scholarly journals Composite likelihood method for inferring local pedigrees

PLoS Genetics ◽  
2017 ◽  
Vol 13 (8) ◽  
pp. e1006963 ◽  
Author(s):  
Amy Ko ◽  
Rasmus Nielsen
Keyword(s):  
Composite Likelihood ◽  
Likelihood Method

scholarly journals A spatially aware likelihood test to detect sweeps from haplotype distributions

2021 ◽  
Author(s):  
Michael DeGiorgio ◽  
Zachary A Szpiech
Keyword(s):  
Positive Selection ◽  
Frequency Spectrum ◽  
Haplotype Frequency ◽  
Positive Control ◽  
Composite Likelihood ◽  
Likelihood Method ◽  
Human Populations ◽  
Adaptive Mutations ◽  
Two Parameters ◽  
User Friendly

The inference of positive selection in genomes is a problem of great interest in evolutionary genomics. By identifying putative regions of the genome that contain adaptive mutations, we are able to learn about the biology of organisms and their evolutionary history. Here we introduce a composite likelihood method that identifies recently completed or ongoing positive selection by searching for extreme distortions in the spatial distribution of the haplotype frequency spectrum relative to the genome-wide expectation taken as neutrality. Furthermore, the method simultaneously infers two parameters of the sweep: the number of sweeping haplotypes and the ``width'' of the sweep, which is related to the strength and timing of selection. We demonstrate that this method outperforms the leading haplotype-based selection statistics. Then, as a positive control, we apply it to two well-studied human populations from the 1000 Genomes Project and examine haplotype frequency spectrum patterns at the LCT and MHC loci. To facilitate use of this method, we have implemented it in user-friendly open source software.

scholarly journals Tenebrio molitor: possible source of polystyrene-degrading bacteria

2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Oleen Machona ◽  
Farisai Chidzwondo ◽  
Rumbidzai Mangoyi
Keyword(s):  
Klebsiella Oxytoca ◽  
Tenebrio Molitor ◽  
Normal Diet ◽  
Composite Likelihood ◽  
Likelihood Method ◽  
Isolation And Identification ◽  
Degrading Bacteria ◽  
Pcr Products ◽  
Identification Of Bacteria ◽  
Polystyrene Waste

Abstract Background The excessive use of polystyrene as a packaging material has resulted in a rise in environmental pollution. Polystyrene waste has continually increased water pollution, soil pollution and the closing of landfill sites since it is durable and resistant to biodegradation. Therefore, the challenge in polystyrene disposal has caused researchers to look for urgent innovative and eco-friendly solutions for plastic degradation. The current study focuses on the isolation and identification of bacteria produced by the larvae of beetle Tenebrio molitor (yellow mealworms), that enable them to survive when fed with polystyrene foam as their sole carbon diet. Materials and methods The biodegradation of polystyrene by Tenebrio molitor was investigated by breeding and rearing the mealworms in the presence and absence of polystyrene. A comparison was made between those fed with a normal diet and those fed on polystyrene. The mealworms which were fed with polystyrene were then dissected and the guts were collected to isolate and identify the bacteria in their guts. The viability and metabolic activity of the isolates were investigated. The polymerase chain reaction (PCR) followed by sequencing was used for molecular identification of the isolates. The PCR products were directly sequenced using Sanger’s method and the phylogenetic tree and molecular evolutionary analyses were constructed using MEGAX software with the Neighbour Joining algorithm. The evolutionary distances were computed using the Maximum Composite Likelihood method. Results The decrease in mass of the polystyrene as feedstock confirmed that the mealworms were depending on polystyrene as their sole carbon diet. The frass egested by mealworms also confirmed the biodegradation of polystyrene as it contained very tiny residues of polystyrene. Three isolates were obtained from the mealworms guts, and all were found to be gram-negative. The sequencing results showed that the isolates were Klebsiella oxytoca ATCC 13182, Klebsiella oxytoca NBRC 102593 and Klebsiella oxytoca JCM 1665. Conclusion Klebsiella oxytoca ATCC 13182, Klebsiella oxytoca NBRC 102593 and Klebsiella oxytoca JCM 1665 maybe some of the bacteria responsible for polystyrene biodegradation.

scholarly journals Multiple Comparisons Using Composite Likelihood in Clustered Data

