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An Open-Sourced Bioinformatic Pipeline for the Processing of Next-Generation Sequencing Derived Nucleotide Reads
bioRxiv preprint doi: https://doi.org/10.1101/2020.04.20.050369; this version posted May 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. An open-sourced bioinformatic pipeline for the processing of Next-Generation Sequencing derived nucleotide reads: Identification and authentication of ancient metagenomic DNA Thomas C. Collin1, *, Konstantina Drosou2, 3, Jeremiah Daniel O’Riordan4, Tengiz Meshveliani5, Ron Pinhasi6, and Robin N. M. Feeney1 1School of Medicine, University College Dublin, Ireland 2Division of Cell Matrix Biology Regenerative Medicine, University of Manchester, United Kingdom 3Manchester Institute of Biotechnology, School of Earth and Environmental Sciences, University of Manchester, United Kingdom [email protected] 5Institute of Paleobiology and Paleoanthropology, National Museum of Georgia, Tbilisi, Georgia 6Department of Evolutionary Anthropology, University of Vienna, Austria *Corresponding Author Abstract The emerging field of ancient metagenomics adds to these Bioinformatic pipelines optimised for the processing and as- processing complexities with the need for additional steps sessment of metagenomic ancient DNA (aDNA) are needed in the separation and authentication of ancient sequences from modern sequences. Currently, there are few pipelines for studies that do not make use of high yielding DNA cap- available for the analysis of ancient metagenomic DNA ture techniques. These bioinformatic pipelines are tradition- 1 4 ally optimised for broad aDNA purposes, are contingent on (aDNA) ≠ The limited number of bioinformatic pipelines selection biases and are associated with high costs. -
Identification of Transcribed Sequences in Arabidopsis Thaliana by Using High-Resolution Genome Tiling Arrays
Identification of transcribed sequences in Arabidopsis thaliana by using high-resolution genome tiling arrays Viktor Stolc*†‡§, Manoj Pratim Samanta‡§¶, Waraporn Tongprasitʈ, Himanshu Sethiʈ, Shoudan Liang*, David C. Nelson**, Adrian Hegeman**, Clark Nelson**, David Rancour**, Sebastian Bednarek**, Eldon L. Ulrich**, Qin Zhao**, Russell L. Wrobel**, Craig S. Newman**, Brian G. Fox**, George N. Phillips, Jr.**, John L. Markley**, and Michael R. Sussman**†† *Genome Research Facility, National Aeronautics and Space Administration Ames Research Center, Moffett Field, CA 94035; †Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, CT 06520; ¶Systemix Institute, Cupertino, CA 94035; ʈEloret Corporation at National Aeronautics and Space Administration Ames Research Center, Moffett Field, CA 94035; and **Center for Eukaryotic Structural Genomics, University of Wisconsin, Madison, WI 53706 Edited by Sidney Altman, Yale University, New Haven, CT, and approved January 28, 2005 (received for review November 4, 2004) Using a maskless photolithography method, we produced DNA Genome-wide tiling arrays can overcome many of the shortcom- oligonucleotide microarrays with probe sequences tiled through- ings of the previous approaches by comprehensively probing out the genome of the plant Arabidopsis thaliana. RNA expression transcription in all regions of the genome. This technology has was determined for the complete nuclear, mitochondrial, and been used successfully on different organisms (5–12). A recent chloroplast genomes by tiling 5 million 36-mer probes. These study on A. thaliana reported measuring transcriptional activities probes were hybridized to labeled mRNA isolated from liquid of four different cell lines by using 25-mer-based tiling arrays that grown T87 cells, an undifferentiated Arabidopsis cell culture line. -
Efficient Storage and Analysis of Genome Data in Relational Database Systems
