
-
Microarray-based classification of a consecutive series of 121 childhood acute leukemias: prediction of leukemic and genetic subtype as well as of minimal residual disease status.
- 2007
-
In: Leukemia. - : Springer Science and Business Media LLC. - 1476-5551 .- 0887-6924. ; 21:6, s. 1198-1203
-
Journal article (peer-reviewed)abstract
- Gene expression analyses were performed on 121 consecutive childhood leukemias (87 B-lineage acute lymphoblastic leukemias (ALLs), 11 T-cell ALLs and 23 acute myeloid leukemias (AMLs)), investigated during an 8-year period at a single center. The supervised learning algorithm k-nearest neighbor was utilized to build gene expression predictors that could classify the ALLs/AMLs according to clinically important subtypes with high accuracy. Validation experiments in an independent data set verified the high prediction accuracies of our classifiers. B-lineage ALLs with uncharacteristic cytogenetic aberrations or with a normal karyotype displayed heterogeneous gene expression profiles, resulting in low prediction accuracies. Minimal residual disease status (MRD) in T-cell ALLs with a high (40.1%) MRD at day 29 could be classified with 100% accuracy already at the time of diagnosis. In pediatric leukemias with uncharacteristic cytogenetic aberrations or with a normal karyotype, unsupervised analysis identified two novel subgroups: one consisting mainly of cases remaining in complete remission (CR) and one containing a few patients in CR and all but one of the patients who relapsed. This study of a consecutive series of childhood leukemias confirms and extends further previous reports demonstrating that global gene expression profiling provides a valuable tool for genetic and clinical classification of childhood leukemias.
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| 9. |
- Bordería, Antonio V, et al.
(author)
-
Group Selection and Contribution of Minority Variants during Virus Adaptation Determines Virus Fitness and Phenotype.
- 2015
-
In: PLoS Pathogens. - : Public Library of Science (PLoS). - 1553-7366 .- 1553-7374. ; 11:5
-
Journal article (peer-reviewed)abstract
- Understanding how a pathogen colonizes and adapts to a new host environment is a primary aim in studying emerging infectious diseases. Adaptive mutations arise among the thousands of variants generated during RNA virus infection, and identifying these variants will shed light onto how changes in tropism and species jumps can occur. Here, we adapted Coxsackie virus B3 to a highly permissive and less permissive environment. Using deep sequencing and bioinformatics, we identified a multi-step adaptive process to adaptation involving residues in the receptor footprints that correlated with receptor availability and with increase in virus fitness in an environment-specific manner. We show that adaptation occurs by selection of a dominant mutation followed by group selection of minority variants that together, confer the fitness increase observed in the population, rather than selection of a single dominant genotype.
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| 10. |
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| 11. |
- Clave, Emmanuel, et al.
(author)
-
Human thymopoiesis is influenced by a common genetic variant within the TCRA-TCRD locus
- 2018
-
In: Science Translational Medicine. - : American Association for the Advancement of Science (AAAS). - 1946-6234 .- 1946-6242. ; 10:457
-
Journal article (peer-reviewed)abstract
- The thymus is the primary lymphoid organ where naïve T cells are generated; however, with the exception of age, the parameters that govern its function in healthy humans remain unknown. We characterized the variability of thymic function among 1000 age- and sex-stratified healthy adults of the Milieu Intérieur cohort, using quantification of T cell receptor excision circles (TRECs) in peripheral blood T cells as a surrogate marker of thymopoiesis. Age and sex were the only nonheritable factors identified that affect thymic function. TREC amounts decreased with age and were higher in women compared to men. In addition, a genome-wide association study revealed a common variant (rs2204985) within the T cell receptor TCRA-TCRD locus, between the DD2 and DD3 gene segments, which associated with TREC amounts. Strikingly, transplantation of human hematopoietic stem cells with the rs2204985 GG genotype into immunodeficient mice led to thymopoiesis with higher TRECs, increased thymocyte counts, and a higher TCR repertoire diversity. Our population immunology approach revealed a genetic locus that influences thymopoiesis in healthy adults, with potentially broad implications in precision medicine.