2016 ◽  
Vol 12 (2) ◽  
Author(s):  
Mahdis Azadbakhsh ◽  
Xin Gao ◽  
Hanna Jankowski
Keyword(s):  
Type I Error ◽  
Clustered Data ◽  
Likelihood Estimation ◽  
Good Control ◽  
Multiple Hypothesis Testing ◽  
Composite Likelihood ◽  
Multiple Comparison ◽  
Likelihood Method ◽  
Type I ◽  
Multiple Comparison Procedures

AbstractWe study the problem of multiple hypothesis testing for correlated clustered data. As the existing multiple comparison procedures based on maximum likelihood estimation could be computationally intensive, we propose to construct multiple comparison procedures based on composite likelihood method. The new test statistics account for the correlation structure within the clusters and are computationally convenient to compute. Simulation studies show that the composite likelihood based procedures maintain good control of the familywise type I error rate in the presence of intra-cluster correlation, whereas ignoring the correlation leads to erratic performance.

scholarly journals Tenebrio Molitor: Possible Source of Polystyrene-Degrading Bacteria

2021 ◽  
Author(s):  
Oleen Machona ◽  
Farisai Chidzwondo ◽  
Rumbidzai Mangoyi
Keyword(s):  
Klebsiella Oxytoca ◽  
Tenebrio Molitor ◽  
Normal Diet ◽  
Composite Likelihood ◽  
Likelihood Method ◽  
Isolation And Identification ◽  
Degrading Bacteria ◽  
Pcr Products ◽  
Identification Of Bacteria ◽  
Polystyrene Waste

Abstract Background: The excessive use of polystyrene as a packaging material has resulted in a rise in environmental pollution. Polystyrene waste has continually increased water pollution, soil pollution and the closing of landfill sites since it is durable and resistant to biodegradation. Therefore, the challenge in polystyrene disposal has caused researchers to look for urgent innovative and eco-friendly solutions for plastic degradation. The current study focuses on the isolation and identification of bacteria produced by the larvae of beetle Tenebrio molitor (yellow mealworms), that enable them to survive when fed with polystyrene foam as their sole carbon diet. Materials and methods: The biodegradation of polystyrene by Tenebrio molitor was investigated by breeding and rearing the mealworms in the presence and absence of polystyrene. A comparison was made between those fed with a normal diet and those fed on polystyrene. The mealworms which were fed with polystyrene were then dissected and the guts were collected to isolate and identify the bacteria in their guts. The viability and metabolic activity of the isolates were investigated. The polymerase chain reaction (PCR) followed by sequencing was used for molecular identification of the isolates. The PCR products were directly sequenced using the Sanger’s method and the phylogenetic tree and molecular evolutionary analyses were constructed using MEGAX software with the Neighbour Joining algorithm. The evolutionary distances were computed using the Maximum Composite Likelihood method. Results: The decrease in mass of the polystyrene as feedstock confirmed that the mealworms were depending on polystyrene as their sole carbon diet. The frass egested by mealworms also confirmed the biodegradation of polystyrene as it contained very tiny residues of polystyrene. Three isolates were obtained from the mealworms guts, and all were found to be gram-negative. The sequencing results showed that the isolates were Klebsiella oxytoca ATCC 13182, Klebsiella oxytoca NBRC 102593 and Klebsiella oxytoca JCM 1665.Conclusion: Klebsiella oxytoca ATCC 13182, Klebsiella oxytoca NBRC 102593 and Klebsiella oxytoca JCM 1665 maybe some of the bacteria responsible for polystyrene biodegradation.

scholarly journals COAL_PHYRE: A Composite Likelihood Method for Estimating Species Tree Parameters from Genomic Data Using Coalescent Theory

2020 ◽  
Author(s):  
Geno Guerra ◽  
Rasmus Nielsen
Keyword(s):  
Population Size ◽  
Gene Tree ◽  
Divergence Time ◽  
Species Tree ◽  
Composite Likelihood ◽  
Likelihood Method ◽  
Computational Time ◽  
Species Trees ◽  
Divergence Time Estimates ◽  
Full Likelihood

