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  • 1.
    Ali, Raja Hashim
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Arvestad, Lars
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Burnin estimation and convergence assessment in Bayesian phylogenetic inferenceManuskript (preprint) (Annet vitenskapelig)
    Abstract [en]

     Convergence assessment and burnin estimation are central concepts in Markov chain Monte Carlo algorithms. Studies on eects, statistical properties, and comparisons between dierent convergence assessment methods have been conducted during the past few decades. However, not much work has been done on the eect of convergence diagnostic on posterior distribution of tree parameters and which method should be used by researchers in Bayesian phylogenetics inference. In this study, we propose and evaluate two novel burnin estimation methods that estimate burnin using all parameters jointly. We also consider some other popular convergence diagnostics, evaluate them in light of parallel chains and quantify the eect of burnin estimates from various convergence diagnostics on the posterior distribution of trees. We motivate the use of convergence diagnostics to assess convergence and estimate burnin in Bayesian phylogenetics inference and found out that it is better to employ convergence diagnostics rather than remove a xed percentage as burnin. We concluded that the last burnin estimator using eective sample size appears to estimate burnin better than all other convergence diagnostics.

  • 2.
    Ali, Raja Hashim
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Bark, Mikael
    KTH, Skolan för informations- och kommunikationsteknik (ICT).
    Miro, Jorge
    KTH, Skolan för informations- och kommunikationsteknik (ICT).
    Muhammad, Sayyed Auwn
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Sjöstrand, Joel
    Stockholm University.
    Zubair, Syed Muhammad
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsnät. University of Balochistan, Pakistan.
    Abbas, Raja Manzar
    Arvestad, Lars
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    VMCMC: a graphical and statistical analysis tool for Markov chain Monte Carlo tracesManuskript (preprint) (Annet vitenskapelig)
    Abstract [en]

    Motivation: MCMC-based methods are important for Bayesian inference of phylogeny and related parameters. Although being computationally expensive, MCMC yields estimates of posterior distributions that are useful for estimating parameter values and are easy to use in subsequent analysis. There are, however, sometimes practical diculties with MCMC, relating to convergence assessment and determining burn-in, especially in large-scale analyses. Currently, multiple software are required to perform, e.g., convergence, mixing and interactive exploration of both continuous and tree parameters.

    Results: We have written a software called VMCMC to simplify post-processing of MCMC traces with, for example, automatic burn-in estimation. VMCMC can also be used both as a GUI-based application, supporting interactive exploration, and as a command-line tool suitable for automated pipelines.

    Availability: VMCMC is available for Java SE 6+ under the New BSD License. Executable jar les, tutorial manual and source code can be downloaded from https://bitbucket.org/rhali/visualmcmc/.

  • 3.
    Ali, Raja Hashim
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Muhammad, Sayyed Auwn
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    Arvestad, Lars
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST).
    GenFamClust: An accurate, synteny-aware and reliable homology inference algorithm2016Inngår i: BMC EVOLUTIONARY BIOLOGY, ISSN 1471-2148, Vol. 16Artikkel i tidsskrift (Annet vitenskapelig)
    Abstract [en]

    Background: Homology inference is pivotal to evolutionary biology and is primarily based on significant sequence similarity, which, in general, is a good indicator of homology. Algorithms have also been designed to utilize conservation in gene order as an indication of homologous regions. We have developed GenFamClust, a method based on quantification of both gene order conservation and sequence similarity. Results: In this study, we validate GenFamClust by comparing it to well known homology inference algorithms on a synthetic dataset. We applied several popular clustering algorithms on homologs inferred by GenFamClust and other algorithms on a metazoan dataset and studied the outcomes. Accuracy, similarity, dependence, and other characteristics were investigated for gene families yielded by the clustering algorithms. GenFamClust was also applied to genes from a set of complete fungal genomes and gene families were inferred using clustering. The resulting gene families were compared with a manually curated gold standard of pillars from the Yeast Gene Order Browser. We found that the gene-order component of GenFamClust is simple, yet biologically realistic, and captures local synteny information for homologs. Conclusions: The study shows that GenFamClust is a more accurate, informed, and comprehensive pipeline to infer homologs and gene families than other commonly used homology and gene-family inference methods.

