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  • 51.
    Karlsson, Måns
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Hössjer, Ola
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Classification Under Partial Reject Options2023Ingår i: Journal of Classification, ISSN 0176-4268, E-ISSN 1432-1343, artikel-id s00357-023-09455-xArtikel i tidskrift (Refereegranskat)
    Abstract [en]

    In many applications there is ambiguity about which (if any) of a finite number N of hypotheses that best fits an observation. It is of interest then to possibly output awhole set of categories, that is, a scenario where the size of the classified set of categories ranges from 0 to N. Empty sets correspond to an outlier, sets of size 1 represent a firm decision that singles out one hypothesis, sets of size N correspond to a rejection to classify, whereas sets of sizes 2,..., N - 1 represent a partial rejection to classify, where some hypotheses are excluded from further analysis. In this paper, we review and unify several proposed methods of Bayesian set-valued classification, where the objective is to find the optimal Bayesian classifier that maximizes the expected reward. We study a large class of reward functions with rewards for sets that include the true category, whereas additive or multiplicative penalties are incurred for sets depending on their size. For models with one homogeneous block of hypotheses, we provide general expressions for the accompanying Bayesian classifier, several of which extend previous results in the literature. Then, we derive novel results for the more general setting when hypotheses are partitioned into blocks, where ambiguity within and between blocks are of different severity. We also discuss how well-known methods of classification, such as conformal prediction, indifference zones, and hierarchical classification, fit into our framework. Finally, set-valued classification is illustrated using an ornithological data set, with taxa partitioned into blocks and parameters estimated using MCMC. The associated reward function's tuning parameters are chosen through cross-validation.

  • 52.
    Karlsson, Måns
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Hössjer, Ola
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Identification of taxon through classification with partial reject options2023Ingår i: The Journal of the Royal Statistical Society, Series C: Applied Statistics, ISSN 0035-9254, E-ISSN 1467-9876, Vol. 72, nr 4, s. 937-975Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Identification of taxa can significantly be assisted by statistical classification based on trait measurements either individually or by phylogenetic (clustering) methods. In this article, we present a general Bayesian approach for classifying species individually based on measurements of a mixture of continuous and ordinal traits, and any type of covariates. The trait vector is derived from a latent variable with a multivariate Gaussian distribution. Decision rules based on supervised learning are presented that estimate model parameters through blocked Gibbs sampling. These decision regions allow for uncertainty (partial rejection), so that not necessarily one specific category (taxon) is output when new subjects are classified, but rather a set of categories including the most probable taxa. This type of discriminant analysis employs reward functions with a set-valued input argument, so that an optimal Bayes classifier can be defined. We also present a way of safeguarding against outlying new observations, using an analogue of a p-value within our Bayesian setting. We refer to our Bayesian set-valued classifier as the Karlsson–Hössjer method, and it is illustrated on an original ornithological data set of birds. We also incorporate model selection through cross-validation, exemplified on another original data set of birds. 

  • 53. Kurbasic, Azra
    et al.
    Hössjer, Ola
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    A general method of linkage disequilibrium correction for multipoint linkage and association2008Ingår i: Genetic Epidemiology, Vol. 32, s. 647-657Artikel i tidskrift (Refereegranskat)
  • 54.
    Kurland, Sara
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Zoologiska institutionen, Avdelningen för populationsgenetik.
    Ryman, Nils
    Stockholms universitet, Naturvetenskapliga fakulteten, Zoologiska institutionen, Avdelningen för populationsgenetik.
    Hössjer, Ola
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Laikre, Linda
    Stockholms universitet, Naturvetenskapliga fakulteten, Zoologiska institutionen, Avdelningen för populationsgenetik.
    Effects of subpopulation extinction on effective size (Ne) of metapopulations2023Ingår i: Conservation Genetics, ISSN 1566-0621, E-ISSN 1572-9737, Vol. 24, nr 4, s. 417-433Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Population extinction is ubiquitous in all taxa. Such extirpations can reduce intraspecific diversity, but the extent to which genetic diversity of surviving populations are affected remains largely unclear. A key concept in this context is the effective population size (Ne), which quantifies the rate at which genetic diversity within populations is lost. Ne was developed for single, isolated populations while many natural populations are instead connected to other populations via gene flow. Recent analytical approaches and software permit modelling of Ne of interconnected populations (metapopulations). Here, we apply such tools to investigate how extinction of subpopulations affects Ne of the metapopulation (NeMeta) and of separate surviving subpopulations (NeRx) under different rates and patterns of genetic exchange between subpopulations. We assess extinction effects before and at migration-drift equilibrium. We find that the effect of extinction on NeMeta increases with reduced connectivity, suggesting that stepping stone models of migration are more impacted than island-migration models when the same number of subpopulations are lost. Furthermore, in stepping stone models, after extinction and before a new equilibrium has been reached, NeRx can vary drastically among surviving subpopulations and depends on their initial spatial position relative to extinct ones. Our results demonstrate that extinctions can have far more complex effects on the retention of intraspecific diversity than typically recognized. Metapopulation dynamics need heightened consideration in sustainable management and conservation, e.g., in monitoring genetic diversity, and are relevant to a wide range of species in the ongoing extinction crisis. 

