Environmental DNA (eDNA) metabarcoding is a promising method to monitor species and community diversity that is rapid, affordable and non‐invasive. The longstanding needs of the eDNA community are modular informatics tools, comprehensive and customizable reference databases, flexibility across high‐throughput sequencing platforms, fast multilocus metabarcode processing and accurate taxonomic assignment. Improvements in bioinformatics tools make addressing each of these demands within a single toolkit a reality. The new modular metabarcode sequence toolkit Anacapa ( https://github.com/limey-bean/Anacapa/) addresses the above needs, allowing users to build comprehensive reference databases and assign taxonomy to raw multilocus metabarcode sequence data. A novel aspect of Anacapa is its database building module, “Creating Reference libraries Using eXisting tools” (CRUX), which generates comprehensive reference databases for specific user‐defined metabarcoding loci. The Quality Control and ASV Parsing module sorts and processes multiple metabarcoding loci and processes merged, unmerged and unpaired reads maximizing recovered diversity. DADA2 then detects amplicon sequence variants (ASVs) and the Anacapa Classifier module aligns these ASVs to CRUX‐generated reference databases using Bowtie2. Lastly, taxonomy is assigned to ASVs with confidence scores using a Bayesian Lowest Common Ancestor (BLCA) method. The Anacapa Toolkit also includes an r package, ranacapa, for automated results exploration through standard biodiversity statistical analysis. Benchmarking tests verify that the Anacapa Toolkit effectively and efficiently generates comprehensive reference databases that capture taxonomic diversity, and can assign taxonomy to both MiSeq and HiSeq‐length sequence data. We demonstrate the value of the Anacapa Toolkit in assigning taxonomy to seawater eDNA samples collected in southern California. The Anacapa Toolkit improves the functionality of eDNA and streamlines biodiversity assessment and management by generating metabarcode specific databases, processing multilocus data, retaining a larger proportion of sequencing reads and expanding non‐traditional eDNA targets. All the components of the Anacapa Toolkit are open and available in a virtual container to ease installation.

A new cluster algorithm based on invasion percolation is described. The algorithm samples the critical point of a spin system without a priori knowledge of the critical temperature and provides an efficient way to determine the critical temperature and other observables in the critical region. The method is illustrated for the two-and three-dimensional Ising models. The algorithm equilibrates spin configurations much faster than the closely related Swendsen-Wang algorithm. PACS numbers: 75.40.Mg, 75. 10.Hk Enormous improvements in simulating systems near critical points have been achieved by using cluster algorithms [1,2]. In the present paper we describe a new cluster method which has the additional property of "selforganized criticality. " In particular, the method can be used to sample the critical region of various spin models without the need to fine tune any parameters (or know them in advance). Here, as in other cluster algorithms, bond clusters play a pivotal role in a Markov process, where successive spin configurations are generated using the Fortuin-Kasteleyn [3] representation to identify clusters of spins for flipping. However, the clusters themselves are identified using invasion percolation. The new algorithm is closely related to the Swendsen-Wang (SW) algorithm [1] and may be adapted for a wide range of systems. For purposes of illustration, in this work we will consider the Ising model. Let us first recall the SW algorithm as applied to an Ising system (in the Potts representation).Starting from a spin configuration, satisfied bonds those connecting spins that are of the same type are occupied with probability, p(p) = 1 -e~where p = J/kttT is the coupling strength. Unsatisfied bonds are never occupied.Clusters of sites connected by occupied bonds are locked into the same spin type, and all clusters (including isolated sites) are independently flipped with probability 1/2. The SW algorithm samples the canonical ensemble of the spin system at coupling P and/or the random cluster (bond configuration) ensemble with parameter p. At T, the. SW algorithm is far more efficient than single spin-Rip methods, because the flipped clusters are also critical droplets [4].Here we propose using invasion percolation [5 -10] to generate the bond clusters for the spin Hips. In the usual invasion percolation, random numbers are independently assigned to the bonds of the lattice. Growth starts from one or more seed sites, and at each step the clusters grow by the addition of the perimeter bond with the smallest random number.If a single cluster grows indefinitely on an infinite lattice, its large scale behavior is presumed to be that of the "incipient infinite cluster" of ordinary percolation. In particular, the fraction of perimeter bonds accepted into the growing cluster approaches the percolation threshold p, . [9,10]. Invasion percolation is thus a self-organized critical phenomenon.For the present, we modify invasion percolation in two ways. First, we initiate cluster growth at all lattice site». Consider this ...

are co-equal second authors.Robert Wayne and Rachel S. Meyer are co-equal senior authors. Abstract 1. Environmental DNA (eDNA) metabarcoding is a promising method to monitor species and community diversity that is rapid, affordable and non-invasive. The longstanding needs of the eDNA community are modular informatics tools, comprehensive and customizable reference databases, flexibility across high-throughput sequencing platforms, fast multilocus metabarcode processing and accurate taxonomic assignment. Improvements in bioinformatics tools make addressing each of these demands within a single toolkit a reality.2. The new modular metabarcode sequence toolkit Anacapa (https ://github.com/ limey-bean/Anaca pa/) addresses the above needs, allowing users to build comprehensive reference databases and assign taxonomy to raw multilocus metabarcode sequence data. A novel aspect of Anacapa is its database building module, "Creating Reference libraries Using eXisting tools" (CRUX), which generates comprehensive reference databases for specific user-defined metabarcoding loci. The Quality Control and ASV Parsing module sorts and processes multiple metabarcoding loci and processes merged, unmerged and unpaired reads maximizing recovered diversity. DADA2 then detects amplicon sequence variants (ASVs) and the Anacapa Classifier module aligns these ASVs to CRUX-generated reference databases using Bowtie2. Lastly, taxonomy is assigned to ASVs with confidence scores using a Bayesian Lowest Common Ancestor (BLCA) method. The Anacapa Toolkit also includes an r package, ranacapa, for automated results exploration through standard biodiversity statistical analysis.3. Benchmarking tests verify that the Anacapa Toolkit effectively and efficiently generates comprehensive reference databases that capture taxonomic diversity, and can assign taxonomy to both MiSeq and HiSeq-length sequence data. We demonstrate the value of the Anacapa Toolkit in assigning taxonomy to seawater eDNA samples collected in southern California.

Knowledge of mutation rates is crucial for calibrating population genetics models of demographic history in units of years. However, mutation rates remain challenging to estimate because of the need to identify extremely rare events. We estimated the nuclear mutation rate in wolves by identifying de novo mutations in a pedigree of seven wolves. Putative de novo mutations were discovered by whole-genome sequencing and were verified by Sanger sequencing of parents and offspring. Using stringent filters and an estimate of the false negative rate in the remaining observable genome, we obtain an estimate of ∼4.5 × 10−9 per base pair per generation and provide conservative bounds between 2.6 × 10−9 and 7.1 × 10−9. Although our estimate is consistent with recent mutation rate estimates from ancient DNA (4.0 × 10−9 and 3.0–4.5 × 10−9), it suggests a wider possible range. We also examined the consequences of our rate and the accompanying interval for dating several critical events in canid demographic history. For example, applying our full range of rates to coalescent models of dog and wolf demographic history implies a wide set of possible divergence times between the ancestral populations of dogs and extant Eurasian wolves (16,000–64,000 years ago) although our point estimate indicates a date between 25,000 and 33,000 years ago. Aside from one study in mice, ours provides the only direct mammalian mutation rate outside of primates and is likely to be vital to future investigations of mutation rate evolution.