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A Comprehensive Workflow for Variant Calling Pipeline Comparison and Analysis Using R Programming
www.ijcrt.org © 2020 IJCRT | Volume 8, Issue 8 August 2020 | ISSN: 2320-2882 A COMPREHENSIVE WORKFLOW FOR VARIANT CALLING PIPELINE COMPARISON AND ANALYSIS USING R PROGRAMMING 1Mansi Ujjainwal, 2Preeti Chaudhary 1MSc Bioinformatics, 2Mtech Bioinformatics, 1Amity Institute of Biotechnology 1Amity University, Noida, India Abstract: The aim of the article is to provide variant calling workflow and analysis protocol for comparing results of the two using two variant calling platforms. Variant calling pipelines used here are predominantly used for calling variants in human whole exome data and whole genome data. The result of a variant calling pipeline is a set of variants( SNPS, insertions, deletions etc) present in the sequencing data. Each pipeline is capable of calling its certain intersecting and certain unique variants. The intersecting and unique variants can further be distinguished on the basis of their reference SNP ID and grouped on the basis of its annotation. The number of variants called can be humongous depending upon the size and complexity of the data. R programming packages and ubuntu command shell can be used to differentiate and analyse the variants called by each type of pipeline. Index Terms – Whole Exome Sequencing, Variant Calling, Sequencing data, R programming I. INTRODUCTION The Human Genome Project started in 1990, makes up the single most significant project in the field of biomedical sciences and biology. The project was set out to change how we see biology and medicine. The project was set out to sequence complete genome of Homo sapiens as well as several microorganisms including Escherichia coli, Saccharomyces cerevisiae, and metazoans such as Caenorhabtidis elegans. -
Kinesin-4 KIF21B Limits Microtubule Growth to Allow Rapid Centrosome
RESEARCH ARTICLE Kinesin-4 KIF21B limits microtubule growth to allow rapid centrosome polarization in T cells Peter Jan Hooikaas1†, Hugo GJ Damstra1†, Oane J Gros1, Wilhelmina E van Riel1‡, Maud Martin1§, Yesper TH Smits2, Jorg van Loosdregt2, Lukas C Kapitein1, Florian Berger1*, Anna Akhmanova1* 1Cell Biology, Neurobiology and Biophysics, Department of Biology, Faculty of Science, Utrecht University, Utrecht, Netherlands; 2Center for Translational Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands Abstract When a T cell and an antigen-presenting cell form an immunological synapse, rapid dynein-driven translocation of the centrosome toward the contact site leads to reorganization of microtubules and associated organelles. Currently, little is known about how the regulation of *For correspondence: microtubule dynamics contributes to this process. Here, we show that the knockout of KIF21B, a [email protected] (FB); kinesin-4 linked to autoimmune disorders, causes microtubule overgrowth and perturbs [email protected] (AA) centrosome translocation. KIF21B restricts microtubule length by inducing microtubule pausing typically followed by catastrophe. Catastrophe induction with vinblastine prevented microtubule †These authors contributed overgrowth and was sufficient to rescue centrosome polarization in KIF21B-knockout cells. equally to this work Biophysical simulations showed that a relatively small number of KIF21B molecules can restrict ‡ Present address: Netherlands mirotubule length and promote an imbalance -
Bioinformatics Study of Lectins: New Classification and Prediction In
Bioinformatics study of lectins : new classification and prediction in genomes François Bonnardel To cite this version: François Bonnardel. Bioinformatics study of lectins : new classification and prediction in genomes. Structural Biology [q-bio.BM]. Université Grenoble Alpes [2020-..]; Université de Genève, 2021. En- glish. NNT : 2021GRALV010. tel-03331649 HAL Id: tel-03331649 https://tel.archives-ouvertes.fr/tel-03331649 Submitted on 2 Sep 2021 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. THÈSE Pour obtenir le grade de DOCTEUR DE L’UNIVERSITE GRENOBLE ALPES préparée dans le cadre d’une cotutelle entre la Communauté Université Grenoble Alpes et l’Université de Genève Spécialités: Chimie Biologie Arrêté ministériel : le 6 janvier 2005 – 25 mai 2016 Présentée par François Bonnardel Thèse dirigée par la Dr. Anne Imberty codirigée par la Dr/Prof. Frédérique Lisacek préparée au sein du laboratoire CERMAV, CNRS et du Computer Science Department, UNIGE et de l’équipe PIG, SIB Dans les Écoles Doctorales EDCSV et UNIGE Etude bioinformatique des lectines: nouvelle classification et prédiction dans les génomes Thèse soutenue publiquement le 8 Février 2021, devant le jury composé de : Dr. Alexandre de Brevern UMR S1134, Inserm, Université Paris Diderot, Paris, France, Rapporteur Dr. -