  • 55.
    Laikre, Linda
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Zoologiska institutionen.
    Olsson, Fredrik
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Jansson, Eeva
    Stockholms universitet, Naturvetenskapliga fakulteten, Zoologiska institutionen.
    Hössjer, Ola
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Ryman, Nils
    Stockholms universitet, Naturvetenskapliga fakulteten, Zoologiska institutionen.
    Metapopulation effective size and conservation genetic goals for the Fennoscandian wolf (Canis lupus) population2016Ingår i: Heredity, ISSN 0018-067X, E-ISSN 1365-2540, Vol. 117, nr 4, s. 279-289Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The Scandinavian wolf population descends from only five individuals, is isolated, highly inbred and exhibits inbreeding depression. To meet international conservation goals, suggestions include managing subdivided wolf populations over Fennoscandia as a metapopulation; a genetically effective population size of N-e >= 500, in line with the widely accepted long-term genetic viability target, might be attainable with gene flow among subpopulations of Scandinavia, Finland and Russian parts of Fennoscandia. Analytical means for modeling N-e of subdivided populations under such non-idealized situations have been missing, but we recently developed new mathematical methods for exploring inbreeding dynamics and effective population size of complex metapopulations. We apply this theory to the Fennoscandian wolves using empirical estimates of demographic parameters. We suggest that the long-term conservation genetic target for metapopulations should imply that inbreeding rates in the total system and in the separate subpopulations should not exceed Delta f = 0.001. This implies a meta-Ne of N-eMeta >= 500 and a realized effective size of each subpopulation of N-eRx >= 500. With current local effective population sizes and one migrant per generation, as recommended by management guidelines, the meta-Ne that can be reached is similar to 250. Unidirectional gene flow from Finland to Scandinavia reduces meta-N-e to similar to 130. Our results indicate that both local subpopulation effective sizes and migration among subpopulations must increase substantially from current levels to meet the conservation target. Alternatively, immigration from a large (N-e >= 500) population in northwestern Russia could support the Fennoscandian metapopulation, but immigration must be substantial (5-10 effective immigrants per generation) and migration among Fennoscandian subpopulations must nevertheless increase.

  • 56. Lekman, Magnus
    et al.
    Hössjer, Ola
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Andrews, Peter
    Källberg, Henrik
    Uvehag, Daniel
    Charney, Dennis
    Manji, Husseini
    Rush, John A.
    McMahon, Francis J.
    Moore, Jason H.
    Kockum, Ingrid
    The genetic interacting landscape of 63 candidate genes in Major Depressive Disorder: an explorative study2014Ingår i: BioData Mining, E-ISSN 1756-0381, Vol. 7, s. 19-Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Background: Genetic contributions to major depressive disorder (MDD) are thought to result from multiple genes interacting with each other. Different procedures have been proposed to detect such interactions. Which approach is best for explaining the risk of developing disease is unclear. This study sought to elucidate the genetic interaction landscape in candidate genes for MDD by conducting a SNP-SNP interaction analysis using an exhaustive search through 3,704 SNP-markers in 1,732 cases and 1,783 controls provided from the GAIN MDD study. We used three different methods to detect interactions, two logistic regressions models (multiplicative and additive) and one data mining and machine learning (MDR) approach. Results: Although none of the interaction survived correction for multiple comparisons, the results provide important information for future genetic interaction studies in complex disorders. Among the 0.5% most significant observations, none had been reported previously for risk to MDD. Within this group of interactions, less than 0.03% would have been detectable based on main effect approach or an a priori algorithm. We evaluated correlations among the three different models and conclude that all three algorithms detected the same interactions to a low degree. Although the top interactions had a surprisingly large effect size for MDD (e. g. additive dominant model P-uncorrected = 9.10E-9 with attributable proportion (AP) value = 0.58 and multiplicative recessive model with P-uncorrected = 6.95E-5 with odds ratio (OR estimated from beta 3) value = 4.99) the area under the curve (AUC) estimates were low (< 0.54). Moreover, the population attributable fraction (PAF) estimates were also low (< 0.15). Conclusions: We conclude that the top interactions on their own did not explain much of the genetic variance of MDD. The different statistical interaction methods we used in the present study did not identify the same pairs of interacting markers. Genetic interaction studies may uncover previously unsuspected effects that could provide novel insights into MDD risk, but much larger sample sizes are needed before this strategy can be powerfully applied.