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| 12. |
- Duffy, Darragh, et al.
(author)
-
The ABCs of viral hepatitis that define biomarker signatures of acute viral hepatitis
- 2014
-
In: Hepatology. - : Ovid Technologies (Wolters Kluwer Health). - 1527-3350 .- 0270-9139. ; 59:4, s. 1273-1282
-
Journal article (peer-reviewed)abstract
- Viral hepatitis is the leading cause of liver disease worldwide and can be caused by several agents, including hepatitis A (HAV), B (HBV), and C (HCV) virus. We employed multiplexed protein immune assays to identify biomarker signatures of viral hepatitis in order to define unique and common responses for three different acute viral infections of the liver. We performed multianalyte profiling, measuring the concentrations of 182 serum proteins obtained from acute HAV- (18), HBV- (18), and HCV-infected (28) individuals, recruited as part of a hospital-based surveillance program in Cairo, Egypt. Virus-specific biomarker signatures were identified and validation was performed using a unique patient population. A core signature of 46 plasma proteins was commonly modulated in all three infections, as compared to healthy controls. Principle component analysis (PCA) revealed a host response based upon 34 proteins, which could distinguish HCV patients from HAV- and HBV-infected individuals or healthy controls. When HAV and HBV groups were compared directly, 34 differentially expressed serum proteins allowed the separation of these two patient groups. A validation study was performed on an additional 111 patients, confirming the relevance of our initial findings, and defining the 17 analytes that reproducibly segregated the patient populations. Conclusions: This combined discovery and biomarker validation approach revealed a previously unrecognized virus-specific induction of host proteins. The identification of hepatitis virus specific signatures provides a foundation for functional studies and the identification of potential correlates of viral clearance. (Hepatology 2014;59:1273-1282)
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| 13. |
- Fontes, Magnus
(author)
-
Analys av genuttrycksdata
- 2008
-
In: Människor och matematik - läsebok för nyfikna. - 9789185143085 ; , s. 353-365
-
Book chapter (pop. science, debate, etc.)
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| 14. |
- Fontes, Magnus
(author)
-
Initial-boundary value problems for parabolic equations
- 2009
-
In: Annales Academiae Scientiarum Fennicae. Mathematica. - 1239-629X. ; 34, s. 583-605
-
Journal article (peer-reviewed)abstract
- We prove new existence and uniqueness results for weak solutions to non-homogeneous initial-boundary value problems for parabolic equations modeled on the evolution of the p-Laplacian.
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| 15. |
- Fontes, Magnus
(author)
-
Optimal results for the nonhomogeneous initial-boundary value problem for the two-dimensional Navier-Stokes equations
- 2010
-
In: Journal of Mathematical Fluid Mechanics. - : Springer Science and Business Media LLC. - 1422-6928 .- 1422-6952. ; 12, s. 412-434
-
Journal article (peer-reviewed)abstract
- In this work we study the fully nonhomogeneous initial boundary value problem for the two-dimensional time-dependent Navier–Stokes equations in a general open space domain in R2 with low regularity assumptions on the initial and the boundary value data. We show that the perturbed Navier–Stokes operator is a diffeomorphism from a suitable function space onto its own dual and as a corollary we get that the Navier–Stokes equations are uniquely solvable in these spaces and that the solution depends smoothly on all involved data. Our source data space and solution space are in complete natural duality and in this sense, without any smallness assumptions on the data, we solve the equations for data with optimally low regularity in both space and time.
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| 16. |
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| 17. |
- Fontes, Magnus
(author)
-
Parabolic equations with low regularity
- 1996
-
Doctoral thesis (other academic/artistic)abstract
- In this work we study a variational method for treating parabolic equations that yields new results for non-linear equations with low regularity on source and boundary data. We treat mainly strongly parabolic quasilinear equations and systems in divergence form. The basic idea is to compose the parabolic operator with a weighted sum of the identity operator and the Hilbert transformation in the time direction, and in this way obtain a coercive operator. We work with functions having space derivatives in some Lp-space and half order time derivatives in L2. A key to our results is the celebrated theorem by Marcel Riesz concerning the boundedness of the Hilbert transformation on Lp-spaces when p is strictly greater than one.
