Showing papers by "Fredrik Ronquist published in 2023"
TL;DR: In this article , a static analysis technique is presented to automatically determine checkpoints in probabilistic programs, relieving PPL users of the task of determining the location of checkpoints in programs.
Abstract: Probabilistic Programming Languages (PPLs) allow users to encode statistical inference problems and automatically apply an inference algorithm to solve them. Popular inference algorithms for PPLs, such as sequential Monte Carlo (SMC) and Markov chain Monte Carlo (MCMC), are built around checkpoints -- relevant events for the inference algorithm during the execution of a probabilistic program. Deciding the location of checkpoints is, in current PPLs, not done optimally. To solve this problem, we present a static analysis technique that automatically determines checkpoints in programs, relieving PPL users of this task. The analysis identifies a set of checkpoints that execute in the same order in every program run -- they are aligned. We formalize alignment, prove the correctness of the analysis, and implement the analysis as part of the higher-order functional PPL Miking CorePPL. By utilizing the alignment analysis, we design two novel inference algorithm variants: aligned SMC and aligned lightweight MCMC. We show, through real-world experiments, that they significantly improve inference execution time and accuracy compared to standard PPL versions of SMC and MCMC.
1 citations
TL;DR: The Amplicon Sequence Variant (ASV) portal as mentioned in this paper is a web interface to sequence-based biodiversity observations in the Living Atlas, which allows data providers to submit denoised metabarcoding output via an intermediary ASV database.
Abstract: Abstract Background The Living Atlas is an open source platform used to collect, visualise and analyse biodiversity data from multiple sources, and serves as the national biodiversity data hub in many countries. Although powerful, the Living Atlas has had limited functionality for species occurrence data derived from DNA sequences. As a step toward integrating this fast-growing data source into the platform, we developed the Amplicon Sequence Variant (ASV) portal: a web interface to sequence-based biodiversity observations in the Living Atlas. Results The ASV portal allows data providers to submit denoised metabarcoding output to the Living Atlas platform via an intermediary ASV database. It also enables users to search for existing ASVs and associated Living Atlas records using the Basic Local Alignment Search Tool, or via filters on taxonomy and sequencing details. The ASV portal is a Python-Flask/jQuery web interface, implemented as a multi-container docker service, and is an integral part of the Swedish Biodiversity Data Infrastructure. Conclusion The ASV portal is a web interface that effectively integrates biodiversity data derived from DNA sequences into the Living Atlas platform.
1 citations
TL;DR: In this article , a non-destructive metabarcoding protocol is proposed for high-throughput processing of Malaise trap samples and other bulk insect samples, which can yield a comprehensive assessment of the number of species present in a given sample, their relative read abundances and the overall insect biomass.
Abstract: Insects are diverse and sustain essential ecosystem functions, yet remain understudied. Recent reports about declines in insect abundance and diversity have highlighted a pressing need for comprehensive large-scale monitoring. Metabarcoding (high-throughput bulk sequencing of marker gene amplicons) offers a cost-effective and relatively fast method for characterizing insect community samples. However, the methodology applied varies greatly among studies, thus complicating the design of large-scale and repeatable monitoring schemes. Here we describe a non-destructive metabarcoding protocol that is optimized for high-throughput processing of Malaise trap samples and other bulk insect samples. The protocol details the process from obtaining bulk samples up to submitting libraries for sequencing. It is divided into four sections: 1) Laboratory workspace preparation; 2) Sample processing—decanting ethanol, measuring the wet-weight biomass and the concentration of the preservative ethanol, performing non-destructive lysis and preserving the insect material for future work; 3) DNA extraction and purification; and 4) Library preparation and sequencing. The protocol relies on readily available reagents and materials. For steps that require expensive infrastructure, such as the DNA purification robots, we suggest alternative low-cost solutions. The use of this protocol yields a comprehensive assessment of the number of species present in a given sample, their relative read abundances and the overall insect biomass. To date, we have successfully applied the protocol to more than 7000 Malaise trap samples obtained from Sweden and Madagascar. We demonstrate the data yield from the protocol using a small subset of these samples.