Toolboxes for a Standardised and Systematic Study of Glycans
Campbell et al. BMC Bioinformatics 2014, 15(Suppl 1):S9 http://www.biomedcentral.com/1471-2105/15/S1/S9 RESEARCH Open Access Toolboxes for a standardised and systematic study of glycans Matthew P Campbell1, René Ranzinger2, Thomas Lütteke3, Julien Mariethoz4, Catherine A Hayes5, Jingyu Zhang1, Yukie Akune6, Kiyoko F Aoki-Kinoshita6, David Damerell7,11, Giorgio Carta8, Will S York2, Stuart M Haslam7, Hisashi Narimatsu9, Pauline M Rudd8, Niclas G Karlsson4, Nicolle H Packer1, Frédérique Lisacek4,10* From Integrated Bio-Search: 12th International Workshop on Network Tools and Applications in Biology (NETTAB 2012) Como, Italy. 14-16 November 2012 Abstract Background: Recent progress in method development for characterising the branched structures of complex carbohydrates has now enabled higher throughput technology. Automation of structure analysis then calls for software development since adding meaning to large data collections in reasonable time requires corresponding bioinformatics methods and tools. Current glycobioinformatics resources do cover information on the structure and function of glycans, their interaction with proteins or their enzymatic synthesis. However, this information is partial, scattered and often difficult to find to for non-glycobiologists. Methods: Following our diagnosis of the causes of the slow development of glycobioinformatics, we review the “objective” difficulties encountered in defining adequate formats for representing complex entities and developing efficient analysis software. Results: Various solutions already implemented and strategies defined to bridge glycobiology with different fields and integrate the heterogeneous glyco-related information are presented. Conclusions: Despite the initial stage of our integrative efforts, this paper highlights the rapid expansion of glycomics, the validity of existing resources and the bright future of glycobioinformatics. -
Property Graph Vs RDF Triple Store: a Comparison on Glycan Substructure Search
RESEARCH ARTICLE Property Graph vs RDF Triple Store: A Comparison on Glycan Substructure Search Davide Alocci1,2, Julien Mariethoz1, Oliver Horlacher1,2, Jerven T. Bolleman3, Matthew P. Campbell4, Frederique Lisacek1,2* 1 Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, Geneva, 1211, Switzerland, 2 Computer Science Department, University of Geneva, Geneva, 1227, Switzerland, 3 Swiss-Prot Group, SIB Swiss Institute of Bioinformatics, Geneva, 1211, Switzerland, 4 Department of Chemistry and Biomolecular Sciences, Macquarie University, Sydney, Australia * [email protected] Abstract Resource description framework (RDF) and Property Graph databases are emerging tech- nologies that are used for storing graph-structured data. We compare these technologies OPEN ACCESS through a molecular biology use case: glycan substructure search. Glycans are branched Citation: Alocci D, Mariethoz J, Horlacher O, tree-like molecules composed of building blocks linked together by chemical bonds. The Bolleman JT, Campbell MP, Lisacek F (2015) molecular structure of a glycan can be encoded into a direct acyclic graph where each node Property Graph vs RDF Triple Store: A Comparison on Glycan Substructure Search. PLoS ONE 10(12): represents a building block and each edge serves as a chemical linkage between two build- e0144578. doi:10.1371/journal.pone.0144578 ing blocks. In this context, Graph databases are possible software solutions for storing gly- Editor: Manuela Helmer-Citterich, University of can structures and Graph query languages, such as SPARQL and Cypher, can be used to Rome Tor Vergata, ITALY perform a substructure search. Glycan substructure searching is an important feature for Received: July 16, 2015 querying structure and experimental glycan databases and retrieving biologically meaning- ful data. -