  • 57. Lekman, Magnus
    et al.
    Karlsson, Robert
    Graae, Lisette
    Hössjer, Ola
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Kockum, Ingrid
    A significant risk locus on 19q13 for bipolar disorder identified using a combined genome-wide linkage and copy number variation analysis2015Ingår i: BioData Mining, E-ISSN 1756-0381, Vol. 8, artikel-id 42Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Background: The genetic background to bipolar disorder (BPD) has been attributed to different genetic and genomic risk factors. In the present study we hypothesized that inherited copy number variations (CNVs) contribute to susceptibility of BPD. We screened 637 BP-pedigrees from the NIMH Genetic Initiative and gave priority to 46 pedigrees. In this subsample we performed parametric and non-parametric genome-wide linkage analyses using similar to 21,000 SNP-markers. We developed an algorithm to test for linkage restricted to regions with CNVs that are shared within and across families. Results: For the combined CNV and linkage analysis, one region on 19q13 survived correction for multiple comparisons and replicates a previous BPD risk locus. The shared CNV map to the pregnancy-specific glycoprotein (PSG) gene, a gene-family not previously implicated in BPD etiology. Two SNPs in the shared CNV are likely transcription factor binding sites and are linked to expression of an F-box binding gene, a key regulator of neuronal pathways suggested to be involved in BPD etiology. Conclusions: Our CNV-weighted linkage approach identifies a risk locus for BPD on 19q13 and forms a useful tool to future studies to unravel part of the genetic vulnerability to BPD.

  • 58.
    Malmberg, Hannes
    et al.
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Institutet för internationell ekonomi.
    Hössjer, Ola
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Argmax over continuous indeces of random variables - an approach using random fields2012Rapport (Övrigt vetenskapligt)
  • 59.
    Malmberg, Hannes
    et al.
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Institutet för internationell ekonomi.
    Hössjer, Ola
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Probabilistic choice with an infinite set of options: An Approach Based on Random Sup Measures2014Ingår i: Modern Problems in Insurance Mathematics / [ed] Dmitrii Silvestrov, Anders Martin-Löf, London: Springer, 2014, s. 291-312Kapitel i bok, del av antologi (Refereegranskat)
    Abstract [en]

    This chapter deals with probabilistic choice when the number of options is infinite. The choice space is a compact set S⊆R k   and we model choice over S  as a limit of choices over triangular sequences {x n1 ,…,x nn }⊆S  as n→∞  . We employ the theory of random sup measures and show that in the limit when n→∞  , people behave as though they are maximising over a random sup measure. Thus, our results complement Resnick and Roy’s [18] theory of probabilistic choice over infinite sets. They define choice as a maximisation over a stochastic process on S  with upper semi-continuous (usc) paths. This connects to our model as their random usc function can be defined as a sup-derivative of a random sup measure, and their maximisation problem can be transformed into a maximisation problem over this random sup measure. One difference remains though: with our model the limiting random sup measures are independently scattered, without usc paths. A benefit of our model is that we provide a way of connecting the stochastic process in their model with finite case distributional assumptions, which are easier to interpret. In particular, when choices are valued additively with one deterministic and one random part, we explore the importance of the tail behaviour of the random part, and show that the exponential distribution is an important boundary case between heavy-tailed and light-tailed distributions.

