| 1. |
- Johnsson, Kerstin, et al.
(författare)
-
What is a “unimodal” cell population? Using statistical tests as criteria for unimodality in automated gating and quality control
- 2017
-
Ingår i: Cytometry Part A. - : Wiley. - 1552-4922. ; 91:9, s. 908-916
-
Tidskriftsartikel (refereegranskat)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.
|
|
| 2. |
- Bordería, Antonio V, et al.
(författare)
-
Group Selection and Contribution of Minority Variants during Virus Adaptation Determines Virus Fitness and Phenotype.
- 2015
-
Ingår i: PLoS Pathogens. - : Public Library of Science (PLoS). - 1553-7366 .- 1553-7374. ; 11:5
-
Tidskriftsartikel (refereegranskat)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.
|
|
| 3. |
- Clave, Emmanuel, et al.
(författare)
-
Human thymopoiesis is influenced by a common genetic variant within the TCRA-TCRD locus
- 2018
-
Ingår i: Science Translational Medicine. - : American Association for the Advancement of Science (AAAS). - 1946-6234 .- 1946-6242. ; 10:457
-
Tidskriftsartikel (refereegranskat)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.
|
|
| 4. |
- Henningsson, Rasmus, et al.
(författare)
-
SMSSVD : SubMatrix Selection Singular Value Decomposition
- 2019
-
Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 35:3, s. 478-486
-
Tidskriftsartikel (refereegranskat)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.
|
|
| 5. |
- Johnsson, Kerstin, et al.
(författare)
-
BayesFlow: latent modeling of flow cytometry cell populations
- 2016
-
Ingår i: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 17:25
-
Tidskriftsartikel (refereegranskat)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.
|
|
| 6. |
- Johnsson, Kerstin, et al.
(författare)
-
Low Bias Local Intrinsic Dimension Estimation from Expected Simplex Skewness
- 2015
-
Ingår i: IEEE Transactions on Pattern Analysis and Machine Intelligence. - 1939-3539. ; 37:1, s. 196-202
-
Tidskriftsartikel (refereegranskat)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.
|
|
| 7. |
- Lilljebjörn, Henrik, et al.
(författare)
-
Identification of ETV6-RUNX1-like and DUX4-rearranged subtypes in paediatric B-cell precursor acute lymphoblastic leukaemia
- 2016
-
Ingår i: Nature Communications. - : NATURE PUBLISHING GROUP. - 2041-1723. ; 7:11790
-
Tidskriftsartikel (refereegranskat)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.
|
|
| 8. |
- Patin, Etienne, et al.
(författare)
-
Natural variation in the parameters of innate immune cells is preferentially driven by genetic factors
- 2018
-
Ingår i: Nature Immunology. - : Springer Science and Business Media LLC. - 1529-2908 .- 1529-2916. ; 19, s. 302-314
-
Tidskriftsartikel (refereegranskat)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.
|
|
| 9. |
- Rodriguez-Roche, Rosmari, et al.
(författare)
-
Increasing clinical severity during a dengue virus type 3 Cuban epidemic: deep sequencing of evolving viral populations
- 2016
-
Ingår i: Journal of Virology. - 1098-5514. ; 90:19, s. 4320-4333
-
Tidskriftsartikel (refereegranskat)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.
|
|
| 10. |
- Scharff, Anna Zychlinsky, et al.
(författare)
-
Sex differences in IL-17 contribute to chronicity in male versus female urinary tract infection
- 2019
-
Ingår i: JCI Insight. - : American Society for Clinical Investigation. - 2379-3708. ; 4:13
-
Tidskriftsartikel (refereegranskat)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.
|
|