Genomic Alignment (Mapping) and SNP / Polymorphism Calling
GenomicGenomic alignmentalignment (mapping)(mapping) andand SNPSNP // polymorphismpolymorphism callingcalling Jérôme Mariette & Christophe Klopp http://bioinfo.genotoul.fr/ Bioinfo Genotoul platform – Since 2008 ● 1 Roche 454 ● 1 MiSeq ● 2 HiSeq – Providing ● Data processing for quality control ● Secure data access to end users http://bioinfo.genotoul.fr/ http://ng6.toulouse.inra.fr/ 2 Bioinfo Genotoul : Services – High speed computing facility access – Application and web-server hosting – Training – Support – Project partnership 3 Genetic variation http://en.wikipedia.org/wiki/Genetic_variation Genetic variation, variations in alleles of genes, occurs both within and in populations. Genetic variation is important because it provides the “raw material” for natural selection. http://studentreader.com/genotypes-phenotypes/ 4 Types of variations ● SNP : Single nucleotide polymorphism ● CNV : copy number variation ● Chromosomal rearrangement ● Chromosomal duplication http://en.wikipedia.org/wiki/Copy-number_variation http://en.wikipedia.org/wiki/Human_genetic_variation 5 The variation transmission ● Mutation : In molecular biology and genetics, mutations are changes in a genomic sequence: the DNA sequence of a cell's genome or the DNA or RNA sequence of a virus (http://en.wikipedia.org/wiki/Mutation). ● Mutations are transmitted if they are not lethal. ● Mutations can impact the phenotype. 6 Genetic markers and genotyping ● A set of SNPs is selected along the genome. ● The phenotypes are collected for individuals. ● The SNPs are genotyped -
Cell Architecture: Putting the Building Blocks Together
COCEBI-1090; NO. OF PAGES 3 Available online at www.sciencedirect.com Cell architecture: putting the building blocks together Editorial overview Anna Akhmanova and Tim Stearns Current Opinion in Cell Biology 2012, 25:xx–yy 0955-0674/$ – see front matter, # 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.ceb.2012.12.003 Anna Akhmanova Cell Biology, Faculty of Science, Utrecht In considering cell architecture it is important to realize that for cells, as for University, Padualaan 8, 3584 CH Utrecht, buildings, the underpinning for the external shape is provided by a complex The Netherlands internal superstructure. And for cells, this cytoskeletal underpinning must e-mail: [email protected] be highly dynamic to effect the changes in morphology and organization associated with division, growth and differentiation. Cytoskeletal elements Anna Akhmanova is Professor of Cell Biology at Utrecht University, the Netherlands, and a were some of the first components of intracellular structure described by member of EMBO. Her lab uses cell early microscopists in the late 19th century, but it was not until a century biological approaches, in vitro reconstitutions later that the remarkable complexity of the cytoskeleton, in both compo- and high-resolution microscopy to study sition and behavior, has been revealed. Advances in genomics and proteo- molecular mechanisms of microtubule mics have provided us with near-comprehensive lists of the molecular dynamics and vesicle trafficking and their players associated with the various cytoskeletal systems. The challenge contribution to mammalian development and human disease. now is to understand how these components work together, and this is one of the central themes of this issue of Current Opinion in Cell Biology. -
Genetics 211 - 2018 Lecture 3
Genetics 211 - 2018 Lecture 3 High Throughput Sequencing Pt II Gavin Sherlock [email protected] January 23rd 2018 Long “Synthetic Reads” aka Moleculo Genomic DNA Fragment Size Select (10kb) Polish, ligate amplification adaptors ~10 kb DNA Dilute to 500 molecules per well Amplify, fragment, add sequencing adaptors Pool Sequence Separate, based on well barcode Remove barcodes, assemble 10kb fragments Assemble genome from 10kb fragments Synthetic Read Characteristics 10x Genomics • Similar in concept to CPT-Seq from last week’s paper • Idea is to uniquely barcode reads that derive from a long molecule - ~50-100kb • 10x Chromium system automates much of the process for you ~10 HMW gDNA molecules per GEM 10x Barcoded Beads HMW gDNA Oil Benefits of 10x • Correct placement in difficult to align regions: Paralog A Paralog B Benefits of 