2AbstractGenome-scale data are increasingly being used to infer phylogenetic trees. A major challenge in such inferences is that different regions of the genome may have local topologies that differ from the species tree due to incomplete lineage sorting (ILS). Another source of gene tree discrepancies is estimation errors arising from the randomness of the mutational process during sequence evolution. There are two major groups of methods for estimating species tree from whole-genome data: a set of full likelihood methods, which model both sources of variance, but do not scale to large numbers of independent loci, and a class of faster approximation methods which do not model the mutational variance.To bridge the gap between these two classes of methods, we present COAL_PHYRE (COmposite Approximate Likelihood for PHYlogenetic REconstruction), a composite likelihood based method for inferring population size and divergence time estimates of rooted species trees from aligned gene sequences. COAL_PHYRE jointly models coalescent variation across loci using the MSC and variation in local gene tree reconstruction using a normal approximation. To evaluate the accuracy and speed of the method, we compare against BPP, a powerful MCMC full-likelihood method, as well as ASTRAL-III, a fast approximate method. We show that COAL_PHYRE’s divergence time and population size estimates are more accurate than ASTRAL, and comparable to those obtained using BPP, with an order of magnitude decrease in computational time. We also present results on previously published data from a set of Gibbon species to evaluate the accuracy in topology and parameter inference on real data, and to illustrate the method’s ability to analyze data sets which are prohibitively large for MCMC methods.

scholarly journals Molecular Characterization, Phylogenetic and Variation Analyzes of SARS-CoV-2 strains in Turkey

2020 ◽  
Author(s):  
Karamese Murat ◽  
Ozgur Didem ◽  
Tutuncu Emin Ediz
Keyword(s):  
Illumina Miseq ◽  
Composite Likelihood ◽  
Likelihood Method ◽  
Neighbor Joining ◽  
Genome Sequences ◽  
Illumina Miseq Platform ◽  
Complete Genomes ◽  
Genome Analysis Toolkit ◽  
Miseq Platform ◽  
Turkish Patients

ABSTRACTIntroductionWe present the sequence analysis for 47 complete genomes for SARS-CoV-2 isolates on Turkish patients. To identify their genetic similarity, phylogenetic analysis was performed by comparing the worldwide SARS-CoV-2 sequences, selected from GISAID, to the complete genomes from Turkish isolates. In addition, we focused on the variation analysis to show the mutations on SARS-CoV-2 genomes.MethodsIllumina MiSeq platform was used for sequencing the libraries. The raw reads were aligned to the known SARS-CoV-2 genome (GenBank: MN908947.3) using the Burrows-Wheeler aligner (v.0.7.1). The phylogenetic tree was constructer using Phylip v.3.6 with Neighbor-Joining and composite likelihood method. The variants were detected by using Genome Analysis Toolkit-HaplotypeCaller v.3.8.0 and were inspected on GenomeBrowse v2.1.2.ResultsAll viral genome sequences of our isolates was located in lineage B under the different clusters such as B.1 (n=3), B.1.1 (n=28), and B.1.9 (n=16). According to the GISAID nomenclature, all our complete genomes were placed in G, GR and GH clades. Five hundred forty-nine total and 53 unique variants were detected. All 47 genomes exhibited different kinds of variants. The distinct variants consist of 274 missense, 225 synonymous, and 50 non-coding alleles.ConclusionThe results indicated that the SARS-CoV-2 sequences of our isolates have great similarity with all Turkish and European sequences. Further studies should be performed for better comparison of strains, after more complete genome sequences will be released. We also believe that collecting and sharing any data about SARS-CoV-2 virus and COVID-19 will be effective and may help the related studies.

scholarly journals Closed-Form Two-Locus Sampling Distributions: Accuracy and Universality

Genetics ◽  
2009 ◽  
Vol 183 (3) ◽  
pp. 1087-1103 ◽  
Author(s):  
Paul A. Jenkins ◽  
Yun S. Song
Keyword(s):  
Closed Form ◽  
Recombination Rate ◽  
Extensive Study ◽  
Composite Likelihood ◽  
Likelihood Method ◽  
Sampling Formula ◽  
Sampling Distributions ◽  
Mutation Model ◽  
Asymptotic Sampling

