Algorithms for Molecular Biology最新文献

{"title":"Fast computation of genome-metagenome interaction effects.","authors":"Florent Guinot,&nbsp;Marie Szafranski,&nbsp;Julien Chiquet,&nbsp;Anouk Zancarini,&nbsp;Christine Le Signor,&nbsp;Christophe Mougel,&nbsp;Christophe Ambroise","doi":"10.1186/s13015-020-00173-2","DOIUrl":"https://doi.org/10.1186/s13015-020-00173-2","url":null,"abstract":"<p><strong>Motivation: </strong>Association studies have been widely used to search for associations between common genetic variants observations and a given phenotype. However, it is now generally accepted that genes and environment must be examined jointly when estimating phenotypic variance. In this work we consider two types of biological markers: genotypic markers, which characterize an observation in terms of inherited genetic information, and metagenomic marker which are related to the environment. Both types of markers are available in their millions and can be used to characterize any observation uniquely.</p><p><strong>Objective: </strong>Our focus is on detecting interactions between groups of genetic and metagenomic markers in order to gain a better understanding of the complex relationship between environment and genome in the expression of a given phenotype.</p><p><strong>Contributions: </strong>We propose a novel approach for efficiently detecting interactions between complementary datasets in a high-dimensional setting with a reduced computational cost. The method, named SICOMORE, reduces the dimension of the search space by selecting a subset of supervariables in the two complementary datasets. These supervariables are given by a weighted group structure defined on sets of variables at different scales. A Lasso selection is then applied on each type of supervariable to obtain a subset of potential interactions that will be explored via linear model testing.</p><p><strong>Results: </strong>We compare SICOMORE with other approaches in simulations, with varying sample sizes, noise, and numbers of true interactions. SICOMORE exhibits convincing results in terms of recall, as well as competitive performances with respect to running time. The method is also used to detect interaction between genomic markers in <i>Medicago truncatula</i> and metagenomic markers in its rhizosphere bacterial community.</p><p><strong>Software availability: </strong>An R package is available [4], along with its documentation and associated scripts, allowing the reader to reproduce the results presented in the paper.</p>","PeriodicalId":50823,"journal":{"name":"Algorithms for Molecular Biology","volume":"15 ","pages":"13"},"PeriodicalIF":1.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s13015-020-00173-2","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38119459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evolution through segmental duplications and losses: a Super-Reconciliation approach.","authors":"Mattéo Delabre,&nbsp;Nadia El-Mabrouk,&nbsp;Katharina T Huber,&nbsp;Manuel Lafond,&nbsp;Vincent Moulton,&nbsp;Emmanuel Noutahi,&nbsp;Miguel Sautie Castellanos","doi":"10.1186/s13015-020-00171-4","DOIUrl":"https://doi.org/10.1186/s13015-020-00171-4","url":null,"abstract":"<p><p>The classical gene and species tree reconciliation, used to infer the history of gene gain and loss explaining the evolution of gene families, assumes an independent evolution for each family. While this assumption is reasonable for genes that are far apart in the genome, it is not appropriate for genes grouped into syntenic blocks, which are more plausibly the result of a concerted evolution. Here, we introduce the <i>Super-Reconciliation</i> problem which consists in inferring a history of segmental duplication and loss events (involving a set of neighboring genes) leading to a set of present-day syntenies from a single ancestral one. In other words, we extend the traditional Duplication-Loss reconciliation problem of a single gene tree, to a set of trees, accounting for segmental duplications and losses. Existency of a Super-Reconciliation depends on individual gene tree consistency. In addition, ignoring rearrangements implies that existency also depends on gene order consistency. We first show that the problem of reconstructing a most parsimonious Super-Reconciliation, if any, is NP-hard and give an exact exponential-time algorithm to solve it. Alternatively, we show that accounting for rearrangements in the evolutionary model, but still only minimizing segmental duplication and loss events, leads to an exact polynomial-time algorithm. We finally assess time efficiency of the former exponential time algorithm for the Duplication-Loss model on simulated datasets, and give a proof of concept on the opioid receptor genes.</p>","PeriodicalId":50823,"journal":{"name":"Algorithms for Molecular Biology","volume":"15 ","pages":"12"},"PeriodicalIF":1.0,"publicationDate":"2020-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s13015-020-00171-4","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38022547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The distance and median problems in the single-cut-or-join model with single-gene duplications.","authors":"Aniket C Mane,&nbsp;Manuel Lafond,&nbsp;Pedro C Feijao,&nbsp;Cedric Chauve","doi":"10.1186/s13015-020-00169-y","DOIUrl":"https://doi.org/10.1186/s13015-020-00169-y","url":null,"abstract":"<p><strong>Background: </strong>In the field of genome rearrangement algorithms, models accounting for gene duplication lead often to hard problems. For example, while computing the pairwise distance is tractable in most duplication-free models, the problem is NP-complete for most extensions of these models accounting for duplicated genes. Moreover, problems involving more than two genomes, such as the genome median and the Small Parsimony problem, are intractable for most duplication-free models, with some exceptions, for example the Single-Cut-or-Join (SCJ) model.