120 research outputs found
Joint impact of clinical and behavioral variables on the risk of unplanned readmission and death after a heart failure hospitalization
Most current methods for modeling rehospitalization events in heart failure patients make use of only clinical and medications data that is available in the electronic health records. However, information about patient-reported functional limitations, behavioral variables and socio-economic background of patients may also play an important role in predicting the risk of readmission in heart failure patients. We developed methods for predicting the risk of rehospitalization in heart failure patients using models that integrate clinical characteristics with patient-reported functional limitations, behavioral and socio-economic characteristics. Our goal was to estimate the predictive accuracy of the joint model and compare it with models that make use of clinical data alone or behavioral and socio-economic characteristics alone, using real patient data. We collected data about the occurrence of hospital readmissions from a cohort of 789 heart failure patients for whom a range of clinical and behavioral characteristics data is also available. We applied the Cox model, four different variants of the Cox proportional hazards framework as well as an alternative non-parametric approach and determined the predictive accuracy for different categories of variables. The concordance index obtained from the joint prediction model including all types of variables was significantly higher than the accuracy obtained from using only clinical factors or using only behavioral, socioeconomic background and functional limitations in patients as predictors. Collecting information on behavior, patient-reported estimates of physical limitations and frailty and socio-economic data has significant value in the predicting the risk of readmissions with regards to heart failure events and can lead to substantially more accurate events prediction models
Probability that a chromosome is lost without trace under the neutral Wright-Fisher model with recombination
I describe an analytical approximation for calculating the short-term
probability of loss of a chromosome under the neutral Wright-Fisher model with
recombination. I also present an upper and lower bound for this probability.
Exact analytical calculation of this quantity is difficult and computationally
expensive because the number of different ways in which a chromosome can be
lost, grows very large in the presence of recombination. Simulations indicate
that the probabilities obtained using my approximate formula are always
comparable to the true expectations provided that the number of generations
remains small. These results are useful in the context of an algorithm that we
recently developed for simulating Wright-Fisher populations forward in time.
C++ programs that can efficiently calculate these formulas are available on
request.Comment: Additional Information, Padhukasahasram et al. 2008, Genetics,
FORWSIM algorith
Bayesian Population Genomic Inference of Crossing Over and Gene Conversion
Meiotic recombination is a fundamental cellular mechanism in sexually reproducing organisms and its different forms, crossing over and gene conversion both play an important role in shaping genetic variation in populations. Here, we describe a coalescent-based full-likelihood Markov chain Monte Carlo (MCMC) method for jointly estimating the crossing-over, gene-conversion, and mean tract length parameters from population genomic data under a Bayesian framework. Although computationally more expensive than methods that use approximate likelihoods, the relative efficiency of our method is expected to be optimal in theory. Furthermore, it is also possible to obtain a posterior sample of genealogies for the data using this method. We first check the performance of the new method on simulated data and verify its correctness. We also extend the method for inference under models with variable gene-conversion and crossing-over rates and demonstrate its ability to identify recombination hotspots. Then, we apply the method to two empirical data sets that were sequenced in the telomeric regions of the X chromosome of Drosophila melanogaster. Our results indicate that gene conversion occurs more frequently than crossing over in the su-w and su-s gene sequences while the local rates of crossing over as inferred by our program are not low. The mean tract lengths for gene-conversion events are estimated to be ∼70 bp and 430 bp, respectively, for these data sets. Finally, we discuss ideas and optimizations for reducing the execution time of our algorithm
Presymptomatic risk assessment for chronic non-communicable diseases
The prevalence of common chronic non-communicable diseases (CNCDs) far
overshadows the prevalence of both monogenic and infectious diseases combined.
