Decision Theory-Based COI-SNP Tagging Approach for 126 Scombriformes Species Tagging.
Ontology highlight
ABSTRACT:
SUBMITTER: Yang CH
PROVIDER: S-EPMC6456664 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:BackgroundRapid and reliable identification of quarantine pests is essential for plant inspection services to prevent introduction of invasive species. For insects, this may be a serious problem when dealing with morphologically similar cryptic species complexes and early developmental stages that lack distinctive characters useful for taxonomic identification. DNA based barcoding could solve many of these problems. The standard barcode fragment, an approx. 650 base pairs long sequence of the 5'end of the mitochondrial cytochrome oxidase I (COI), enables differentiation of a very wide range of arthropods. However, problems remain in some taxa, such as Tephritidae, where recent genetic differentiation among some of the described species hinders accurate molecular discrimination.ResultsIn order to explore the full species discrimination potential of COI, we sequenced the barcoding region of the COI gene of a range of economically important Tephritid species and complemented these data with all GenBank and BOLD entries for the systematic group available as of January 2012. We explored the limits of species delimitation of this barcode fragment among 193 putative Tephritid species and established operational taxonomic units (OTUs), between which discrimination is reliably possible. Furthermore, to enable future development of rapid diagnostic assays based on this sequence information, we characterized all single nucleotide polymorphisms (SNPs) and established "near-minimal" sets of SNPs that differentiate among all included OTUs with at least three and four SNPs, respectively.ConclusionsWe found that although several species cannot be differentiated based on the genetic diversity observed in COI and hence form composite OTUs, 85% of all OTUs correspond to described species. Because our SNP panels are developed based on all currently available sequence information and rely on a minimal pairwise difference of three SNPs, they are highly reliable and hence represent an important resource for developing taxon-specific diagnostic assays. For selected cases, possible explanations that may cause composite OTUs are discussed.
| S-EPMC3682933 | biostudies-literature
Project description: Not available
| S-DIXA-D-1146 | biostudies-other
Project description:BackgroundNon-inferiority trials are performed when the main therapeutic effect of the new therapy is expected to be not unacceptably worse than that of the standard therapy, and the new therapy is expected to have advantages over the standard therapy in costs or other (health) consequences. These advantages however are not included in the classic frequentist approach of sample size calculation for non-inferiority trials. In contrast, the decision theory approach of sample size calculation does include these factors. The objective of this study is to compare the conceptual and practical aspects of the frequentist approach and decision theory approach of sample size calculation for non-inferiority trials, thereby demonstrating that the decision theory approach is more appropriate for sample size calculation of non-inferiority trials.MethodsThe frequentist approach and decision theory approach of sample size calculation for non-inferiority trials are compared and applied to a case of a non-inferiority trial on individually tailored duration of elastic compression stocking therapy compared to two years elastic compression stocking therapy for the prevention of post thrombotic syndrome after deep vein thrombosis.ResultsThe two approaches differ substantially in conceptual background, analytical approach, and input requirements. The sample size calculated according to the frequentist approach yielded 788 patients, using a power of 80% and a one-sided significance level of 5%. The decision theory approach indicated that the optimal sample size was 500 patients, with a net value of €92 million.ConclusionsThis study demonstrates and explains the differences between the classic frequentist approach and the decision theory approach of sample size calculation for non-inferiority trials. We argue that the decision theory approach of sample size estimation is most suitable for sample size calculation of non-inferiority trials.
| S-EPMC4468148 | biostudies-literature
Project description:Exhaust gas recirculation (EGR) is one of the main methods of reducing NOX emissions and has been widely used in marine diesel engines. This paper proposes an optimized comprehensive assessment method based on multi-objective grey situation decision theory, grey relation theory and grey entropy analysis to evaluate the performance and optimize rate determination of EGR, which currently lack clear theoretical guidance. First, multi-objective grey situation decision theory is used to establish the initial decision-making model according to the main EGR parameters. The optimal compromise between diesel engine combustion and emission performance is transformed into a decision-making target weight problem. After establishing the initial model and considering the characteristics of EGR under different conditions, an optimized target weight algorithm based on grey relation theory and grey entropy analysis is applied to generate the comprehensive evaluation and decision-making model. Finally, the proposed method is successfully applied to a TBD234V12 turbocharged diesel engine, and the results clearly illustrate the feasibility of the proposed method for providing theoretical support and a reference for further EGR optimization.
| S-EPMC5788385 | biostudies-literature
Project description:A key problem in high-dimensional significance analysis is to find pre-defined sets that show enrichment for a statistical signal of interest; the classic example is the enrichment of gene sets for differentially expressed genes. Here, we propose a new decision-theory approach to the analysis of gene sets which focuses on estimating the fraction of non-null variables in a set. We introduce the idea of "atoms," non-overlapping sets based on the original pre-defined set annotations. Our approach focuses on finding the union of atoms that minimizes a weighted average of the number of false discoveries and missed discoveries. We introduce a new false discovery rate for sets, called the atomic false discovery rate (afdr), and prove that the optimal estimator in our decision-theory framework is to threshold the afdr. These results provide a coherent and interpretable framework for the analysis of sets that addresses the key issues of overlapping annotations and difficulty in interpreting p values in both competitive and self-contained tests. We illustrate our method and compare it to a popular existing method using simulated examples, as well as gene-set and brain ROI data analyses.