  • 4.
    Ali, Raja Hashim
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Muhammad, Sayyed Auwn
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Khan, Mehmodd Alam
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Arvestad, Lars
    Stockholms universitet.
    Quantitative synteny scoring improves homology inference and partitioning of gene families2013Inngår i: BMC Bioinformatics, ISSN 1471-2105, E-ISSN 1471-2105, Vol. 14, s. S12-Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Background: Clustering sequences into families has long been an important step in characterization of genes and proteins. There are many algorithms developed for this purpose, most of which are based on either direct similarity between gene pairs or some sort of network structure, where weights on edges of constructed graphs are based on similarity. However, conserved synteny is an important signal that can help distinguish homology and it has not been utilized to its fullest potential. Results: Here, we present GenFamClust, a pipeline that combines the network properties of sequence similarity and synteny to assess homology relationship and merge known homologs into groups of gene families. GenFamClust identifies homologs in a more informed and accurate manner as compared to similarity based approaches. We tested our method against the Neighborhood Correlation method on two diverse datasets consisting of fully sequenced genomes of eukaryotes and synthetic data. Conclusions: The results obtained from both datasets confirm that synteny helps determine homology and GenFamClust improves on Neighborhood Correlation method. The accuracy as well as the definition of synteny scores is the most valuable contribution of GenFamClust.

  • 5.
    Emanuelsson, Olof
    et al.
    KTH, Skolan för bioteknologi (BIO), Genteknologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Arvestad, Lars
    KTH, Centra, Science for Life Laboratory, SciLifeLab. Stockholm University.
    Käll, Lukas
    KTH, Skolan för bioteknologi (BIO), Genteknologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Engagera och aktivera studenter med inspiration från konferenser: examination genom poster-presentation2014Inngår i: Proceedings 2014, 8:e Pedagogiska inspirationskonferensen 17 december 2014 / [ed] Roy Andersson, Lund, 2014Konferansepaper (Fagfellevurdert)
    Abstract [sv]

    I en forskningsnära kurs om 7.5 hp på master-nivå inom bioinformatikämnet vid KTH består drygt halva kursen av ett projekt som genomförs i grupper om tre studenter. Varje projekt har en egen projektuppgift med inget eller marginellt överlapp med andra gruppers uppgifter. Projekten är så gott som uteslutande baserade på aktuella frågeställningar i lärarteamets egna forskningsgrupper eller deras närhet. Projektet redovisas dels genom en posterpresentation, dels med individuell webbaserad projektdagbok. Vid posterredovisningen, som omfattar tre timmar i slutet av tentamensperioden, är alla kursdeltagare med. Vi försöker i möjligaste mån efterlikna situationen där ett autentiskt forskningsresultat presenteras på en riktig konferens. Varje deltagare (student) förväntas alltså ta del av varje annan grupps poster, på samma sätt som sker vid de flesta vetenskapliga konferenser. Vi genomför en enklare kamratbedömning på posternivå, där varje student ska avge en kort och konfidentiell kommentar om var och en av övriga postrar. Kursens lärare bedömer förstås också postrarna. En av svårigheterna är att sätta individuella betyg. Här använder vi oss av individuella projektdagböcker, som ger vägledning till de olika individernas insatser inom projektet. Vi har provat detta under fyra kursomgångar med som mest sju projekt. Examinationsformen är rolig och motiverande både för studenterna och lärarna.

