Biology subjects

Schreiber, S.

Publications and source records attributed to Schreiber, S..

75 records · Page 5Linked to original sources

bioRxiv2017

Identifying Crohns disease signal from variome analysis

BackgroundAfter many years of concentrated research efforts, the exact cause of Crohns disease remains unknown. Its accurate diagnosis, however, helps in management and even preventing the onset of disease. Genome-wide association studies have identified 140 loci associated with CD, but these carry very small log odds ratios and are uninformative for diagnoses.\n\nResultsHere we describe a machine learning method - AVA,Dx (Analysis of Variation for Association with Disease) - that uses whole exome sequencing data to make predictions of CD status. Using the person-specific variation in these genes from a panel of only 111 individuals, we built disease-prediction models informative of previously undiscovered disease genes. In this panel, our models differentiate CD patients from healthy controls with 71% precision and 73% recall at the default cutoff. By additionally accounting for batch effects, we are also able to predict individual CD status for previously unseen individuals from a separate CD study (84% precision, 73% recall).\n\nConclusionsLarger training panels and additional features, including regulatory variants and environmental factors, e.g. human-associated microbiota, are expected to improve model performance. However, current results already position AVA,Dx as both an effective method for highlighting pathogenesis pathways and as a simple Crohns disease risk analysis tool, which can improve clinical diagnostic time and accuracy.

bioinformatics↗

bioRxiv2017

The structured demography of open populations in fluctuating environments

At the spatial scale relevant to many field studies and management policies, populations may experience more external recruitment than internal recruitment. These sources of recruitment, as well as local demography, are often subject to stochastic fluctuations in environmental conditions. Here, we introduce a class of stochastic models accounting for these complexities and provide analytic methods for understanding their long-term behavior. The population state n(x) of these stochastic models is a function or vector keeping track of densities of individuals with continuous (e.g. size) or discrete (e.g. age) traits x taking values in a compact metric space. This state variable is updated by a stochastic affine equation nt+1 = At+1nt + bt+1 where At+1 is a time varying operator (e.g. an integral operator or a matrix) that updates the local demography, and bt+1 is a time varying function or vector representing external recruitment. When the realized per-capita growth rate of the local demography is negative, we show that all initial conditions converge to the same time-varying trajectory. Furthermore, when A1, A2... and b1, b2, ... are stationary sequences, this limiting behavior is determined by a unique stationary distribution. When the stationary sequences are periodic, uncorrelated, or a mixture of these two types of stationarity, we derive explicit formulas for the mean, within-year covariance, and auto-covariance of the stationary distribution. Sensitivity formulas for these statistical features are also given. The analtyic methods are illustrated with applications to discrete size-structured models of space-limited coral populations, and continuously size-structured models of giant clam populations.

ecology↗

bioRxiv2017

When rarity has costs: coexistence under positive frequency-dependence and environmental stochasticity

Stable coexistence relies on negative frequency-dependence, in which rarer species invading a patch benefit from a lack of conspecific competition experienced by residents. In nature, however, rarity can have costs, resulting in positive frequency-dependence (PFD) particularly when species are rare. Many processes can cause positive frequency-dependence, including a lack of mates, mutualist interactions, and reproductive interference from heterospecifics. When species become rare in the community, positive frequency-dependence creates vulnerability to extinction, if frequencies drop below certain thresholds. For example, environmental fluctuations can drive species to low frequencies where they are then vulnerable to PFD. Here, we analyze deterministic and stochastic mathematical models of two species interacting through both PFD and resource competition in a Chessonian framework. Reproductive success of individuals in these models is reduced by a product of two terms: the reduction in fecundity due to PFD, and the reduction in fecundity due to competition. Consistent with classical coexistence theory, the effect of competition on individual reproductive success exhibits negative frequency-dependence when individuals experience greater intraspecific competition than interspecific competition i.e., niche overlap is less than one. In the absence of environmental fluctuations, our analysis reveals that (1) a synergistic effect of PFD and niche overlap that hastens exclusion, (2) trade-offs between susceptibility to PFD and maximal fecundity can mediate coexistence, and (3) coexistence, when it occurs, requires that neither species is initially rare. Analysis of the stochastic model highlights that environmental fluctuations, unless perfectly correlated, coupled with PFD ultimately drive one species extinct. Over any given time frame, this extinction risk decreases with the correlation of the demographic responses of the two species to the environmental fluctuations, and increases with the temporal autocorrelation of these fluctuations. For species with overlapping generations, these trends in extinction risk persist despite the strength of the storage effect decreasing with correlated demographic responses and increasing with temporal autocorrelations. These results highlight how the presence of PFD may alter the outcomes predicted by modern coexistence mechanisms.

ecology↗