| S-EPMC3927844 | biostudies-literature
Project description:DNA barcode sequences are accumulating in large data sets. A barcode is generally a sequence larger than 1000 base pairs and generates a computational burden. Although the DNA barcode was originally envisioned as straightforward species tags, the identification usage of barcode sequences is rarely emphasized currently. Single-nucleotide polymorphism (SNP) association studies provide us an idea that the SNPs may be the ideal target of feature selection to discriminate between different species. We hypothesize that SNP-based barcodes may be more effective than the full length of DNA barcode sequences for species discrimination. To address this issue, we tested a ribulose diphosphate carboxylase (rbcL) SNP barcoding (RSB) strategy using a decision tree algorithm. After alignment and trimming, 31 SNPs were discovered in the rbcL sequences from 38 Brassicaceae plant species. In the decision tree construction, these SNPs were computed to set up the decision rule to assign the sequences into 2 groups level by level. After algorithm processing, 37 nodes and 31 loci were required for discriminating 38 species. Finally, the sequence tags consisting of 31 rbcL SNP barcodes were identified for discriminating 38 Brassicaceae species based on the decision tree-selected SNP pattern using RSB method. Taken together, this study provides the rational that the SNP aspect of DNA barcode for rbcL gene is a useful and effective sequence for tagging 38 Brassicaceae species.
| S-EPMC5846911 | biostudies-literature
Project description:This paper puts forward a grey situation group decision-making method on the basis of prospect theory, in view of the grey situation group decision-making problems that decisions are often made by multiple decision experts and those experts have risk preferences. The method takes the positive and negative ideal situation distance as reference points, defines positive and negative prospect value function, and introduces decision experts' risk preference into grey situation decision-making to make the final decision be more in line with decision experts' psychological behavior. Based on TOPSIS method, this paper determines the weight of each decision expert, sets up comprehensive prospect value matrix for decision experts' evaluation, and finally determines the optimal situation. At last, this paper verifies the effectiveness and feasibility of the method by means of a specific example.
| S-EPMC4146360 | biostudies-other
Project description:Cicadidae periostracum (CP), the medicinal name of cicada exuviae, is well-known insect-derived traditional medicine with various pharmacological effects, e.g., anticonvulsive, anti-inflammatory, antitussive, and anticancer effects; it is also beneficial for the treatment of Parkinson's disease. For appropriate CP application, accurate species identification is essential. The Korean pharmacopoeia and the pharmacopoeia of the People's Republic of China define Cryptotympana atrata as the only authentic source of CP. Species identification of commercially distributed CP based on morphological features, however, is difficult because of the combined packaging of many cicada exuviae in markets, damage during distribution, and processing into powder form. DNA-based molecular markers are an excellent alternative to morphological detection. In this study, the mitochondrial cytochrome c oxidase subunit I sequences of C. atrata, Meimuna opalifera, Platypleura kaempferi, and Hyalessa maculaticollis were analyzed. On the basis of sequence alignments, we developed sequence-characterized amplified-region (SCAR) markers for efficient species identification. These markers successfully discriminated C. atrata from the three other cicada species, and detected the adulteration of market CP samples. This SCAR assay is a rapid, simple, cheap, reliable, and reproducible method for species identification, regardless of sample form and status, and contributes to CP quality control.
| S-EPMC7143061 | biostudies-literature
Project description:Community similarity is often assessed through similarities in species occurrences and abundances (i.e., compositional similarity) or through the distribution of species interactions (i.e., interaction similarity). Unfortunately, the joint empirical evaluation of both is still a challenge. Here, we analyze community similarity in ecological systems in order to evaluate the extent to which indices based exclusively on species composition differ from those that incorporate species interactions. Borrowing tools from graph theory, we compared the classic Jaccard index with the graph edit distance (GED), a metric that allowed us to combine species composition and interactions. We found that similarity measures computed using only taxonomic composition could differ strongly from those that include composition and interactions. We conclude that new indices that incorporate community features beyond composition will be more robust for assessing similitude between natural systems than those purely based on species occurrences. Our results have therefore important conceptual and practical consequences for the analysis of ecological communities.
| S-EPMC6546078 | biostudies-literature
Project description:Taxonomic identification can be difficult when two or more species appear morphologically similar. DNA barcoding based on the sequence of the mitochondrial cytochrome c oxidase 1 gene (COI) is now widely used in identifying animal species. High-resolution melting analysis (HRM) provides an alternative method for detecting sequence variations among amplicons without having to perform DNA sequencing. The purpose of this study was to determine whether HRM of the COI barcode can be used to distinguish animal species. Using anurans as a model, we found distinct COI melting profiles among three congeners of both Lithobates spp. and Hyla spp. Sequence variations within species shifted the melting temperature of one or more melting domains slightly but do not affect the distinctness of the melting profiles for each species. An NMDS ordination plot comparing melting peak profiles among eight Anuran species showed overlapping profiles for Lithobates sphenocephala and Gastrophryne carolinensis. The COI amplicon for both species contained two melting domains with melting temperatures that were similar between the two species. The two species belong to two different families, highlighting the fact that COI melting profiles do not reveal phylogenetic relationships but simply reflect DNA sequence differences among stretches of DNA within amplicons. This study suggests that high-resolution melting analysis of COI barcodes (COI-HRM) may be useful as a simple and rapid method to distinguish animal species that appear morphologically similar.
| S-EPMC6912877 | biostudies-literature