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| 18. |
- Fontes, Magnus, et al.
(author)
-
Simplified a priori Estimate for the Time Periodic Burgers' Equation
- 2010
-
In: Proceedings of the Estonian Academy of Sciences. - : Estonian Academy Publishers. - 1736-6046 .- 1736-7530. ; 59:1, s. 34-41
-
Journal article (peer-reviewed)abstract
- We present here a version of the existence and uniqueness result of time periodic solutions to the viscous Burgers’ equation with irregular forcing terms (with Sobolev regularity –1 in space). The key result here is an a priori estimate which is simpler than the previously treated case of forcing terms with regularity –½ in time.
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| 19. |
- Fontes, Magnus, et al.
(author)
-
Statistical and Knowledge Supported Visualization of Multivariate data
- 2012
-
In: Analysis for Science, Engineering and Beyond. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 2190-5622 .- 2190-5614. - 9783642202353 - 9783642202360 ; Springer Proceedings in Mathematics Volume 6, s. 143-173
-
Book chapter (peer-reviewed)abstract
- In the present work we have selected a collection of statistical and mathematical tools useful for the exploration of multivariate data and we present them in a form that is meant to be particularly accessible to a classically trained mathematician. We give self contained and streamlined introductions to principal component analysis, multidimensional scaling and statistical hypothesis testing. Within the presented mathematical framework we then propose a general exploratory methodology for the investigation of real world high dimensional datasets that builds on statistical and knowledge supported visualizations. We exemplify the proposed methodology by applying it to several different genomewide DNA-microarray datasets. The exploratory methodology should be seen as an embryo that can be expanded and developed in many directions. As an example we point out some recent promising advances in the theory for random matrices that, if further developed, potentially could provide practically useful and theoretically well founded estimations of information content in dimension reducing visualizations. We hope that the present work can serve as an introduction to, and help to stimulate more research within, the interesting and rapidly expanding field of data exploration.
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| 20. |
- Fontes, Magnus, et al.
(author)
-
The projection score - an evaluation criterion for variable subset selection in PCA visualization
- 2011
-
In: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 12
-
Journal article (peer-reviewed)abstract
- Background In many scientific domains, it is becoming increasingly common to collect high-dimensional data sets, often with an exploratory aim, to generate new and relevant hypotheses. The exploratory perspective often makes statistically guided visualization methods, such as Principal Component Analysis (PCA), the methods of choice. However, the clarity of the obtained visualizations, and thereby the potential to use them to formulate relevant hypotheses, may be confounded by the presence of the many non-informative variables. For microarray data, more easily interpretable visualizations are often obtained by filtering the variable set, for example by removing the variables with the smallest variances or by only including the variables most highly related to a specific response. The resulting visualization may depend heavily on the inclusion criterion, that is, effectively the number of retained variables. To our knowledge, there exists no objective method for determining the optimal inclusion criterion in the context of visualization. Results We present the projection score, which is a straightforward, intuitively appealing measure of the informativeness of a variable subset with respect to PCA visualization. This measure can be universally applied to find suitable inclusion criteria for any type of variable filtering. We apply the presented measure to find optimal variable subsets for different filtering methods in both microarray data sets and synthetic data sets. We note also that the projection score can be applied in general contexts, to compare the informativeness of any variable subsets with respect to visualization by PCA. Conclusions We conclude that the projection score provides an easily interpretable and universally applicable measure of the informativeness of a variable subset with respect to visualization by PCA, that can be used to systematically find the most interpretable PCA visualization in practical exploratory analysis.
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| 21. |
- Fontes, Magnus, et al.
(author)
-
Time-Periodic Solutions of the Burgers Equation
- 2009
-
In: Journal of Mathematical Fluid Mechanics. - : Springer Science and Business Media LLC. - 1422-6928 .- 1422-6952. ; 11:2, s. 303-323
-
Journal article (peer-reviewed)abstract
- Abstract: We investigate the time periodic solutions to the viscous Burgers equation u(t) - mu u(xx) + uu(x) = f for irregular forcing terms. We prove that the corresponding Burgers operator is a diffeomorphism between appropriate function spaces.