10x • Correct placement in difficult to align regions: Paralog A Paralog B Benefits of 10x • Correct placement in difficult to align regions: Paralog A Paralog B Benefits of 10x • Correct placement in difficult to align regions: Paralog A Paralog B Benefits of 10x • Correct placement in difficult to align regions: Paralog A Paralog B Benefits of 10x • Haplotype phasing: Benefits of 10x • Haplotype phasing: Benefits of 10x • Haplotype phasing: Benefits of 10x • Haplotype phasing: Using Hi-C data to aid assemblies • Hi-C is a proximity ligation method, aimed at reconstructing the 3 dimensional structure of a genome • Originally developed with the idea of looking at how the genome of an organism for which a good reference exists is physically organized • But, probability of intrachromosomal contacts is much higher than that of interchromosomal contacts. -
EMBO Facts & Figures
excellence in life sciences Reykjavik Helsinki Oslo Stockholm Tallinn EMBO facts & figures & EMBO facts Copenhagen Dublin Amsterdam Berlin Warsaw London Brussels Prague Luxembourg Paris Vienna Bratislava Budapest Bern Ljubljana Zagreb Rome Madrid Ankara Lisbon Athens Jerusalem EMBO facts & figures HIGHLIGHTS CONTACT EMBO & EMBC EMBO Long-Term Fellowships Five Advanced Fellows are selected (page ). Long-Term and Short-Term Fellowships are awarded. The Fellows’ EMBO Young Investigators Meeting is held in Heidelberg in June . EMBO Installation Grants New EMBO Members & EMBO elects new members (page ), selects Young EMBO Women in Science Young Investigators Investigators (page ) and eight Installation Grantees Gerlind Wallon EMBO Scientific Publications (page ). Programme Manager Bernd Pulverer S Maria Leptin Deputy Director Head A EMBO Science Policy Issues report on quotas in academia to assure gender balance. R EMBO Director + + A Conducts workshops on emerging biotechnologies and on H T cognitive genomics. Gives invited talks at US National Academy E IC of Sciences, International Summit on Human Genome Editing, I H 5 D MAN 201 O N Washington, DC.; World Congress on Research Integrity, Rio de A M Janeiro; International Scienti c Advisory Board for the Centre for Eilish Craddock IT 2 015 Mammalian Synthetic Biology, Edinburgh. Personal Assistant to EMBO Fellowships EMBO Scientific Publications EMBO Gold Medal Sarah Teichmann and Ido Amit receive the EMBO Gold the EMBO Director David del Álamo Thomas Lemberger Medal (page ). + Programme Manager Deputy Head EMBO Global Activities India and Singapore sign agreements to become EMBC Associate + + Member States. EMBO Courses & Workshops More than , participants from countries attend 6th scienti c events (page ); participants attend EMBO Laboratory Management Courses (page ); rst online course EMBO Courses & Workshops recorded in collaboration with iBiology. -
PROGRAM and ABSTRACTS for 2020 ANNUAL MEETING of the SOCIETY for GLYCOBIOLOGY November 9–12, 2020 Phoenix, AZ, USA 1017 2020 Sfg Virtual Meeting Preliminary Schedule
Downloaded from https://academic.oup.com/glycob/article/30/12/1016/5948902 by guest on 25 January 2021 PROGRAM AND ABSTRACTS FOR 2020 ANNUAL MEETING OF THE SOCIETY FOR GLYCOBIOLOGY November 9–12, 2020 Phoenix, AZ, USA 1017 2020 SfG Virtual Meeting Preliminary Schedule Mon. Nov 9 (Day 1) TOKYO ROME PACIFIC EASTERN EASTERN SESSION TIME TIME TIME START END TIME TIME 23:30 15:30 6:30 9:30 9:50 Welcome and Introduction - Michael Tiemeyer, CCRC UGA Downloaded from https://academic.oup.com/glycob/article/30/12/1016/5948902 by guest on 25 January 2021 23:30 15:30 6:30 9:50 – 12:36 Session 1: Glycobiology of Normal and Disordered Development | Chair: Kelly Ten-Hagen, NIH/NIDCR 23:50 15:50 6:50 9:50 10:10 KEYNOTE: “POGLUT1 mutations cause myopathy with reduced Notch signaling and α-dystroglycan hypoglycosylation” - Carmen Paradas Lopez, Biomedical Institute Sevilla 0:12 16:12 7:12 10:12 10:24 Poster Talk: “Regulation of Notch signaling by O-glycans in the intestine” – Mohd Nauman, Albert Einstein 0:26 16:26 7:26 10:26 10:38 Poster Talk: “Generation of an unbiased interactome for the tetratricopeptide repeat domain of the O-GlcNAc transferase indicates a role for the enzyme in intellectual disability” – Hannah Stephen, University of Georgia 0:40 16:30 7:30 10:40 10:50 Q&A 10:52 11:12 7:52 10:52 11:12 KEYNOTE: “Aberrations in N-cadherin Processing Drive PMM2-CDG Pathogenesis” - Heather Flanagan-Steet, Greenwood Genetics Center 1:14 11:26 8:14 11:14 11:26 Poster Talk: “Functional analyses of TMTC-type protein O-mannosyltransferases in Drosophila model -