  • 60.
    Olsson, Fredrik
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Hössjer, Ola
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Equilibrium distributions and simulation methods for age structured populations2015Ingår i: Mathematical Biosciences, ISSN 0025-5564, E-ISSN 1879-3134, Vol. 268, s. 45-51Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A simulation method is presented for the demographic and genetic variation of age structured haploid populations. First, we use matrix analytic methods to derive an equilibrium distribution for the age class sizes conditioned on the total population size. Knowledge of this distribution eliminates the need of a burn-in time in simulations. Next, we derive the distribution of the alleles at a polymorphic locus in various age classes given the allele frequencies in the total population and the age size composition. For the time dynamics, we start by simulating the dynamics for the total population. In order to generate the inheritance of the alleles, we derive their distribution conditionally on the simulated population sizes. This method enables a fast simulation procedure of multiple loci in linkage equilibrium.

  • 61.
    Olsson, Fredrik
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Hössjer, Ola
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Estimation of the variance effective population size in age structured populations2015Ingår i: Theoretical Population Biology, ISSN 0040-5809, E-ISSN 1096-0325, Vol. 101, s. 9-23Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The variance effective population size for age structured populations is generally hard to estimate and the temporal method often gives biased estimates. Here, we give an explicit expression for a correction factor which, combined with estimates from the temporal method, yield approximately unbiased estimates. The calculation of the correction factor requires knowledge of the age specific offspring distribution and survival probabilities as well as possible correlation between survival and reproductive success. In order to relax these requirements, we show that only first order moments of these distributions need to be known if the time between samples is large, or individuals from all age classes which reproduce are sampled. A very explicit approximate expression for the asymptotic coefficient of standard deviation of the estimator is derived, and it can be used to construct confidence intervals and optimal ways of weighting information from different markers. The asymptotic coefficient of standard deviation can also be used to design studies and we show that in order to maximize the precision for a given sample size, individuals from older age classes should be sampled since their expected variance of allele frequency change is higher and easier to estimate. However, for populations with fluctuating age class sizes, the accuracy of the method is reduced when samples are taken from older age classes with high demographic variation. We also present a method for simultaneous estimation of the variance effective and census population size.

  • 62.
    Olsson, Fredrik
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Hössjer, Ola
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Laikre, Linda
    Stockholms universitet, Naturvetenskapliga fakulteten, Zoologiska institutionen.
    Ryman, Nils
    Stockholms universitet, Naturvetenskapliga fakulteten, Zoologiska institutionen.
    Characteristics of the variance effective population size over time using an age structured model with variable size2013Ingår i: Theoretical Population Biology, ISSN 0040-5809, E-ISSN 1096-0325, Vol. 90, s. 91-103Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The variance effective population size (N-ev) is a key concept in population biology, because it quantifies the microevolutionary process of random genetic drift, and understanding the characteristics of N-ev is thus of central importance. Current formulas for Nev for populations with overlapping generations weight age classes according to their reproductive values (i.e. reflecting the contribution of genes from separate age classes to the population growth) to obtain a correct measure of genetic drift when computing the variance of the allele frequency change over time. In this paper, we examine the effect of applying different weights to the age classes using a novel analytical approach for exploring N-ev. We consider a haploid organism with overlapping generations and populations of increasing, declining, or constant expected size and stochastic variation with respect to the number of individuals in the separate age classes. We define Nov, as a function of how the age classes are weighted, and of the span between the two points in time, when measuring allele frequency change. With this model, time profiles for N-ev can be calculated for populations with various life histories and with fluctuations in life history composition, using different weighting schemes. We examine analytically and by simulations when Nei, using a weighting scheme with respect to reproductive contribution of separate age classes, accurately reflect the variance of the allele frequency change due to genetic drift over time. We show that the discrepancy of N-ev, calculated with reproductive values as weights, compared to when individuals are weighted equally, tends to a constant when the time span between the two measurements increases. This constant is zero only for a population with a constant expected population size. Our results confirm that the effect of ignoring overlapping generations, when empirically assessing Nell from allele frequency shifts, gets smaller as the time interval between samples increases. Our model has empirical applications including assessment of (i) time intervals necessary to permit ignoring the effect of overlapping generations for N-ev estimation by means of the temporal method, and (ii) effects of life table manipulation on N-ev over varying time periods.