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| 22. |
- Henningsson, Rasmus, et al.
(author)
-
SMSSVD : SubMatrix Selection Singular Value Decomposition
- 2019
-
In: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 35:3, s. 478-486
-
Journal article (peer-reviewed)abstract
- Motivation: High throughput biomedical measurements normally capture multiple overlaid biologically relevant signals and often also signals representing different types of technical artefacts like e.g. batch effects. Signal identification and decomposition are accordingly main objectives in statistical biomedical modeling and data analysis. Existing methods, aimed at signal reconstruction and deconvolution, in general, are either supervised, contain parameters that need to be estimated or present other types of ad hoc features. We here introduce SubMatrix Selection Singular Value Decomposition (SMSSVD), a parameter-free unsupervised signal decomposition and dimension reduction method, designed to reduce noise, adaptively for each low-rank-signal in a given data matrix, and represent the signals in the data in a way that enable unbiased exploratory analysis and reconstruction of multiple overlaid signals, including identifying groups of variables that drive different signals. Results: The SMSSVD method produces a denoised signal decomposition from a given data matrix. It also guarantees orthogonality between signal components in a straightforward manner and it is designed to make automation possible. We illustrate SMSSVD by applying it to several real and synthetic datasets and compare its performance to golden standard methods like PCA (Principal Component Analysis) and SPC (Sparse Principal Components, using Lasso constraints). The SMSSVD is computationally efficient and despite being a parameter-free method, in general, outperforms existing statistical learning methods. Availability and implementation: A Julia implementation of SMSSVD is openly available on GitHub (https://github.com/rasmushenningsson/SubMatrixSelectionSVD.jl). Supplementary information: Supplementary data are available at Bioinformatics online.
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| 23. |
- Johnsson, Kerstin, et al.
(author)
-
BayesFlow: latent modeling of flow cytometry cell populations
- 2016
-
In: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 17:25
-
Journal article (peer-reviewed)abstract
- Background: Flow cytometry is a widespread single-cell measurement technology with a multitude of clinical and research applications. Interpretation of flow cytometry data is hard; the instrumentation is delicate and can not render absolute measurements, hence samples can only be interpreted in relation to each other while at the same time comparisons are confounded by inter-sample variation. Despite this, most automated flow cytometry data analysis methods either treat samples individually or ignore the variation by for example pooling the data. A key requirement for models that include multiple samples is the ability to visualize and assess inferred variation, since what could be technical variation in one setting would be different phenotypes in another. Results: We introduce BayesFlow, a pipeline for latent modeling of flow cytometry cell populations built upon a Bayesian hierarchical model. The model systematizes variation in location as well as shape. Expert knowledge can be incorporated through informative priors and the results can be supervised through compact and comprehensive visualizations. BayesFlow is applied to two synthetic and two real flow cytometry data sets. For the first real data set, taken from the FlowCAP I challenge, BayesFlow does not only give a gating which would place it among the top performers in FlowCAP I for this dataset, it also gives a more consistent treatment of different samples than either manual gating or other automated gating methods. The second real data set contains replicated flow cytometry measurements of samples from healthy individuals. BayesFlow gives here cell populations with clear expression patterns and small technical intra-donor variation as compared to biological inter-donor variation. Conclusions: Modeling latent relations between samples through BayesFlow enables a systematic analysis of inter-sample variation. As opposed to other joint gating methods, effort is put at ensuring that the obtained partition of the data corresponds to actual cell populations, and the result is therefore directly biologically interpretable. BayesFlow is freely available at GitHub.
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| 24. |
- Johnsson, Kerstin, et al.