Efficient Storage and Analysis of Genome Data in Relational Database Systems D I S S E R T A T I O N zur Erlangung des akademischen Grades Doktoringenieur (Dr.-Ing.) angenommen durch die Fakultät für Informatik der Otto-von-Guericke-Universität Magdeburg von M.Sc. Sebastian Dorok geb. am 09.10.1986 in Haldensleben Gutachterinnen/Gutachter Prof. Dr. Gunter Saake Prof. Dr. Jens Teubner Prof. Dr. Ralf Hofestädt Magdeburg, den 27.04.2017 Dorok, Sebastian: Efficient storage and analysis of genome data in relational database systems Dissertation, University of Magdeburg, 2017. Abstract Genome analysis allows researchers to reveal insights about the genetic makeup of living organisms. In the near future, genome analysis will become a key means in the detection and treatment of diseases that are based on variations of the genetic makeup. To this end, powerful variant detection tools were developed or are still under development. However, genome analysis faces a large data deluge. The amounts of data that are produced in a typical genome analysis experiment easily exceed several 100 gigabytes. At the same time, the number of genome analysis experiments increases as the costs drop. Thus, the reliable and efficient management and analysis of large amounts of genome data will likely become a bottleneck, if we do not improve current genome data management and analysis solutions. Currently, genome data management and analysis relies mainly on flat-file based storage and command-line driven analysis tools. Such approaches offer only limited data man- agement capabilities that can hardly cope with future requirements such as annotation management or provenance tracking. -
Pixel-Based Video Coding
UPTEC IT 14 003 Examensarbete 30 hp Mars 2014 Pixel-based video coding Johannes Olsson Sandgren Abstract Pixel-based video coding Johannes Olsson Sandgren Teknisk- naturvetenskaplig fakultet UTH-enheten This paper studies the possibilities of extending the pixel-based compression algorithm LOCO-I, used by the lossless and near lossless image compression standard Besöksadress: JPEG-LS, introduced by the Joint Photographic Experts Group (JPEG) in 1999, to Ångströmlaboratoriet Lägerhyddsvägen 1 video sequences and very low bit-rates. Bitrates below 1 bit per pixel are achieved Hus 4, Plan 0 through skipping signaling when the prediction of a pixels sufficiently good. The pixels to be skipped are implicitly detected by the decoder, minimizing the overhead. Postadress: Different methods of quantization are tested, and the possibility of using vector Box 536 751 21 Uppsala quantization is investigated, by matching pixel sequences against a dynamically generated vector tree. Several different prediction schemes are evaluated, both linear Telefon: and non-linear, with both static and adaptive weights. Maintaining the low 018 – 471 30 03 computational complexity of LOCO-I has been a priority. The results are compared Telefax: to different HEVC implementations with regards to compression speed and ratio. 018 – 471 30 00 Hemsida: http://www.teknat.uu.se/student Handledare: Jonatan Samuelsson Ämnesgranskare: Cris Luengo Examinator: Lars-Åke Nordén ISSN: 1401-5749, UPTEC IT 14 003 Tryckt av: Reprocentralen ITC Sammanfattning på svenska De dominerande videokomprimeringsstandarderna idag, som H.26x, är blockbaserade, och har förhållandevis hög beräkningsmässig komplexitet, framförallt i kodningsfasen. I följande text utforskas möjligheten att utöka en välkänd algoritm, LOCO-I, för pixel- baserad komprimering så att komprimering lägre än 1 bit per pixel blir möjlig. -
Annual Scientific Report 2011 Annual Scientific Report 2011 Designed and Produced by Pickeringhutchins Ltd
European Bioinformatics Institute EMBL-EBI Annual Scientific Report 2011 Annual Scientific Report 2011 Designed and Produced by PickeringHutchins Ltd www.pickeringhutchins.com EMBL member states: Austria, Croatia, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Israel, Italy, Luxembourg, the Netherlands, Norway, Portugal, Spain, Sweden, Switzerland, United Kingdom. Associate member state: Australia EMBL-EBI is a part of the European Molecular Biology Laboratory (EMBL) EMBL-EBI EMBL-EBI EMBL-EBI EMBL-European Bioinformatics Institute Wellcome Trust Genome Campus, Hinxton Cambridge CB10 1SD United Kingdom Tel. +44 (0)1223 494 444, Fax +44 (0)1223 494 468 www.ebi.ac.uk EMBL Heidelberg Meyerhofstraße 1 69117 Heidelberg Germany Tel. +49 (0)6221 3870, Fax +49 (0)6221 387 8306 www.embl.org [email protected] EMBL Grenoble 6, rue Jules Horowitz, BP181 38042 Grenoble, Cedex 9 France Tel. +33 (0)476 20 7269, Fax +33 (0)476 20 2199 EMBL Hamburg c/o DESY Notkestraße 85 22603 Hamburg Germany Tel. +49 (0)4089 902 110, Fax +49 (0)4089 902 149 EMBL Monterotondo Adriano Buzzati-Traverso Campus Via Ramarini, 32 00015 Monterotondo (Rome) Italy Tel. +39 (0)6900 91402, Fax +39 (0)6900 91406 © 2012 EMBL-European Bioinformatics Institute All texts written by EBI-EMBL Group and Team Leaders. This publication was produced by the EBI’s Outreach and Training Programme. Contents Introduction Foreword 2 Major Achievements 2011 4 Services Rolf Apweiler and Ewan Birney: Protein and nucleotide data 10 Guy Cochrane: The European Nucleotide Archive 14 Paul Flicek: -
Vosoughi, Mbw2, Cavallar}@Rice.Edu
Baseband Signal Compression in Wireless Base Stations Aida Vosoughi, Michael Wu, and Joseph R. Cavallaro {vosoughi, mbw2, cavallar}@rice.edu Unused Significant USBR code Motivation 010, 5(=101) Experimental Setup and Results Bit Removal binary code 01011001 11001 Using WARP hardware and WARPLab framework for over-the- With new wireless standards, base stations require 01010000 10000 Used before in air experiments: (a) Downlink, (b) Uplink greater data rates over the serial data link between base 01000111 00111 Network on chip serial station processor and (remote) RF unit. 01001100 01100 link compression 10011100 1001, 4(=100) This link is especially important in: 10010011 1100 10011010 0011 • Distributed Antenna Systems 10010001 1010 • Cooperating base stations …. 0001 • Cloud-based Radio Access Networks … We propose to use a differencing step before compressing with Baseband signals: each of the above lossless schemes. • Usually oversampled and correlated Compression Ratio Results: • Represented with extra bit resolution Proposed Lossy Compression Lossless Schemes: Lossy Scheme: LSB Removal/Quantization: Algorithm TX RX DQPSK 16-QAM Compression can decrease hardware complexity and cost. The number of LSBs that can [1] 1.51 1.07 TX 4 2.3 be removed without causing USBR 1.41 1.17 RX 3.5 2 distortion depends on the Elias-gamma + 1.40 0.84 Introduction and Related Work Adaptive AC modulation type. Adaptive AC 1.26 0.95 Base station architecture with compression/decompression: Elias-gamma 1.22 0.72 With higher size constellations, more bit -
Compressing Integers for Fast File Access
Compressing Integers for Fast File Access Hugh E. Williams and Justin Zobel Department of Computer Science, RMIT University GPO Box 2476V, Melbourne 3001, Australia Email: hugh,jz @cs.rmit.edu.au { } Fast access to files of integers is crucial for the efficient resolution of queries to databases. Integers are the basis of indexes used to resolve queries, for exam- ple, in large internet search systems and numeric data forms a large part of most databases. Disk access costs can be reduced by compression, if the cost of retriev- ing a compressed representation from disk and the CPU cost of decoding such a representation is less than that of retrieving uncompressed data. In this paper we show experimentally that, for large or small collections, storing integers in a com- pressed format reduces the time required for either sequential stream access or random access. We compare different approaches to compressing integers, includ- ing the Elias gamma and delta codes, Golomb coding, and a variable-byte integer scheme. As a conclusion, we recommend that, for fast access to integers, files be stored compressed. Keywords: Integer compression, variable-bit coding, variable-byte coding, fast file access, scientific and numeric databases. 1. INTRODUCTION codes [2], and parameterised Golomb codes [3]; second, we evaluate byte-wise storage using standard four-byte Many data processing applications depend on efficient integers and a variable-byte scheme. access to files of integers. For example, integer data is We have found in our experiments that coding us- prevalent in scientific and financial databases, and the ing a tailored integer compression scheme can allow indexes to databases can consist of large sequences of retrieval to be up to twice as fast than with integers integer record identifiers. -
Lampiran a Listing Program