  • 63.
    Olsson, Fredrik
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Laikre, Linda
    Stockholms universitet, Naturvetenskapliga fakulteten, Zoologiska institutionen.
    Hössjer, Ola
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Ryman, Nils
    Stockholms universitet, Naturvetenskapliga fakulteten, Zoologiska institutionen.
    GESP: A computer program for modelling genetic effective population size, inbreeding and divergence in substructured populations2017Ingår i: Molecular Ecology Resources, ISSN 1755-098X, E-ISSN 1755-0998, Vol. 17, nr 6, s. 1378-1384Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The genetically effective population size (N-e) is of key importance for quantifying rates of inbreeding and genetic drift and is often used in conservation management to set targets for genetic viability. The concept was developed for single, isolated populations and the mathematical means for analysing the expected N-e in complex, subdivided populations have previously not been available. We recently developed such analytical theory and central parts of that work have now been incorporated into a freely available software tool presented here. gesp (Genetic Effective population size, inbreeding and divergence in Substructured Populations) is R-based and designed to model short- and long-term patterns of genetic differentiation and effective population size of subdivided populations. The algorithms performed by gesp allow exact computation of global and local inbreeding and eigenvalue effective population size, predictions of genetic divergence among populations (G(ST)) as well as departures from random mating (F-IS, F-IT) while varying (i) subpopulation census and effective size, separately or including trend of the global population size, (ii) rate and direction of migration between all pairs of subpopulations, (iii) degree of relatedness and divergence among subpopulations, (iv) ploidy (haploid or diploid) and (v) degree of selfing. Here, we describe gesp and exemplify its use in conservation genetics modelling.

  • 64.
    Ryman, Nils
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Zoologiska institutionen.
    Allendorf, Fred W.
    Jorde, Per Erik
    Laikre, Linda
    Stockholms universitet, Naturvetenskapliga fakulteten, Zoologiska institutionen.
    Hössjer, Ola
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Samples from subdivided populations yield biased estimates of effective size that overestimate the rate of loss of genetic variation2014Ingår i: Molecular Ecology Resources, ISSN 1755-098X, E-ISSN 1755-0998, Vol. 14, nr 1, s. 87-99Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Many empirical studies estimating effective population size apply the temporal method that provides an estimate of the variance effective size through the amount of temporal allele frequency change under the assumption that the study population is completely isolated. This assumption is frequently violated, and the magnitude of the resulting bias is generally unknown. We studied how gene flow affects estimates of effective size obtained by the temporal method when sampling from a population system and provide analytical expressions for the expected estimate under an island model of migration. We show that the temporal method tends to systematically underestimate both local and global effective size when populations are connected by gene flow, and the bias is sometimes dramatic. The problem is particularly likely to occur when sampling from a subdivided population where high levels of gene flow obscure identification of subpopulation boundaries. In such situations, sampling in a manner that prevents biased estimates can be difficult. This phenomenon might partially explain the frequently reported unexpectedly low effective population sizes of marine populations that have raised concern regarding the genetic vulnerability of even exceptionally large populations.

  • 65.
    Ryman, Nils
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Zoologiska institutionen.
    Laikre, Linda
    Stockholms universitet, Naturvetenskapliga fakulteten, Zoologiska institutionen.
    Hössjer, Ola
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Do estimates of contemporary effective population size tell us what we want to know?2019Ingår i: Molecular Ecology, ISSN 0962-1083, E-ISSN 1365-294X, Vol. 28, nr 8, s. 1904-1918Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Estimation of effective population size (N-e) from genetic marker data is a major focus for biodiversity conservation because it is essential to know at what rates inbreeding is increasing and additive genetic variation is lost. But are these the rates assessed when applying commonly used N-e estimation techniques? Here we use recently developed analytical tools and demonstrate that in the case of substructured populations the answer is no. This is because the following: Genetic change can be quantified in several ways reflecting different types of N-e such as inbreeding (N-eI), variance (N-eV), additive genetic variance (N-eAV), linkage disequilibrium equilibrium (N-eLD), eigenvalue (N-eE) and coalescence (N-eCo) effective size. They are all the same for an isolated population of constant size, but the realized values of these effective sizes can differ dramatically in populations under migration. Commonly applied N-e-estimators target N-eV or N(eLD )of individual subpopulations. While such estimates are safe proxies for the rates of inbreeding and loss of additive genetic variation under isolation, we show that they are poor indicators of these rates in populations affected by migration. In fact, both the local and global inbreeding (N-eI) and additive genetic variance (N-eAV) effective sizes are consistently underestimated in a subdivided population. This is serious because these are the effective sizes that are relevant to the widely accepted 50/500 rule for short and long term genetic conservation. The bias can be infinitely large and is due to inappropriate parameters being estimated when applying theory for isolated populations to subdivided ones.