(author)
-
Low Bias Local Intrinsic Dimension Estimation from Expected Simplex Skewness
- 2015
-
In: IEEE Transactions on Pattern Analysis and Machine Intelligence. - 1939-3539. ; 37:1, s. 196-202
-
Journal article (peer-reviewed)abstract
- In exploratory high-dimensional data analysis, local intrinsic dimension estimation can sometimes be used in order to discriminate between data sets sampled from different low-dimensional structures. Global intrinsic dimension estimators can in many cases be adapted to local estimation, but this leads to problems with high negative bias or high variance. We introduce a method that exploits the curse/blessing of dimensionality and produces local intrinsic dimension estimators that have very low bias, even in cases where the intrinsic dimension is higher than the number of data points, in combination with relatively low variance. We show that our estimators have a very good ability to classify local data sets by their dimension compared to other local intrinsic dimension estimators; furthermore we provide examples showing the usefulness of local intrinsic dimension estimation in general and our method in particular for stratification of real data sets.
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| 25. |
- Lilljebjörn, Henrik, et al.
(author)
-
Identification of ETV6-RUNX1-like and DUX4-rearranged subtypes in paediatric B-cell precursor acute lymphoblastic leukaemia
- 2016
-
In: Nature Communications. - : NATURE PUBLISHING GROUP. - 2041-1723. ; 7:11790
-
Journal article (peer-reviewed)abstract
- Fusion genes are potent driver mutations in cancer. In this study, we delineate the fusion gene landscape in a consecutive series of 195 paediatric B-cell precursor acute lymphoblastic leukaemia (BCP ALL). Using RNA sequencing, we find in-frame fusion genes in 127 (65%) cases, including 27 novel fusions. We describe a subtype characterized by recurrent IGH-DUX4 or ERG-DUX4 fusions, representing 4% of cases, leading to overexpression of DUX4 and frequently co-occurring with intragenic ERG deletions. Furthermore, we identify a subtype characterized by an ETV6-RUNX1-like gene-expression profile and coexisting ETV6 and IKZF1 alterations. Thus, this study provides a detailed overview of fusion genes in paediatric BCP ALL and adds new pathogenetic insights, which may improve risk stratification and provide therapeutic options for this disease.
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| 26. |
- Lilljebjörn, Henrik, et al.
(author)
-
The correlation pattern of acquired copy number changes in 164 ETV6/RUNX1-positive childhood acute lymphoblastic leukemias
- 2010
-
In: Human Molecular Genetics. - : Oxford University Press. - 0964-6906 .- 1460-2083. ; 19:16, s. 3150-3158
-
Journal article (peer-reviewed)abstract
- The ETV6/RUNX1 fusion gene, present in 25% of B-lineage childhood acute lymphoblastic leukemia (ALL), is thought to represent an initiating event, which requires additional genetic changes for leukemia development. To identify additional genetic alterations, 24 ETV6/RUNX1-positive ALLs were analyzed using 500K single nucleotide polymorphism arrays. The results were combined with previously published data sets, allowing us to ascertain genomic copy number aberrations (CNAs) in 164 cases. In total, 45 recurrent CNAs were identified with an average number of 3.5 recurrent changes per case (range 0-13). Twenty-six percent of cases displayed a set of recurrent CNAs identical to that of other cases in the data set. The majority (74%), however, displayed a unique pattern of recurrent CNAs, indicating a large heterogeneity within this ALL subtype. As previously demonstrated, alterations targeting genes involved in B-cell development were common (present in 28% of cases). However, the combined analysis also identified alterations affecting nuclear hormone response (24%) to be a characteristic feature of ETV6/RUNX1-positive ALL. Studying the correlation pattern of the CNAs allowed us to highlight significant positive and negative correlations between specific aberrations. Furthermore, oncogenetic tree models identified ETV6, CDKN2A/B, PAX5, del(6q) and +16 as possible early events in the leukemogenic process.
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| 27. |
- Nilsson, Jens, et al.