</p><p><strong>Results: </strong>We introduce a variant of the SCJ distance that accounts for duplicated genes, in the context of directed evolution from an ancestral genome to a descendant genome where orthology relations between ancestral genes and their descendant are known. Our model includes two duplication mechanisms: single-gene tandem duplication and the creation of single-gene circular chromosomes. We prove that in this model, computing the directed distance and a parsimonious evolutionary scenario in terms of SCJ and single-gene duplication events can be done in linear time. We also show that the directed median problem is tractable for this distance, while the rooted median problem, where we assume that one of the given genomes is ancestral to the median, is NP-complete. We also describe an Integer Linear Program for solving this problem. We evaluate the directed distance and rooted median algorithms on simulated data.</p><p><strong>Conclusion: </strong>Our results provide a simple genome rearrangement model, extending the SCJ model to account for single-gene duplications, for which we prove a mix of tractability and hardness results. For the NP-complete rooted median problem, we design a simple Integer Linear Program. Our publicly available implementation of these algorithms for the directed distance and median problems allow to solve efficiently these problems on large instances.</p>","PeriodicalId":50823,"journal":{"name":"Algorithms for Molecular Biology","volume":"15 ","pages":"8"},"PeriodicalIF":1.0,"publicationDate":"2020-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s13015-020-00169-y","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37920085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Non-parametric and semi-parametric support estimation using SEquential RESampling random walks on biomolecular sequences.","authors":"Wei Wang,&nbsp;Jack Smith,&nbsp;Hussein A Hejase,&nbsp;Kevin J Liu","doi":"10.1186/s13015-020-00167-0","DOIUrl":"https://doi.org/10.1186/s13015-020-00167-0","url":null,"abstract":"<p><p>Non-parametric and semi-parametric resampling procedures are widely used to perform support estimation in computational biology and bioinformatics. Among the most widely used methods in this class is the standard bootstrap method, which consists of random sampling with replacement. While not requiring assumptions about any particular parametric model for resampling purposes, the bootstrap and related techniques assume that sites are independent and identically distributed (i.i.d.). The i.i.d. assumption can be an over-simplification for many problems in computational biology and bioinformatics. In particular, sequential dependence within biomolecular sequences is often an essential biological feature due to biochemical function, evolutionary processes such as recombination, and other factors. To relax the simplifying i.i.d. assumption, we propose a new non-parametric/semi-parametric sequential resampling technique that generalizes \"Heads-or-Tails\" mirrored inputs, a simple but clever technique due to Landan and Graur. The generalized procedure takes the form of random walks along either aligned or unaligned biomolecular sequences. We refer to our new method as the SERES (or \"SEquential RESampling\") method. To demonstrate the performance of the new technique, we apply SERES to estimate support for the multiple sequence alignment problem. Using simulated and empirical data, we show that SERES-based support estimation yields comparable or typically better performance compared to state-of-the-art methods.</p>","PeriodicalId":50823,"journal":{"name":"Algorithms for Molecular Biology","volume":"15 ","pages":"7"},"PeriodicalIF":1.0,"publicationDate":"2020-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s13015-020-00167-0","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37862476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Linear-time algorithms for phylogenetic tree completion under Robinson-Foulds distance.","authors":"Mukul S Bansal","doi":"10.1186/s13015-020-00166-1","DOIUrl":"https://doi.org/10.1186/s13015-020-00166-1","url":null,"abstract":"<p><strong>Background: </strong>We consider two fundamental computational problems that arise when comparing phylogenetic trees, rooted or unrooted, with non-identical leaf sets. The first problem arises when comparing two trees where the leaf set of one tree is a proper subset of the other. The second problem arises when the two trees to be compared have only partially overlapping leaf sets. The traditional approach to handling these problems is to first restrict the two trees to their common leaf set. An alternative approach that has shown promise is to first <i>complete</i> the trees by adding missing leaves, so that the resulting trees have identical leaf sets. This requires the computation of an optimal completion that minimizes the distance between the two resulting trees over all possible completions.</p><p><strong>Results: </strong>We provide optimal linear-time algorithms for both completion problems under the widely-used Robinson-Foulds (RF) distance measure. Our algorithm for the first problem improves the time complexity of the current fastest algorithm from quadratic (in the size of the two trees) to linear. No algorithms have yet been proposed for the more general second problem where both trees have missing leaves. We advance the study of this general problem by proposing a useful restricted version of the general problem and providing optimal linear-time algorithms for the restricted version. Our experimental results on biological data sets suggest that completion-based RF distances can be very different compared to traditional RF distances.