  • 66.
    Ryman, Nils
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Zoologiska institutionen, Avdelningen för populationsgenetik.
    Laikre, Linda
    Stockholms universitet, Naturvetenskapliga fakulteten, Zoologiska institutionen, Avdelningen för populationsgenetik.
    Hössjer, Ola
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Variance effective population size is affected by census size in sub-structured populations2023Ingår i: Molecular Ecology Resources, ISSN 1755-098X, E-ISSN 1755-0998, Vol. 23, nr 6, s. 1334-1347Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Measurement of allele frequency shifts between temporally spaced samples has long been used for assessment of effective population size (N-e), and this 'temporal method' provides estimates of N-e referred to as variance effective size (N-eV). We show that N-eV of a local population that belongs to a sub-structured population (a metapopulation) is determined not only by genetic drift and migration rate (m), but also by the census size (N-c). The realized N-eV of a local population can either increase or decrease with increasing m, depending on the relationship between N-e and N-c in isolation. This is shown by explicit mathematical expressions for the factors affecting N-eV derived for an island model of migration. We verify analytical results using high-resolution computer simulations, and show that the phenomenon is not restricted to the island model migration pattern. The effect of N-c on the realized N-eV of a local subpopulation is most pronounced at high migration rates. We show that N-c only affects local N-eV, whereas N-eV for the metapopulation as a whole, inbreeding (N-eI), and linkage disequilibrium (N-eLD) effective size are all independent of N-c. Our results provide a possible explanation to the large variation of N-e/N-c ratios reported in the literature, where N-e is frequently estimated by N-eV. They are also important for the interpretation of empirical N-e estimates in genetic management where local N-eV is often used as a substitute for inbreeding effective size, and we suggest an increased focus on metapopulation N-eV as a proxy for N-eI.

  • 67.
    Saha, Atal
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Zoologiska institutionen, Avdelningen för populationsgenetik.
    Andersson, Anastasia
    Stockholms universitet, Naturvetenskapliga fakulteten, Zoologiska institutionen, Avdelningen för populationsgenetik.
    Kurland, Sara
    Stockholms universitet, Naturvetenskapliga fakulteten, Zoologiska institutionen, Avdelningen för populationsgenetik.
    Keehnen, Naomi L. P.
    Stockholms universitet, Naturvetenskapliga fakulteten, Zoologiska institutionen, Avdelningen för populationsgenetik.
    Kutschera, Verena E.
    Stockholms universitet, Science for Life Laboratory (SciLifeLab). Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för biokemi och biofysik.
    Ekman, Diana
    Stockholms universitet, Science for Life Laboratory (SciLifeLab). Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för biokemi och biofysik.
    Karlsson, Sten
    Kardos, Marty
    Hössjer, Ola
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Ståhl, Gunnar
    Allendorf, Fred W.
    Ryman, Nils
    Stockholms universitet, Naturvetenskapliga fakulteten, Zoologiska institutionen, Avdelningen för populationsgenetik.
    Laikre, Linda
    Stockholms universitet, Naturvetenskapliga fakulteten, Zoologiska institutionen, Avdelningen för populationsgenetik.
    Whole-genome resequencing confirms reproductive isolation between sympatric demes of brown trout (Salmo trutta) detected with allozymesManuskript (preprint) (Övrigt vetenskapligt)
  • 68.
    Saha, Atal
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Zoologiska institutionen, Avdelningen för populationsgenetik.
    Andersson, Anastasia
    Stockholms universitet, Naturvetenskapliga fakulteten, Zoologiska institutionen, Avdelningen för populationsgenetik.
    Kurland, Sara
    Stockholms universitet, Naturvetenskapliga fakulteten, Zoologiska institutionen, Avdelningen för populationsgenetik.
    Pruisscher Keehnen, Naomi Larissa
    Stockholms universitet, Naturvetenskapliga fakulteten, Zoologiska institutionen, Avdelningen för populationsgenetik.
    Kutschera, Verena E.
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för biokemi och biofysik. Stockholms universitet, Science for Life Laboratory (SciLifeLab).
    Hössjer, Ola
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Ekman, Diana
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för biokemi och biofysik. Stockholms universitet, Science for Life Laboratory (SciLifeLab).
    Karlsson, Sten
    Kardos, Marty
    Ståhl, Gunnar
    Allendorf, Fred W.
    Ryman, Nils
    Stockholms universitet, Naturvetenskapliga fakulteten, Zoologiska institutionen, Avdelningen för populationsgenetik.
    Laikre, Linda
    Stockholms universitet, Naturvetenskapliga fakulteten, Zoologiska institutionen, Avdelningen för populationsgenetik.
    Whole-genome resequencing confirms reproductive isolation between sympatric demes of brown trout (Salmo trutta) detected with allozymes2022Ingår i: Molecular Ecology, ISSN 0962-1083, E-ISSN 1365-294X, Vol. 31, nr 2, s. 498-511Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The sympatric existence of genetically distinguishable populations of the same species remains a puzzle in ecology. Coexisting salmonid fish populations are known from over 100 freshwater lakes. Most studies of sympatric populations have used limited numbers of genetic markers making it unclear if genetic divergence involves certain parts of the genome. We returned to the first reported case of salmonid sympatry, initially detected through contrasting homozygosity at a single allozyme locus (coding for lactate dehydrogenase A) in brown trout in the small Lakes Bunnersjöarna, Sweden. First, we verified the existence of the two coexisting demes using a 96-SNP fluidigm array. We then applied whole-genome resequencing of pooled DNA to explore genome-wide diversity within and between these demes; nucleotide diversity was higher in deme I than in deme II. Strong genetic divergence is observed with genome-wide FST ≈ 0.2. Compared with data from populations of similar small lakes, this divergence is of similar magnitude as that between reproductively isolated populations. Individual whole-genome resequencing of two individuals per deme suggests higher inbreeding in deme II versus deme I, indicating different degree of isolation. We located two gene-copies for LDH-A and found divergence between demes in a regulatory section of one of these genes. However, we did not find a perfect fit between the sequence data and previous allozyme results, and this will require further research. Our data demonstrates genome-wide divergence governed mostly by genetic drift but also by diversifying selection in coexisting populations. This type of hidden biodiversity needs consideration in conservation management.