  • 6.
    Kahles, André
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Sarqume, Fahad
    KTH, Skolan för bioteknologi (BIO).
    Savolainen, Peter
    KTH, Skolan för bioteknologi (BIO), Genteknologi. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Arvestad, Lars
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. KTH, Centra, Science for Life Laboratory, SciLifeLab. Stockholms universitet.
    Excap: maximization of haplotypic diversity of linked markers2013Inngår i: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 8, nr 11, s. e79012-Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Genetic markers, defined as variable regions of DNA, can be utilized for distinguishing individuals or populations. As long as markers are independent, it is easy to combine the information they provide. For nonrecombinant sequences like mtDNA, choosing the right set of markers for forensic applications can be difficult and requires careful consideration. In particular, one wants to maximize the utility of the markers. Until now, this has mainly been done by hand. We propose an algorithm that finds the most informative subset of a set of markers. The algorithm uses a depth first search combined with a branch-and-bound approach. Since the worst case complexity is exponential, we also propose some data-reduction techniques and a heuristic. We implemented the algorithm and applied it to two forensic caseworks using mitochondrial DNA, which resulted in marker sets with significantly improved haplotypic diversity compared to previous suggestions. Additionally, we evaluated the quality of the estimation with an artificial dataset of mtDNA. The heuristic is shown to provide extensive speedup at little cost in accuracy.

  • 7.
    Khan, Mehmood Alam
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Elias, Isaac
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Sjölund, Erik
    Stockholms universitet.
    Nylander, Kristina
    KTH, Skolan för datavetenskap och kommunikation (CSC).
    Guimera, Roman Valls
    Stockholms univetsitet.
    Schobesberger, Richard
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. University of Applied Sciences Upper Austria.
    Schmitzberger, Peter
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. University of Applied Sciences Upper Austria.
    Lagergren, Jens
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Arvestad, Lars
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    fastphylo: Fast tools for phylogenetics2013Inngår i: BMC Bioinformatics, ISSN 1471-2105, E-ISSN 1471-2105, Vol. 14, nr 1, s. 334-Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Background: Distance methods are ubiquitous tools in phylogenetics. Their primary purpose may be to reconstruct evolutionary history, but they are also used as components in bioinformatic pipelines. However, poor computational efficiency has been a constraint on the applicability of distance methods on very large problem instances. Results: We present fastphylo, a software package containing implementations of efficient algorithms for two common problems in phylogenetics: estimating DNA/protein sequence distances and reconstructing a phylogeny from a distance matrix. We compare fastphylo with other neighbor joining based methods and report the results in terms of speed and memory efficiency. Conclusions: Fastphylo is a fast, memory efficient, and easy to use software suite. Due to its modular architecture, fastphylo is a flexible tool for many phylogenetic studies.

  • 8.
    Khan, Mehmood Alam
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC). KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Mahmudi, Owais
    KTH, Skolan för datavetenskap och kommunikation (CSC). KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Ulah, Ikram
    KTH, Skolan för datavetenskap och kommunikation (CSC). KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Arvestad, Lars
    KTH, Centra, Science for Life Laboratory, SciLifeLab. KTH, Centra, SeRC - Swedish e-Science Research Centre. Stockholm Univ, Sweden.
    Lagergren, Jens
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST). KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Probabilistic inference of lateral gene transfer events2016Inngår i: BMC Bioinformatics, ISSN 1471-2105, E-ISSN 1471-2105, Vol. 17, artikkel-id 431Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Background: Lateral gene transfer (LGT) is an evolutionary process that has an important role in biology. It challenges the traditional binary tree-like evolution of species and is attracting increasing attention of the molecular biologists due to its involvement in antibiotic resistance. A number of attempts have been made to model LGT in the presence of gene duplication and loss, but reliably placing LGT events in the species tree has remained a challenge. Results: In this paper, we propose probabilistic methods that samples reconciliations of the gene tree with a dated species tree and computes maximum a posteriori probabilities. The MCMC-based method uses the probabilistic model DLTRS, that integrates LGT, gene duplication, gene loss, and sequence evolution under a relaxed molecular clock for substitution rates. We can estimate posterior distributions on gene trees and, in contrast to previous work, the actual placement of potential LGT, which can be used to, e.g., identify "highways" of LGT. Conclusions: Based on a simulation study, we conclude that the method is able to infer the true LGT events on gene tree and reconcile it to the correct edges on the species tree in most cases. Applied to two biological datasets, containing gene families from Cyanobacteria and Molicutes, we find potential LGTs highways that corroborate other studies as well as previously undetected examples.