</p>","PeriodicalId":50823,"journal":{"name":"Algorithms for Molecular Biology","volume":"15 ","pages":"6"},"PeriodicalIF":1.0,"publicationDate":"2020-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s13015-020-00166-1","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37853940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GrpClassifierEC: a novel classification approach based on the ensemble clustering space.","authors":"Loai Abdallah,&nbsp;Malik Yousef","doi":"10.1186/s13015-020-0162-7","DOIUrl":"https://doi.org/10.1186/s13015-020-0162-7","url":null,"abstract":"<p><strong>Background: </strong>Advances in molecular biology have resulted in big and complicated data sets, therefore a clustering approach that able to capture the actual structure and the hidden patterns of the data is required. Moreover, the geometric space may not reflects the actual similarity between the different objects. As a result, in this research we use clustering-based space that convert the geometric space of the molecular to a categorical space based on clustering results. Then we use this space for developing a new classification algorithm.</p><p><strong>Results: </strong>In this study, we propose a new classification method named <i>GrpClassifierEC</i> that replaces the given data space with categorical space based on ensemble clustering (EC). The EC space is defined by tracking the membership of the points over multiple runs of clustering algorithms. Different points that were included in the same clusters will be represented as a single point. Our algorithm classifies all these points as a single class. The similarity between two objects is defined as the number of times that these objects were not belong to the same cluster. In order to evaluate our suggested method, we compare its results to the <i>k</i> nearest neighbors, Decision tree and Random forest classification algorithms on several benchmark datasets. The results confirm that the suggested new algorithm <i>GrpClassifierEC</i> outperforms the other algorithms.</p><p><strong>Conclusions: </strong>Our algorithm can be integrated with many other algorithms. In this research, we use only the k-means clustering algorithm with different k values. In future research, we propose several directions: (1) checking the effect of the clustering algorithm to build an ensemble clustering space. (2) Finding poor clustering results based on the training data, (3) reducing the volume of the data by combining similar points based on the EC.</p><p><strong>Availability and implementation: </strong>The KNIME workflow, implementing <i>GrpClassifierEC</i>, is available at https://malikyousef.com.</p>","PeriodicalId":50823,"journal":{"name":"Algorithms for Molecular Biology","volume":"15 ","pages":"3"},"PeriodicalIF":1.0,"publicationDate":"2020-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s13015-020-0162-7","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37664645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Non-parametric correction of estimated gene trees using TRACTION.","authors":"Sarah Christensen,&nbsp;Erin K Molloy,&nbsp;Pranjal Vachaspati,&nbsp;Ananya Yammanuru,&nbsp;Tandy Warnow","doi":"10.1186/s13015-019-0161-8","DOIUrl":"https://doi.org/10.1186/s13015-019-0161-8","url":null,"abstract":"<p><strong>Motivation: </strong>Estimated gene trees are often inaccurate, due to insufficient phylogenetic signal in the single gene alignment, among other causes. Gene tree correction aims to improve the accuracy of an estimated gene tree by using computational techniques along with auxiliary information, such as a reference species tree or sequencing data. However, gene trees and species trees can differ as a result of gene duplication and loss (GDL), incomplete lineage sorting (ILS), and other biological processes. Thus gene tree correction methods need to take estimation error as well as gene tree heterogeneity into account. Many prior gene tree correction methods have been developed for the case where GDL is present.</p><p><strong>Results: </strong>Here, we study the problem of gene tree correction where gene tree heterogeneity is instead due to ILS and/or HGT. We introduce TRACTION, a simple polynomial time method that provably finds an optimal solution to the RF-optimal tree refinement and completion (RF-OTRC) Problem, which seeks a refinement and completion of a singly-labeled gene tree with respect to a given singly-labeled species tree so as to minimize the Robinson-Foulds (RF) distance. Our extensive simulation study on 68,000 estimated gene trees shows that TRACTION matches or improves on the accuracy of well-established methods from the GDL literature when HGT and ILS are both present, and ties for best under the ILS-only conditions. Furthermore, TRACTION ties for fastest on these datasets. We also show that a naive generalization of the RF-OTRC problem to multi-labeled trees is possible, but can produce misleading results where gene tree heterogeneity is due to GDL.</p>","PeriodicalId":50823,"journal":{"name":"Algorithms for Molecular Biology","volume":"15 ","pages":"1"},"PeriodicalIF":1.0,"publicationDate":"2020-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s13015-019-0161-8","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37519970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Kohdista: an efficient method to index and query possible Rmap alignments.","authors":"Martin D Muggli,&nbsp;Simon J Puglisi,&nbsp;Christina Boucher","doi":"10.1186/s13015-019-0160-9","DOIUrl":"https://doi.org/10.1186/s13015-019-0160-9","url":null,"abstract":"<p><strong>Background: </strong>Genome-wide optical maps are ordered high-resolution restriction maps that give the position of occurrence of restriction cut sites corresponding to one or more restriction enzymes. These genome-wide optical maps are assembled using an overlap-layout-consensus approach using raw optical map data, which are referred to as Rmaps. Due to the high error-rate of Rmap data, finding the overlap between Rmaps remains challenging.