Latest Articles

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  Section: Mathematical & Computational Biology ; Topics: Biophysics and computational biology, Computer sciences

  Accelerating k-mer-based sequence filtering

  Martayan, Igor;   Vandamme, Léa;   Constantinides, Bede;   Cazaux, Bastien;   Paperman, Charles;   Limasset, Antoine  

  10.24072/pcjournal.735 - Peer Community Journal, Volume 6 (2026), article no. e55

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  Motivation. The exponential growth of global sequencing data repositories presents both analytical challenges and opportunities. While k-mer-based indexing has improved scalability over traditional alignment for identifying relevant documents, pinpointing the exact sequences matching numerous queries remains a hurdle. In particular, searching for numerous k-mers with a single large query or multiple distinct queries strains existing exact matching tools, whose performance scales poorly with an increasing number of patterns. At the same time, indexing entire vast datasets for infrequent or ad-hoc searches is often resource-prohibitive. Designing fast methods for matching a large number of k-mers without exhaustive pre-indexing is therefore critical.  Contributions. We propose an efficient solution to the problem of k-mer-based sequence filtering: given a set of k-mers of interests and a threshold, quickly evaluate whether an arbitrary sequence has a number of k-mer matches above or below the threshold. Our approach demonstrates how minimizer-based based sketching, alongside SIMD acceleration, can enhance the performance of streaming searches, and is implemented as a Rust tool named K2Rmini. On a consumer laptop, K2Rmini is able to filter long reads at 2 Gbp/s.  Availability. https://github.com/Malfoy/K2Rmini.

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  Section: Ecology ; Topics: Ecology, Statistics

  Uncovering the relative movements of ecological trajectories

  Djeghri, Nicolas;   Gauthier, Olivier; Sturbois, Anthony;   Meiners, Scott J.;   Allen, Robert B.;   De Cáceres, Miquel  

  10.24072/pcjournal.736 - Peer Community Journal, Volume 6 (2026), article no. e54

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  Movement analogies are often employed by ecologists to describe how ecological dynamics relate to one another. For instance, two communities whose similarity increases in time may be said to converge. Here we argue that the movement analogies used by ecologists to compare ecological dynamics could be enriched with other notions such as “pursuit” or “parallel” movements, if accompanied by appropriate statistical testing. By building on the framework of Ecological Trajectory Analysis, we present here Relative Trajectory Movement Assessment (RTMA), a framework to detect and qualify relative movements in ecological dynamics defined as trajectories in multivariate space. Using synthetic trajectory data, we illustrate how RTMA can reveal a diverse range of relative movements beyond the convergence and divergence patterns already recognized in ecology. We exemplify the use of RTMA on real ecological datasets describing 1) old field successional dynamics in eastern North America and 2) temporal patterns in tree size structure of a New Zealand forest. RTMA provides ecologists with a new way of describing and comparing ecological dynamics that could be widely applied, from plot-scale dynamics to the effects of global change.

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  Section: Ecology ; Topics: Ecology, Population biology, Statistics

  Disentangling different sources of variation in functional responses: between-individual variability, measurement error and inherent stochasticity of the prey-predator interaction process

  Baey, Charlotte;   Billiard, Sylvain;   Delattre, Maud  

  10.24072/pcjournal.729 - Peer Community Journal, Volume 6 (2026), article no. e53

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  The consumption rate of prey by predators, or functional responses, are known to be highly variable even within a single population. Identifying and estimating the different sources of variation of functional responses is a long-standing challenge. We develop here a statistical framework derived from a mechanistic stochastic process model that explicitly accounts for different sources of variation. We apply it to disentangle and estimate in particular 1) residual variance due to measurement errors and model misspecification, 2) between-predator variability, and 3) the interaction stochasticity,  i.e. the intrinsic and mechanistic variability due to interactions processes between prey and predators. We show that it is possible to estimate these sources of variation under realistic experimental conditions. Our results also show that model fitting can compensate by overestimating residual source of variation, leading to biased parameter estimates when interaction stochasticity is misspecified. Applied to empirical data, the model reveals that standard assumptions, such as prey renewal and lack of spatial structure, fail to capture observed variability. We also show how experimental design affects parameter identifiability, highlighting the trade-off between the number of individuals and repeated observations.

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  Section: Ecology ; Topics: Ecology, Statistics

  Space-time species distribution modeling with opportunistic presence-only data: a case study of passerines in a protected area

  Lasgorceux, Florian;   Papaïx, Julien;   Bunz, Yoann;   Combrisson, Damien;   Opitz, Thomas  

  10.24072/pcjournal.731 - Peer Community Journal, Volume 6 (2026), article no. e52

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  Over the recent decades, Europe has experienced a significant decline in common bird species, particularly farmland species, due to anthropic pressures like agricultural intensification. Protected areas, such as the Écrins National Park (ENP) in France, can help mitigate these impacts. We evaluated whether an opportunistic presence-only dataset collected by trained ENP rangers contains biological signals strong enough to support robust statistical inference. Using a generalized additive Poisson model with spatial and spatio-temporal covariates, monthly latent spatio-temporal Gaussian random fields, and a non-spatial inter-annual effect, we estimated the relative abundance of 76 passerine species on a regular grid, with occurrences aggregated per spatio-temporal cell used as a proxy for sampling effort. The model showed good calibration for most species ($\text{AUC} > 0.8$) and reliably captured habitat preferences and migratory status. Relative-abundance trends in ENP were compared with relative abundance from three monitoring programs: STOM (ENP), STOC (France), and MHB (Switzerland). For most species with significant trends, model predictions aligned with survey-based trends. Forest specialists benefited most from the protected-area status, and farmland species declined more slowly in ENP than in France. High-elevation specialists generally decreased in both ENP and Switzerland. Discrepancies mostly arose for common species, likely reflecting uncorrected declines in ranger reporting rates. These results demonstrate that high-resolution opportunistic presence-only data can provide valuable insights into biological patterns and trends while reducing reliance on external data to estimate sampling effort.