LAMPIRAN A LISTING PROGRAM Private Sub Command3_Click() If UBound(OriginalArray) = 0 Then Exit Sub End MsgBox "There is nothing to End If compress/Decompress" End Sub Else Exit Sub LastCoder = WichCompressor End If Private Sub compress_Click() End If If AutoDecodeIsOn = False Then m1.Visible = True Call Copy_Orig2Work decompress = True m2.Visible = True LastDeCoded = decompress If CompDecomp = 0 Then Exit Sub End Sub If JustLoaded = True Then If CompDecomp = 1 Then decompress = False JustLoaded = False Else Private Sub d1_Click() ReDim UsedCodecs(0) decompress = True CompDecomp = 2 End If End If Dim wktmulai As Single compression.MousePointer = If decompress = True Then MousePointerConstants.vbHourglass Dim decompress As Boolean LastUsed = wktmulai = Timer Dim Dummy As Boolean UsedCodecs(UBound(UsedCodecs)) Call DeCompress_arithmetic_Dynamic(hasil) Dim StTime As Double If JustLoaded = True Then LastUsed = 0 Label12.Caption = Timer - wktmulai & " detik" Dim Text As String If WichCompressor <> LastUsed Then compression.MousePointer = Dim LastUsed As Integer Text = "This is not compressed with ." & MousePointerConstants.vbDefault Chr(13) Call Show_Statistics(False, hasil) MsgBox Text A-1 Call afterContent(hasil) If AutoDecodeIsOn = False Then End If compression.save.Visible = True decompress = True Call Copy_Orig2Work d1.Visible = False If CompDecomp = 0 Then Exit Sub LastDeCoded = decompress d2.Visible = False If CompDecomp = 1 Then decompress = False If JustLoaded = True Then End Sub Else JustLoaded = False decompress = True ReDim UsedCodecs(0) -
Entropy Coding and Different Coding Techniques
Journal of Network Communications and Emerging Technologies (JNCET) www.jncet.org Volume 6, Issue 5, May (2016) Entropy Coding and Different Coding Techniques Sandeep Kaur Asst. Prof. in CSE Dept, CGC Landran, Mohali Sukhjeet Singh Asst. Prof. in CS Dept, TSGGSK College, Amritsar. Abstract – In today’s digital world information exchange is been 2. CODING TECHNIQUES held electronically. So there arises a need for secure transmission of the data. Besides security there are several other factors such 1. Huffman Coding- as transfer speed, cost, errors transmission etc. that plays a vital In computer science and information theory, a Huffman code role in the transmission process. The need for an efficient technique for compression of Images ever increasing because the is a particular type of optimal prefix code that is commonly raw images need large amounts of disk space seems to be a big used for lossless data compression. disadvantage during transmission & storage. This paper provide 1.1 Basic principles of Huffman Coding- a basic introduction about entropy encoding and different coding techniques. It also give comparison between various coding Huffman coding is a popular lossless Variable Length Coding techniques. (VLC) scheme, based on the following principles: (a) Shorter Index Terms – Huffman coding, DEFLATE, VLC, UTF-8, code words are assigned to more probable symbols and longer Golomb coding. code words are assigned to less probable symbols. 1. INTRODUCTION (b) No code word of a symbol is a prefix of another code word. This makes Huffman coding uniquely decodable. 1.1 Entropy Encoding (c) Every source symbol must have a unique code word In information theory an entropy encoding is a lossless data assigned to it. -
STUDIES on GOPALA-HEMACHANDRA CODES and THEIR APPLICATIONS. by Logan Childers December, 2020
STUDIES ON GOPALA-HEMACHANDRA CODES AND THEIR APPLICATIONS. by Logan Childers December, 2020 Director of Thesis: Krishnan Gopalakrishnan, PhD Major Department: Computer Science Gopala-Hemachandra codes are a variation of the Fibonacci universal code and have ap- plications in data compression and cryptography. We study a specific parameterization of Gopala-Hemachandra codes and present several results pertaining to these codes. We show that GHa(n) always exists for n ≥ 1 when −2 ≥ a ≥ −4, meaning that these are universal codes. We develop two new algorithms to determine whether a GH code exists for a given a and n, and to construct them if they exist. We also prove that when a = −(4 + k) where k ≥ 1, that there are at most k consecutive integers for which GH codes do not exist. In 2014, Nalli and Ozyilmaz proposed a stream cipher based on GH codes. We show that