1,810 research outputs found

    RNF: a general framework to evaluate NGS read mappers

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    Aligning reads to a reference sequence is a fundamental step in numerous bioinformatics pipelines. As a consequence, the sensitivity and precision of the mapping tool, applied with certain parameters to certain data, can critically affect the accuracy of produced results (e.g., in variant calling applications). Therefore, there has been an increasing demand of methods for comparing mappers and for measuring effects of their parameters. Read simulators combined with alignment evaluation tools provide the most straightforward way to evaluate and compare mappers. Simulation of reads is accompanied by information about their positions in the source genome. This information is then used to evaluate alignments produced by the mapper. Finally, reports containing statistics of successful read alignments are created. In default of standards for encoding read origins, every evaluation tool has to be made explicitly compatible with the simulator used to generate reads. In order to solve this obstacle, we have created a generic format RNF (Read Naming Format) for assigning read names with encoded information about original positions. Futhermore, we have developed an associated software package RNF containing two principal components. MIShmash applies one of popular read simulating tools (among DwgSim, Art, Mason, CuReSim etc.) and transforms the generated reads into RNF format. LAVEnder evaluates then a given read mapper using simulated reads in RNF format. A special attention is payed to mapping qualities that serve for parametrization of ROC curves, and to evaluation of the effect of read sample contamination

    Renewing the framework for secondary mathematics : spring 2008 subject leader development meeting : sessions 2, 3 and 4

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    Graph Isomorphism and the Lasserre Hierarchy

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    In this paper we show lower bounds for a certain large class of algorithms solving the Graph Isomorphism problem, even on expander graph instances. Spielman [25] shows an algorithm for isomorphism of strongly regular expander graphs that runs in time exp(O(n^(1/3)) (this bound was recently improved to expf O(n^(1/5) [5]). It has since been an open question to remove the requirement that the graph be strongly regular. Recent algorithmic results show that for many problems the Lasserre hierarchy works surprisingly well when the underlying graph has expansion properties. Moreover, recent work of Atserias and Maneva [3] shows that k rounds of the Lasserre hierarchy is a generalization of the k-dimensional Weisfeiler-Lehman algorithm for Graph Isomorphism. These two facts combined make the Lasserre hierarchy a good candidate for solving graph isomorphism on expander graphs. Our main result rules out this promising direction by showing that even Omega(n) rounds of the Lasserre semidefinite program hierarchy fail to solve the Graph Isomorphism problem even on expander graphs.Comment: 22 pages, 3 figures, submitted to CC

    Visualizing dimensionality reduction of systems biology data

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    One of the challenges in analyzing high-dimensional expression data is the detection of important biological signals. A common approach is to apply a dimension reduction method, such as principal component analysis. Typically, after application of such a method the data is projected and visualized in the new coordinate system, using scatter plots or profile plots. These methods provide good results if the data have certain properties which become visible in the new coordinate system and which were hard to detect in the original coordinate system. Often however, the application of only one method does not suffice to capture all important signals. Therefore several methods addressing different aspects of the data need to be applied. We have developed a framework for linear and non-linear dimension reduction methods within our visual analytics pipeline SpRay. This includes measures that assist the interpretation of the factorization result. Different visualizations of these measures can be combined with functional annotations that support the interpretation of the results. We show an application to high-resolution time series microarray data in the antibiotic-producing organism Streptomyces coelicolor as well as to microarray data measuring expression of cells with normal karyotype and cells with trisomies of human chromosomes 13 and 21

    Versatile Markovian models for networks with asymmetric TCP sources

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    In this paper we use Stochastic Petri Nets (SPNs) to study the interaction of multiple TCP sources that share one or two buffers, thereby considerably extending earlier work. We first consider two sources sharing a buffer and investigate the consequences of two popular assumptions for the loss process in terms of fairness and link utilization. The results obtained by our model are in agreement with existing analytic models or are closer to results obtained by ns-2 simulations. We then study a network consisting of three sources and two buffers and provide evidence that link sharing is approximately minimum-potential-delay-fair in case of equal round-trip times. \u

    Existence of a Meromorphic Extension of Spectral Zeta Functions on Fractals

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    We investigate the existence of the meromorphic extension of the spectral zeta function of the Laplacian on self-similar fractals using the classical results of Kigami and Lapidus (based on the renewal theory) and new results of Hambly and Kajino based on the heat kernel estimates and other probabilistic techniques. We also formulate conjectures which hold true in the examples that have been analyzed in the existing literature

    Projective Techniques and Functional Integration

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    A general framework for integration over certain infinite dimensional spaces is first developed using projective limits of a projective family of compact Hausdorff spaces. The procedure is then applied to gauge theories to carry out integration over the non-linear, infinite dimensional spaces of connections modulo gauge transformations. This method of evaluating functional integrals can be used either in the Euclidean path integral approach or the Lorentzian canonical approach. A number of measures discussed are diffeomorphism invariant and therefore of interest to (the connection dynamics version of) quantum general relativity. The account is pedagogical; in particular prior knowledge of projective techniques is not assumed. (For the special JMP issue on Functional Integration, edited by C. DeWitt-Morette.)Comment: 36 pages, latex, no figures, Preprint CGPG/94/10-
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