(author)
-
Approximate geodesic distances reveal biologically relevant structures in microarray data
- 2004
-
In: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 20:6, s. 874-880
-
Journal article (peer-reviewed)abstract
- Motivation: Genome-wide gene expression measurements, as currently determined by the microarray technology, can be represented mathematically as points in a high-dimensional gene expression space. Genes interact with each other in regulatory networks, restricting the cellular gene expression profiles to a certain manifold, or surface, in gene expression space. To obtain knowledge about this manifold, various dimensionality reduction methods and distance metrics are used. For data points distributed on curved manifolds, a sensible distance measure would be the geodesic distance along the manifold. In this work, we examine whether an approximate geodesic distance measure captures biological similarities better than the traditionally used Euclidean distance. Results: We computed approximate geodesic distances, determined by the Isomap algorithm, for one set of lymphoma and one set of lung cancer microarray samples. Compared with the ordinary Euclidean distance metric, this distance measure produced more instructive, biologically relevant, visualizations when applying multidimensional scaling. This suggests the Isomap algorithm as a promising tool for the interpretation of microarray data. Furthermore, the results demonstrate the benefit and importance of taking nonlinearities in gene expression data into account.
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| 28. |
- Patin, Etienne, et al.
(author)
-
Natural variation in the parameters of innate immune cells is preferentially driven by genetic factors
- 2018
-
In: Nature Immunology. - : Springer Science and Business Media LLC. - 1529-2908 .- 1529-2916. ; 19, s. 302-314
-
Journal article (peer-reviewed)abstract
- The quantification and characterization of circulating immune cells provide key indicators of human health and disease. To identify the relative effects of environmental and genetic factors on variation in the parameters of innate and adaptive immune cells in homeostatic conditions, we combined standardized flow cytometry of blood leukocytes and genome-wide DNA genotyping of 1,000 healthy, unrelated people of Western European ancestry. We found that smoking, together with age, sex and latent infection with cytomegalovirus, were the main non-genetic factors that affected variation in parameters of human immune cells. Genome-wide association studies of 166 immunophenotypes identified 15 loci that showed enrichment for disease-associated variants. Finally, we demonstrated that the parameters of innate cells were more strongly controlled by genetic variation than were those of adaptive cells, which were driven by mainly environmental exposure. Our data establish a resource that will generate new hypotheses in immunology and highlight the role of innate immunity in susceptibility to common autoimmune diseases.
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| 29. |
- Rodriguez-Roche, Rosmari, et al.
(author)
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Increasing clinical severity during a dengue virus type 3 Cuban epidemic: deep sequencing of evolving viral populations
- 2016
-
In: Journal of Virology. - 1098-5514. ; 90:19, s. 4320-4333
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Journal article (peer-reviewed)abstract
- During the DENV-3 epidemic occurred in Havana in 2001-2002, severe disease was associated with the infection sequence DENV-1/DENV-3, whilst the sequence DENV-2/DENV-3 was associated with mild/asymptomatic infections. To determine the role of the virus in the increasing severity demonstrated during the epidemic serum samples collected at different point times were studied. A total of 22 full-length sequences were obtained using a deep sequencing approach. Bayesian phylogenetic analysis of consensus sequences revealed that two DENV-3 lineages were circulating in Havana at that time, both grouped within genotype III. The predominant lineage is closely related to Peruvian and Ecuadorian strains, whilst the minor lineage is related to Venezuelan strains. According to consensus sequences, relatively few non-synonymous mutations were observed; only one was fixed during the epidemic at position 4380 in the NS2B gene. Intra-host genetic analysis indicated that a significant minor population was selected and became predominant towards the end of the epidemic. In conclusion, greater variability was detected during the epidemic's progression in terms of significant minority variants, particularly in the non-structural genes. An increasing trend of genetic diversity towards the end of the epidemic was only observed for synonymous variant allele rates, with higher variability in secondary cases. Remarkably, significant intra-host genetic variation was demonstrated within the same patient during the course of secondary infection DENV-1/DENV-3, including changes in the structural proteins PrM and E. Therefore, the dynamic of evolving viral populations in the context of heterotypic antibodies could be related to the increasing clinical severity observed during the epidemic.
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| 30. |
- Scharff, Anna Zychlinsky, et al.