  • 69.
    Silvestrov, Dmitrii
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Petersson, Mikael
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Hössjer, Ola
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Nonlinearly perturbed birth-death-type models2018Ingår i: Stochastic Processes and Applications: SPAS2017, Västerås and Stockholm, Sweden, October 4–6, 2017 / [ed] Sergei Silvestrov, Anatoliy Malyarenko, Milica Rančić, Cham: Springer , 2018, s. 189-244Kapitel i bok, del av antologi (Refereegranskat)
    Abstract [en]

    Asymptotic expansions are presented for stationary and conditional quasi-stationary distributions of nonlinearly perturbed birth-death-type semi-Markov models, as well as algorithms for computing the coefficients of these expansions. Three types of applications are discussed in detail. The first is a model of population growth, where either an isolated population is perturbed by immigration, or a sink population with immigration is perturbed by internal births. The second application is epidemic spread of disease, in which a closed population is perturbed by infected individuals from outside. The third model captures the time dynamics of the genetic composition of a population with genetic drift and selection, that is perturbed by various mutation scenarios.

  • 70.
    Silvestrov, Dmitrii
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Petersson, Mikael
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Hössjer, Ola
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Nonlinearly perturbed birth-death-type models2016Rapport (Övrigt vetenskapligt)
    Abstract [en]

    Asymptotic expansions for stationary and conditional quasi-stationary distributions of nonlinearly perturbed birth-death-type semi-Markov models are presented. Applications to models of population growth, epidemic spread and population genetics are discussed.

  • 71. Sjölander, Arvid
    et al.
    Hartman-Werner, Linda
    Hössjer, Ola
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Humphreys, Keith
    Fine mapping of disease genes using tagging SNPs2007Ingår i: Annals of Human Genetics, Vol. 71, nr 6, s. 815-827Artikel i tidskrift (Övrig (populärvetenskap, debatt, mm))
  • 72. Sjölander, Arvid
    et al.
    Hössjer, Ola
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Novel bounds for causal effects based on sensitivity parameters on the risk difference scale2021Ingår i: Journal of Causal Inference, ISSN 2193-3677, E-ISSN 2193-3685, Vol. 9, nr 1, s. 190-210Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Unmeasured confounding is an important threat to the validity of observational studies. A common way to deal with unmeasured confounding is to compute bounds for the causal effect of interest, that is, a range of values that is guaranteed to include the true effect, given the observed data. Recently, bounds have been proposed that are based on sensitivity parameters, which quantify the degree of unmeasured confounding on the risk ratio scale. These bounds can be used to compute an E-value, that is, the degree of confounding required to explain away an observed association, on the risk ratio scale. We complement and extend this previous work by deriving analogous bounds, based on sensitivity parameters on the risk difference scale. We show that our bounds can also be used to compute an E-value, on the risk difference scale. We compare our novel bounds with previous bounds through a real data example and a simulation study.