</p><p><strong>Results: </strong>We present Kohdista, which is an index-based algorithm for finding pairwise alignments between single molecule maps (<i>Rmaps</i>). The novelty of our approach is the formulation of the alignment problem as automaton path matching, and the application of modern index-based data structures. In particular, we combine the use of the Generalized Compressed Suffix Array (GCSA) index with the wavelet tree in order to build Kohdista. We validate Kohdista on simulated <i>E. coli</i> data, showing the approach successfully finds alignments between Rmaps simulated from overlapping genomic regions.</p><p><strong>Conclusion: </strong>we demonstrate Kohdista is the only method that is capable of finding a significant number of high quality pairwise Rmap alignments for large eukaryote organisms in reasonable time.</p>","PeriodicalId":50823,"journal":{"name":"Algorithms for Molecular Biology","volume":" ","pages":"25"},"PeriodicalIF":1.0,"publicationDate":"2019-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s13015-019-0160-9","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37483243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"NANUQ: a method for inferring species networks from gene trees under the coalescent model.","authors":"Elizabeth S Allman,&nbsp;Hector Baños,&nbsp;John A Rhodes","doi":"10.1186/s13015-019-0159-2","DOIUrl":"https://doi.org/10.1186/s13015-019-0159-2","url":null,"abstract":"<p><p>Species networks generalize the notion of species trees to allow for hybridization or other lateral gene transfer. Under the network multispecies coalescent model, individual gene trees arising from a network can have any topology, but arise with frequencies dependent on the network structure and numerical parameters. We propose a new algorithm for statistical inference of a level-1 species network under this model, from data consisting of gene tree topologies, and provide the theoretical justification for it. The algorithm is based on an analysis of quartets displayed on gene trees, combining several statistical hypothesis tests with combinatorial ideas such as a quartet-based intertaxon distance appropriate to networks, the NeighborNet algorithm for circular split systems, and the Circular Network algorithm for constructing a splits graph.</p>","PeriodicalId":50823,"journal":{"name":"Algorithms for Molecular Biology","volume":" ","pages":"24"},"PeriodicalIF":1.0,"publicationDate":"2019-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s13015-019-0159-2","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37449224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"TMRS: an algorithm for computing the time to the most recent substitution event from a multiple alignment column.","authors":"Hisanori Kiryu,&nbsp;Yuto Ichikawa,&nbsp;Yasuhiro Kojima","doi":"10.1186/s13015-019-0158-3","DOIUrl":"https://doi.org/10.1186/s13015-019-0158-3","url":null,"abstract":"<p><strong>Background: </strong>As the number of sequenced genomes grows, researchers have access to an increasingly rich source for discovering detailed evolutionary information. However, the computational technologies for inferring biologically important evolutionary events are not sufficiently developed.</p><p><strong>Results: </strong>We present algorithms to estimate the evolutionary time ( <math><msub><mi>t</mi> <mtext>MRS</mtext></msub> </math> ) to the most recent substitution event from a multiple alignment column by using a probabilistic model of sequence evolution. As the confidence in estimated <math><msub><mi>t</mi> <mtext>MRS</mtext></msub> </math> values varies depending on gap fractions and nucleotide patterns of alignment columns, we also compute the standard deviation <math><mi>σ</mi></math> of <math><msub><mi>t</mi> <mtext>MRS</mtext></msub> </math> by using a dynamic programming algorithm. We identified a number of human genomic sites at which the last substitutions occurred between two speciation events in the human lineage with confidence. A large fraction of such sites have substitutions that occurred between the concestor nodes of Hominoidea and Euarchontoglires. We investigated the correlation between tissue-specific transcribed enhancers and the distribution of the sites with specific substitution time intervals, and found that brain-specific transcribed enhancers are threefold enriched in the density of substitutions in the human lineage relative to expectations.</p><p><strong>Conclusions: </strong>We have presented algorithms to estimate the evolutionary time ( <math><msub><mi>t</mi> <mtext>MRS</mtext></msub> </math> ) to the most recent substitution event from a multiple alignment column by using a probabilistic model of sequence evolution. Our algorithms will be useful for Evo-Devo studies, as they facilitate screening potential genomic sites that have played an important role in the acquisition of unique biological features by target species.</p>","PeriodicalId":50823,"journal":{"name":"Algorithms for Molecular Biology","volume":" ","pages":"23"},"PeriodicalIF":1.0,"publicationDate":"2019-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s13015-019-0158-3","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37453129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}