Sampling distributions play an important role in population genetics analyses, but closed-form sampling formulas are generally intractable to obtain. In the presence of recombination, there is no known closed-form sampling formula that holds for an arbitrary recombination rate. However, we recently showed that it is possible to obtain useful closed-form sampling formulas when the population-scaled recombination rate ρ is large. Specifically, in the case of the two-locus infinite-alleles model, we considered an asymptotic expansion of the sampling formula in inverse powers of ρ and obtained closed-form expressions for the first few terms in the expansion. In this article, we generalize this result to an arbitrary finite-alleles mutation model and show that, up to the first few terms in the expansion that we are able to compute analytically, the functional form of the asymptotic sampling formula is common to all mutation models. We carry out an extensive study of the accuracy of the asymptotic formula for the two-locus parent-independent mutation model and discuss in detail a concrete application in the context of the composite-likelihood method. Furthermore, using our asymptotic sampling formula, we establish a simple sufficient condition for a given two-locus sample configuration to have a finite maximum-likelihood estimate (MLE) of ρ. This condition is the first analytic result on the classification of the MLE of ρ and is instantaneous to check in practice, provided that one-locus probabilities are known.

scholarly journals A Composite Likelihood Method for the Analysis of Multivariate Survival Data: An Application to a PBDE Study

2019 ◽  
Vol 8 (2) ◽  
pp. 23
Author(s):  
Wenqing He ◽  
Wantao Wang ◽  
Lihua Yue ◽  
Xinhua Liu
Keyword(s):  
Survival Data ◽  
Polybrominated Diphenyl Ethers ◽  
Strong Association ◽  
Composite Likelihood ◽  
Likelihood Method ◽  
Survival Times ◽  
Inference Procedure ◽  
Multivariate Survival ◽  
Multivariate Survival Data ◽  
Lower Dimensional

When dealing with multivariate survival data, featuring the association structure is a key difference from the univariate survival analysis. In this paper, we explore to use the composite likelihood framework to handle multivariate survival data, where only the lower dimensional survival distributions need to be specified. The development allows us to use available modeling schemes for bivariate survival data to characterize association structures of correlated survival times. The inference procedure is based on the pseudolikelihood which is the product of the lower dimensional bivariate distributions. The proposed estimation procedure is assessed through simulation studies. As a genuine application, we apply the composite likelihood inference procedure to analyze the data from the polybrominated diphenyl ethers (PBDEs) study, where four types of PBDE congeners are available. The associations among the four PBDE congeners, and the relationships between the covariates and the PBDE congeners are of interest. The result shows that there is strong association among the concentrations of the four PBDE congeners, and statistically significant predictors on the concentrations of the four PBDE congeners are identified.

scholarly journals Bioinformatic analysis of chickpea acetohydroxyacid synthase gene

2019 ◽  
Vol 24 ◽  
pp. 345-349
Author(s):  
H. I. Slishchuk ◽  
N. E. Volkova ◽  
O. O. Zakharova ◽  
A. V. Korchmaryоvа
Keyword(s):  
Single Nucleotide Polymorphism ◽  
Composite Likelihood ◽  
Taqman Probe ◽  
Likelihood Method ◽  
Dimensional Structure ◽  
Acetohydroxyacid Synthase ◽  
Nucleotide Polymorphism ◽  
Aim Analysis ◽  
Single Nucleotide ◽  
Homologous Modeling

Aim. Analysis of homologues of chickpea gene encoding acetohydroxyacid synthase, by bioinformatics methods. Methods. Alignment of nucleotide sequences, UPGMA method, Maximum Composite Likelihood method, homologous modeling of three-dimensional structure of enzyme. Results. Homologues of the acetohydroxyacid syntase gene (AHAS) of  chickpea were found among representatives of different families. A certain level of conservativeness of mRNA homologues sequences of AHAS gene within the families was noted, including legumes. The distribution of clusters corresponds to the taxonomic position of the investigated plant species. The single nucleotide polymorphism C / T at position 581, potentially associated with herbicide resistance, was detected. Based on the homologous modeling results, two models of the enzyme AHAS were constructed. The replacement of C / T, which leads to the replacement of the amino acids of alanine with valine, leads to a change in the conformation in the A chain of protein. Conclusions. Marker screening of the source breeding material by «real-time» polymerase chain reaction with the developed primers and the TaqMan probe to the polymorphic region of the AHAS gene will allow differentiating the herbicide «resistant» and «tolerant» alleles of the gene for the selection of target genotypes. Keywords: chickpea, acetohydroxyacid syntase gene, single nucleotide polymorphism, resistance to herbicides.

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