  • 73. Thorvaldsen, Steinar
    et al.
    Hössjer, Ola
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Estimating the information content of genetic sequence data2023Ingår i: The Journal of the Royal Statistical Society, Series C: Applied Statistics, ISSN 0035-9254, E-ISSN 1467-9876, Vol. 72, nr 5, s. 1310-1338Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A prominent problem in analysing genetic information has been a lack of mathematical frameworks for doing so. This article offers some new statistical methods to model and analyse information content in proteins, protein families, and their sequences. We discuss how to understand the qualitative aspects of genetic information, how to estimate the quantitative aspects of it, and implement a statistical model where the qualitative genetic function is represented jointly with its probabilistic metric of self-information. The functional information of protein families in the Cath and Pfam databases are estimated using a method inspired by rejection sampling. Scientific work may place these components of information as one of the fundamental aspects of molecular biology.

  • 74. Thorvaldsen, Steinar
    et al.
    Hössjer, Ola
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Using statistical methods to model the fine-tuning of molecular machines and systems2020Ingår i: Journal of Theoretical Biology, ISSN 0022-5193, E-ISSN 1095-8541, Vol. 501, artikel-id 110352Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Fine-tuning has received much attention in physics, and it states that the fundamental constants of physics are finely tuned to precise values for a rich chemistry and life permittance. It has not yet been applied in a broad manner to molecular biology. However, in this paper we argue that biological systems present fine-tuning at different levels, e.g. functional proteins, complex biochemical machines in living cells, and cellular networks. This paper describes molecular fine-tuning, how it can be used in biology, and how it challenges conventional Darwinian thinking. We also discuss the statistical methods underpinning fine-tuning and present a framework for such analysis.

  • 75. Verrall, Richard
    et al.
    Hössjer, Ola
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Björkwall, Susanna
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Modelling claims run off with reversible jump markov chain Monte Carlo methods2012Ingår i: Astin Bulletin: Actuarial Studies in Non-Life Insurance, ISSN 0515-0361, E-ISSN 1783-1350, Vol. 42, nr 1, s. 35-58Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In this paper we describe a new approach to modelling the development of claims run-off triangles. This method replaces the usual ad hoc practical process of extrapolating a development pattern to obtain tail factors with an objective procedure. An example is given, illustrating the results in a practical context, and the WinBUGS code is supplied.

  • 76.
    Verrall, Richard
    et al.
    City University, Cass Business School.
    Hössjer, Ola
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Björkwall, Susanna
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Modelling claims run-off with reversible jump Markov chain Monte Carlo methodsManuskript (preprint) (Övrigt vetenskapligt)
  • 77. Zhou, Lili
    et al.
    Díaz-Pachón, Daniel Andrés
    Zhao, Chen
    Rao, J. Sunil
    Hössjer, Ola
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Correcting prevalence estimation for biased sampling with testing errors2023Ingår i: Statistics in Medicine, ISSN 0277-6715, E-ISSN 1097-0258, Vol. 42, nr 26, s. 4713-4737Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Sampling for prevalence estimation of infection is subject to bias by both oversampling of symptomatic individuals and error-prone tests. This results in naïve estimators of prevalence (ie, proportion of observed infected individuals in the sample) that can be very far from the true proportion of infected. In this work, we present a method of prevalence estimation that reduces both the effect of bias due to testing errors and oversampling of symptomatic individuals, eliminating it altogether in some scenarios. Moreover, this procedure considers stratified errors in which tests have different error rate profiles for symptomatic and asymptomatic individuals. This results in easily implementable algorithms, for which code is provided, that produce better prevalence estimates than other methods (in terms of reducing and/or removing bias), as demonstrated by formal results, simulations, and on COVID-19 data from the Israeli Ministry of Health.

  • 78. Ängquist, Lars
    et al.
    Hössjer, Ola
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Groop, Leif
    Strategies for conditional two-locus nonparametric linkage analysis2008Ingår i: Human Heredity, Vol. 66, s. 138-156Artikel i tidskrift (Refereegranskat)
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