All CNCDs, also called complex genetic diseases, have a heritable genetic
component that can be used for pre-symptomatic risk assessment. Common single
nucleotide polymorphisms (SNPs) that tag risk haplotypes across the genome
currently account for a non-trivial portion of the germ-line genetic risk and
we will likely continue to identify the remaining missing heritability in the
form of rare variants, copy number variants and epigenetic modifications. Here,
we describe a novel measure for calculating the lifetime risk of a disease,
called the genetic composite index (GCI), and demonstrate its predictive value
as a clinical classifier. The GCI only considers summary statistics of the
effects of genetic variation and hence does not require the results of
large-scale studies simultaneously assessing multiple risk factors. Combining
GCI scores with environmental risk information provides an additional tool for
clinical decision-making. The GCI can be populated with heritable risk
information of any type, and thus represents a framework for CNCD
pre-symptomatic risk assessment that can be populated as additional risk
information is identified through next-generation technologies.Comment: Plos ONE paper. Previous version was withdrawn to be updated by the
journal's pdf versio
A minimal descriptor of an ancestral recombinations graph
<p>Abstract</p> <p>Background</p> <p>Ancestral Recombinations Graph (ARG) is a phylogenetic structure that encodes both duplication events, such as mutations, as well as genetic exchange events, such as recombinations: this captures the (genetic) dynamics of a population evolving over generations.</p> <p>Results</p> <p>In this paper, we identify structure-preserving and samples-preserving core of an ARG <it>G</it> and call it the minimal descriptor ARG of <it>G</it>. Its structure-preserving characteristic ensures that all the branch lengths of the marginal trees of the minimal descriptor ARG are identical to that of <it>G</it> and the samples-preserving property asserts that the patterns of genetic variation in the samples of the minimal descriptor ARG are exactly the same as that of <it>G</it>. We also prove that even an unbounded <it>G</it> has a finite minimal descriptor, that continues to preserve certain (graph-theoretic) properties of <it>G</it> and for an appropriate class of ARGs, our estimate (Eqn 8) as well as empirical observation is that the expected reduction in the number of vertices is exponential.</p> <p>Conclusions</p> <p>Based on the definition of this lossless and bounded structure, we derive local properties of the vertices of a minimal descriptor ARG, which lend itself very naturally to the design of efficient sampling algorithms. We further show that a class of minimal descriptors, that of binary ARGs, models the standard coalescent exactly (Thm 6).</p
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The Pattern of Polymorphism in <i>Arabidopsis thaliana</i>
We resequenced 876 short fragments in a sample of 96 individuals of Arabidopsis thaliana that included stock center accessions as well as a hierarchical sample from natural populations. Although A. thaliana is a selfing weed, the pattern of polymorphism in general agrees with what is expected for a widely distributed, sexually reproducing species. Linkage disequilibrium decays rapidly, within 50 kb. Variation is shared worldwide, although population structure and isolation by distance are evident. The data fail to fit standard neutral models in several ways. There is a genome-wide excess of rare alleles, at least partially due to selection. There is too much variation between genomic regions in the level of polymorphism. The local level of polymorphism is negatively correlated with gene density and positively correlated with segmental duplications. Because the data do not fit theoretical null distributions, attempts to infer natural selection from polymorphism data will require genome-wide surveys of polymorphism in order to identify anomalous regions. Despite this, our data support the utility of A. thaliana as a model for evolutionary functional genomics
Time-frequency scaling transformation of the phonocardiogram based of the matching pursuit method.