(author)
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Sex differences in IL-17 contribute to chronicity in male versus female urinary tract infection
- 2019
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In: JCI Insight. - : American Society for Clinical Investigation. - 2379-3708. ; 4:13
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Journal article (peer-reviewed)abstract
- Sex-based differences influence incidence and outcome of infectious disease. Women have a significantly greater incidence of urinary tract infection (UTI) than men, yet, conversely, male UTI is more persistent, with greater associated morbidity. Mechanisms underlying these sex-based differences are unknown, in part due to a lack of experimental models. We optimized a model to transurethrally infect male mice and directly compared UTI in both sexes. Although both sexes were initially equally colonized by uropathogenic E. coli, only male and testosterone-treated female mice remained chronically infected for up to 4 weeks. Female mice had more robust innate responses, including higher IL-17 expression, and increased γδ T cells and group 3 innate lymphoid cells in the bladder following infection. Accordingly, neutralizing IL-17 abolished resolution in female mice, identifying a cytokine pathway necessary for bacterial clearance. Our findings support the concept that sex-based responses to UTI contribute to impaired innate immunity in males and provide a rationale for non–antibiotic-based immune targeting to improve the response to UTI.
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| 31. |
- Soneson, Charlotte, et al.
(author)
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A framework for list representation, enabling list stabilization through incorporation of gene exchangeabilities.
- 2012
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In: Biostatistics. - : Oxford University Press (OUP). - 1468-4357 .- 1465-4644. ; 13, s. 129-141
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Journal article (peer-reviewed)abstract
- Analysis of multivariate data sets from, for example, microarray studies frequently results in lists of genes which are associated with some response of interest. The biological interpretation is often complicated by the statistical instability of the obtained gene lists, which may partly be due to the functional redundancy among genes, implying that multiple genes can play exchangeable roles in the cell. In this paper, we use the concept of exchangeability of random variables to model this functional redundancy and thereby account for the instability. We present a flexible framework to incorporate the exchangeability into the representation of lists. The proposed framework supports straightforward comparison between any 2 lists. It can also be used to generate new more stable gene rankings incorporating more information from the experimental data. Using 2 microarray data sets, we show that the proposed method provides more robust gene rankings than existing methods with respect to sampling variations, without compromising the biological significance of the rankings.
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| 32. |
- Soneson, Charlotte, et al.
(author)
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A method for visual identification of small sample subgroups and potential biomarkers
- 2011
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In: Annals of Applied Statistics. - 1932-6157. ; 5:3, s. 2131-2149
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Journal article (peer-reviewed)abstract
- In order to find previously unknown subgroups in biomedical data and generate testable hypotheses, visually guided exploratory analysis can be of tremendous importance. In this paper we propose a new dissimilarity measure that can be used within the Multidimensional Scaling framework to obtain a joint low-dimensional representation of both the samples and variables of a multivariate data set, thereby providing an alternative to conventional biplots. In comparison with biplots, the representations obtained by our approach are particularly useful for exploratory analysis of data sets where there are small groups of variables sharing unusually high or low values for a small group of samples.
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| 33. |
- Soneson, Charlotte, et al.
(author)
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Early changes in the hypothalamic region in prodromal Huntington disease revealed by MRI analysis.
- 2010
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In: Neurobiology of Disease. - : Elsevier BV. - 0969-9961. ; 40, s. 531-543
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Journal article (peer-reviewed)abstract
- Huntington disease (HD) is a fatal neurodegenerative disorder caused by an expanded CAG repeat. Its length can be used to estimate the time of clinical diagnosis, which is defined by overt motor symptoms. Non-motor symptoms begin before motor onset, and involve changes in hypothalamus-regulated functions such as sleep, emotion and metabolism. Therefore we hypothesized that hypothalamic changes occur already prior to the clinical diagnosis. We performed voxel-based morphometry and logistic regression analyses of cross-sectional MR images from 220 HD gene carriers and 75 controls in the Predict-HD study. We show that changes in the hypothalamic region are detectable before clinical diagnosis and that its grey matter contents alone are sufficient to distinguish HD gene carriers from control cases. In conclusion, our study shows, for the first time, that alterations in grey matter contents in the hypothalamic region occur at least a decade before clinical diagnosis in HD using MRI.
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| 34. |
- Soneson, Charlotte, et al.