Introduction to Bioinformatics (Elective) – SBB1609
SCHOOL OF BIO AND CHEMICAL ENGINEERING DEPARTMENT OF BIOTECHNOLOGY Unit 1 – Introduction to Bioinformatics (Elective) – SBB1609 1 I HISTORY OF BIOINFORMATICS Bioinformatics is an interdisciplinary field that develops methods and software tools for understanding biologicaldata. As an interdisciplinary field of science, bioinformatics combines computer science, statistics, mathematics, and engineering to analyze and interpret biological data. Bioinformatics has been used for in silico analyses of biological queries using mathematical and statistical techniques. Bioinformatics derives knowledge from computer analysis of biological data. These can consist of the information stored in the genetic code, but also experimental results from various sources, patient statistics, and scientific literature. Research in bioinformatics includes method development for storage, retrieval, and analysis of the data. Bioinformatics is a rapidly developing branch of biology and is highly interdisciplinary, using techniques and concepts from informatics, statistics, mathematics, chemistry, biochemistry, physics, and linguistics. It has many practical applications in different areas of biology and medicine. Bioinformatics: Research, development, or application of computational tools and approaches for expanding the use of biological, medical, behavioral or health data, including those to acquire, store, organize, archive, analyze, or visualize such data. Computational Biology: The development and application of data-analytical and theoretical methods, mathematical modeling and computational simulation techniques to the study of biological, behavioral, and social systems. "Classical" bioinformatics: "The mathematical, statistical and computing methods that aim to solve biological problems using DNA and amino acid sequences and related information.” The National Center for Biotechnology Information (NCBI 2001) defines bioinformatics as: "Bioinformatics is the field of science in which biology, computer science, and information technology merge into a single discipline. -
Representing Glycophenotypes: Semantic Unification of Glycobiology Resources for Disease Discovery
Representing glycophenotypes: semantic unification of glycobiology resources for disease discovery Authors: Jean-Philippe F. Gourdine1,2,3*, Matthew H. Brush1,3, Nicole A. Vasilevsky1,3, Kent Shefchek3,4, Sebastian Köhler3,5, Nicolas Matentzoglu3,6, Monica C. Munoz-Torres3,4, Julie A. McMurry3,4, Xingmin Aaron Zhang3,7, Melissa A. Haendel1,3,4 Affiliations: 1 Oregon Clinical & Translational Research Institute, Oregon Health & Science University, Portland, OR 97239, USA. 2 Oregon Health & Science University Library, Portland, OR 97239, USA. 3 Monarch Initiative, monarchinitiative.org. 4 Linus Pauling institute, Oregon State University, Corvallis, OR, USA. 5 Charité Centrum für Therapieforschung, Charité-Universitätsmedizin Berlin Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin 10117, Germany. 6 European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Cambridge, UK. 7 The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA. Correspondence: [email protected] Abstract While abnormalities related to carbohydrates (glycans) are frequent for patients with rare and undiagnosed diseases as well as in many common diseases, these glycan-related phenotypes (glycophenotypes) are not well represented in knowledge bases (KBs). If glycan related diseases were more robustly represented and curated with glycophenotypes, these could be used for molecular phenotyping to help realize the goals of precision medicine. Diagnosis of rare diseases by computational cross-species comparison of genotype- phenotype data has been facilitated by leveraging ontological representations of clinical phenotypes, using Human Phenotype Ontology (HPO), and model organism ontologies such as Mammalian Phenotype Ontology (MP) in the context of the Monarch Initiative. In this article, we discuss the importance and complexity of glycobiology, and review the structure of glycan-related content from existing KBs and biological ontologies.