International audienceA time-frequency scaling transformation based on the matching pursuit (MP) method is developed for the phonocardiogram (PCG). The MP method decomposes a signal into a series of time-frequency atoms by using an iterative process. The modification of the time scale of the PCG can be performed without perceptible change in its spectral characteristics. It is also possible to modify the frequency scale without changing the temporal properties. The technique has been tested on 11 PCG's containing heart sounds and different murmurs. A scaling/inverse-scaling procedure was used for quantitative evaluation of the scaling performance. Both the spectrogram and a MP-based Wigner distribution were used for visual comparison in the time-frequency domain. The results showed that the technique is suitable and effective for the time-frequency scale transformation of both the transient property of the heart sounds and the more complex random property of the murmurs. It is also shown that the effectiveness of the method is strongly related to the optimization of the parameters used for the decomposition of the signals
A Model for the Effect of Homologous Recombination on Microbial Diversification
The effect of homologous recombination (HR) on the evolution of microbial genomes remains contentious as competing hypotheses seek to explain the evolutionary dynamics of microbial species. Evidence for HR between microbial genomes is widespread, and this process has been proposed to act as a cohesive force that can constrain the diversification of microbial lineages. We seek to characterize the evolutionary dynamics of sympatric populations to explore the impact of HR on microbial speciation. We describe a simple equation for quantifying the cohesive effect of HR on microbial populations as a function of their nucleotide divergence, μ/ρ = πg10 − 20 πg. The model was verified using a forward-time microbial population simulator that can explore the evolutionary dynamics of sympatric populations in nonoverlapping niche space. The model was also evaluated using multilocus sequence data from a range of microbial species, providing criteria for dividing them into either cohesively recombining or clonally diverging lineages. We conclude that models of microbial diversification that appear contradictory can be explained in a unified manner as the natural and predictable consequence of variation in a small number of population parameters
The Pattern of Polymorphism in Arabidopsis thaliana
We resequenced 876 short fragments in a sample of 96 individuals of Arabidopsis thaliana that included stock center accessions as well as a hierarchical sample from natural populations. Although A. thaliana is a selfing weed, the pattern of polymorphism in general agrees with what is expected for a widely distributed, sexually reproducing species. Linkage disequilibrium decays rapidly, within 50 kb. Variation is shared worldwide, although population structure and isolation by distance are evident. The data fail to fit standard neutral models in several ways. There is a genome-wide excess of rare alleles, at least partially due to selection. There is too much variation between genomic regions in the level of polymorphism. The local level of polymorphism is negatively correlated with gene density and positively correlated with segmental duplications. Because the data do not fit theoretical null distributions, attempts to infer natural selection from polymorphism data will require genome-wide surveys of polymorphism in order to identify anomalous regions. Despite this, our data support the utility of A. thaliana as a model for evolutionary functional genomics
Discovery and Fine-Mapping of Adiposity Loci Using High Density Imputation of Genome-Wide Association Studies in Individuals of African Ancestry: African Ancestry Anthropometry Genetics Consortium
Genome-wide association studies (GWAS) have identified \u3e 300 loci associated with measures of adiposity including body mass index (BMI) and waist-to-hip ratio (adjusted for BMI, WHRadjBMI), but few have been identified through screening of the African ancestry genomes. We performed large scale meta-analyses and replications in up to 52,895 individuals for BMI and up to 23,095 individuals for WHRadjBMI from the African Ancestry Anthropometry Genetics Consortium (AAAGC) using 1000 Genomes phase 1 imputed GWAS to improve coverage of both common and low frequency variants in the low linkage disequilibrium African ancestry genomes. In the sex-combined analyses, we identified one novel locus (TCF7L2/HABP2) for WHRadjBMI and eight previously established loci at P \u3c 5×10−8: seven for BMI, and one for WHRadjBMI in African ancestry individuals. An additional novel locus (SPRYD7/DLEU2) was identified for WHRadjBMI when combined with European GWAS. In the sex-stratified analyses, we identified three novel loci for BMI (INTS10/LPL and MLC1 in men, IRX4/IRX2 in women) and four for WHRadjBMI (SSX2IP, CASC8, PDE3B and ZDHHC1/HSD11B2 in women) in individuals of African ancestry or both African and European ancestry. For four of the novel variants, the minor allele frequency was low (\u3c5%). In the trans-ethnic fine mapping of 47 BMI loci and 27 WHRadjBMI loci that were locus-wide significant (P \u3c 0.05 adjusted for effective number of variants per locus) from the African ancestry sex-combined and sex-stratified analyses, 26 BMI loci and 17 WHRadjBMI loci contained ≤ 20 variants in the credible sets that jointly account for 99% posterior probability of driving the associations. The lead variants in 13 of these loci had a high probability of being causal. As compared to our previous HapMap imputed GWAS for BMI and WHRadjBMI including up to 71,412 and 27,350 African ancestry individuals, respectively, our results suggest that 1000 Genomes imputation showed modest improvement in identifying GWAS loci including low frequency variants. Trans-ethnic meta-analyses further improved fine mapping of putative causal variants in loci shared between the African and European ancestry populations
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