(author)
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Incorporation of gene exchangeabilities improves the reproducibility of gene set rankings
- 2014
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In: Computational Statistics & Data Analysis. - : Elsevier BV. - 0167-9473. ; 71, s. 588-598
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Journal article (peer-reviewed)abstract
- Gene set-based analysis methods have recently gained increasing popularity for analysis of microarray data. Several studies have indicated that the results from such methods are more reproducible and more easily interpretable than the results from single gene-based methods. A new method for ranking gene sets with respect to their association with a given predictor or response, using a new framework for robust gene list representation, is proposed. Employing the concept of exchangeability of random variables, this method attempts to account for the functional redundancy among the genes. Compared to other evaluated methods for gene set ranking, the proposed method yields rankings that are more robust with respect to sampling variations in the underlying data, which allows more reliable biological conclusions. (C) 2012 Elsevier B.V. All rights reserved.
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| 35. |
- Soneson, Charlotte, et al.
(author)
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Integrative analysis of gene expression and copy number alterations using canonical correlation analysis
- 2010
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In: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 11:191, s. 1-20
-
Journal article (peer-reviewed)abstract
- Background: With the rapid development of new genetic measurement methods, several types of genetic alterations can be quantified in a high-throughput manner. While the initial focus has been on investigating each data set separately, there is an increasing interest in studying the correlation structure between two or more data sets. Multivariate methods based on Canonical Correlation Analysis (CCA) have been proposed for integrating paired genetic data sets. The high dimensionality of microarray data imposes computational difficulties, which have been addressed for instance by studying the covariance structure of the data, or by reducing the number of variables prior to applying the CCA. In this work, we propose a new method for analyzing high-dimensional paired genetic data sets, which mainly emphasizes the correlation structure and still permits efficient application to very large data sets. The method is implemented by translating a regularized CCA to its dual form, where the computational complexity depends mainly on the number of samples instead of the number of variables. The optimal regularization parameters are chosen by cross-validation. We apply the regularized dual CCA, as well as a classical CCA preceded by a dimension-reducing Principal Components Analysis (PCA), to a paired data set of gene expression changes and copy number alterations in leukemia. Results: Using the correlation-maximizing methods, regularized dual CCA and PCA+CCA, we show that without pre-selection of known disease-relevant genes, and without using information about clinical class membership, an exploratory analysis singles out two patient groups, corresponding to well-known leukemia subtypes. Furthermore, the variables showing the highest relevance to the extracted features agree with previous biological knowledge concerning copy number alterations and gene expression changes in these subtypes. Finally, the correlation-maximizing methods are shown to yield results which are more biologically interpretable than those resulting from a covariance-maximizing method, and provide different insight compared to when each variable set is studied separately using PCA. Conclusions: We conclude that regularized dual CCA as well as PCA+CCA are useful methods for exploratory analysis of paired genetic data sets, and can be efficiently implemented also when the number of variables is very large.
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| 36. |
- Urrutia, Alejandra, et al.
(author)
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Standardized Whole-Blood Transcriptional Profiling Enables the Deconvolution of Complex Induced Immune Responses
- 2016
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In: Cell Reports. - : Elsevier BV. - 2211-1247. ; 16:10, s. 2777-2791
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Journal article (peer-reviewed)abstract
- Systems approaches for the study of immune signaling pathways have been traditionally based on purified cells or cultured lines. However, in vivo responses involve the coordinated action of multiple cell types, which interact to establish an inflammatory microenvironment. We employed standardized whole-blood stimulation systems to test the hypothesis that responses to Toll-like receptor ligands or whole microbes can be defined by the transcriptional signatures of key cytokines. We found 44 genes, identified using Support Vector Machine learning, that captured the diversity of complex innate immune responses with improved segregation between distinct stimuli. Furthermore, we used donor variability to identify shared inter-cellular pathways and trace cytokine loops involved in gene expression. This provides strategies for dimension reduction of large datasets and deconvolution of innate immune responses applicable for characterizing immunomodulatory molecules. Moreover, we provide an interactive R-Shiny application with healthy donor reference values for induced inflammatory genes.
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