  • 9.
    Klinter, Stefan
    et al.
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Kemi, Glykovetenskap.
    Bulone, Vincent
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Kemi, Glykovetenskap. Univ Adelaide, ARC Ctr Excellence Plant Cell Walls, Waite Campus, Urrbrae, SA 5064, Australia.;Univ Adelaide, Sch Agr Food & Wine, Waite Campus, Urrbrae, SA 5064, Australia..
    Arvestad, Lars
    Stockholm Univ, Dept Math, Swedish E Sci Res Ctr, Sci Life Lab, S-10691 Stockholm, Sweden..
    Diversity and evolution of chitin synthases in oomycetes (Straminipila: Oomycota)2019Inngår i: Molecular Phylogenetics and Evolution, ISSN 1055-7903, E-ISSN 1095-9513, Vol. 139, artikkel-id 106558Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The oomycetes are filamentous eukaryotic microorganisms, distinct from true fungi, many of which act as crop or fish pathogens that cause devastating losses in agriculture and aquaculture. Chitin is present in all true fungi, but it occurs in only small amounts in some Saprolegniomycetes and it is absent in Peronosporomycetes. However, the growth of several oomycetes is severely impacted by competitive chitin synthase (CHS) inhibitors. Here, we shed light on the diversity, evolution and function of oomycete CHS proteins. We show by phylogenetic analysis of 93 putative CHSs from 48 highly diverse oomycetes, including the early diverging Ewychasma dicksonii, that all available oomycete genomes contain at least one putative CHS gene. All gene products contain conserved CHS motifs essential for enzymatic activity and form two Peronosporomycete-specific and six Saprolegniale-specific clades. Proteins of all clades, except one, contain an N-terminal microtubule interacting and trafficking (MIT) domain as predicted by protein domain databases or manual analysis, which is supported by homology modelling and comparison of conserved structural features from sequence logos. We identified at least three groups of CHSs conserved among all oomycete lineages and used phylogenetic reconciliation analysis to infer the dynamic evolution of CHSs in oomycetes. The evolutionary aspects of CHS diversity in modern-day oomycetes are discussed. In addition, we observed hyphal tip rupture in Phytophthora infestans upon treatment with the CHS inhibitor nikkomycin Z. Combining data on phylogeny, gene expression, and response to CHS inhibitors, we propose the association of different CHS clades with certain developmental stages.

  • 10.
    Sahlin, Kristoffer
    et al.
    KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Frånberg, M.
    Arvestad, Lars
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsvetenskap och beräkningsteknik (CST). KTH, Centra, SeRC - Swedish e-Science Research Centre. Stockholm University, Sweden.
    Structural Variation Detection with Read Pair Information: An Improved Null Hypothesis Reduces Bias2017Inngår i: Journal of Computational Biology, ISSN 1066-5277, E-ISSN 1557-8666, Vol. 24, nr 6, s. 581-589Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Reads from paired-end and mate-pair libraries are often utilized to find structural variation in genomes, and one common approach is to use their fragment length for detection. After aligning read pairs to the reference, read pair distances are analyzed for statistically significant deviations. However, previously proposed methods are based on a simplified model of observed fragment lengths that does not agree with data. We show how this model limits statistical analysis of identifying variants and propose a new model by adapting a model we have previously introduced for contig scaffolding, which agrees with data. From this model, we derive an improved null hypothesis that when applied in the variant caller CLEVER, reduces the number of false positives and corrects a bias that contributes to more deletion calls than insertion calls. We advise developers of variant callers with statistical fragment length-based methods to adapt the concepts in our proposed model and null hypothesis.

1 - 10 of 10
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  • ieee
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  • de-DE
  • en-GB
  • en-US
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  • nn-NO
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