this cipher is insecure and provide experimental results on the performance of our program that cracks this cipher. STUDIES ON GOPALA-HEMACHANDRA CODES AND THEIR APPLICATIONS. A Thesis Presented to The Faculty of the Department of Computer Science East Carolina University In Partial Fulfillment of the Requirements for the Degree Master of Science in Computer Science by Logan Childers December, 2020 Copyright Logan Childers, 2020 STUDIES ON GOPALA-HEMACHANDRA CODES AND THEIR APPLICATIONS. by Logan Childers APPROVED BY: DIRECTOR OF THESIS: Krishnan Gopalakrishnan, PhD COMMITTEE MEMBER: Venkat Gudivada, PhD COMMITTEE MEMBER: Karl Abrahamson, PhD CHAIR OF THE DEPARTMENT OF COMPUTER SCIENCE: Venkat Gudivada, PhD DEAN OF THE GRADUATE SCHOOL: Paul J. Gemperline, PhD Table of Contents LIST OF TABLES .................................. -
Mp3
<d.w.o> mp3 book: Table of Contents <david.weekly.org> January 4 2002 mp3 book Table of Contents Table of Contents auf deutsch en español {en français} Chapter 0: Introduction <d.w.o> ● What's In This Book about ● Who This Book Is For ● How To Read This Book books Chapter 1: The Hype code codecs ● What Is Internet Audio and Why Do People Use It? mp3 book ● Some Thoughts on the New Economy ● A Brief History of Internet Audio news ❍ Bell Labs, 1957 - Computer Music Is Born pictures ❍ Compression in Movies & Radio - MP3 is Invented! poems ❍ The Net Circa 1996: RealAudio, MIDI, and .AU projects ● The MP3 Explosion updates ❍ 1996 - The Release ❍ 1997 - The Early Adopters writings ❍ 1998 - The Explosion video ❍ sidebar - The MP3 Summit get my updates ❍ 1999 - Commercial Acceptance ● Why Did It Happen? ❍ Hardware ❍ Open Source -> Free, Convenient Software ❍ Standards ❍ Memes: Idea Viruses ● Conclusion page source http://david.weekly.org/mp3book/toc.php3 (1 of 6) [1/4/2002 10:53:06 AM] <d.w.o> mp3 book: Table of Contents Chapter 2: The Guts of Music Technology ● Digital Audio Basics ● Understanding Fourier ● The Biology of Hearing ● Psychoacoustic Masking ❍ Normal Masking ❍ Tone Masking ❍ Noise Masking ● Critical Bands and Prioritization ● Fixed-Point Quantization ● Conclusion Chapter 3: Modern Audio Codecs ● MPEG Evolves ❍ MP2 ❍ MP3 ❍ AAC / MPEG-4 ● Other Internet Audio Codecs ❍ AC-3 / Dolbynet ❍ RealAudio G2 ❍ VQF ❍ QDesign Music Codec 2 ❍ EPAC ● Summary Chapter 4: The New Pipeline: The New Way To Produce, Distribute, and Listen to Music ● Digital -
Reducing Memory Access Latencies Using Data Compression in Sparse, Iterative Linear Solvers
College of Saint Benedict and Saint John's University DigitalCommons@CSB/SJU All College Thesis Program, 2016-2019 Honors Program Spring 2019 Reducing Memory Access Latencies using Data Compression in Sparse, Iterative Linear Solvers Neil Lindquist [email protected] Follow this and additional works at: https://digitalcommons.csbsju.edu/honors_thesis Part of the Numerical Analysis and Computation Commons, and the Numerical Analysis and Scientific Computing Commons Recommended Citation Lindquist, Neil, "Reducing Memory Access Latencies using Data Compression in Sparse, Iterative Linear Solvers" (2019). All College Thesis Program, 2016-2019. 63. https://digitalcommons.csbsju.edu/honors_thesis/63 Copyright 2019 Neil Lindquist Reducing Memory Access Latencies using Data Compression in Sparse, Iterative Linear Solvers An All-College Thesis College of Saint Benedict/Saint John's University by Neil Lindquist April 2019 Project Title: Reducing Memory Access Latencies using Data Compression in Sparse, Iterative Linear Solvers Approved by: Mike Heroux Scientist in Residence Robert Hesse Associate Professor of Mathematics Jeremy Iverson Assistant Professor of Computer Science Bret Benesh Chair, Department of Mathematics Imad Rahal Chair, Department of Computer Science Director, All College Thesis Program i Abstract Solving large, sparse systems of linear equations plays a significant role in cer- tain scientific computations, such as approximating the solutions of partial dif- ferential equations. However, solvers for these types of problems usually spend most of their time fetching data from main memory. In an effort to improve the performance of these solvers, this work explores using data compression to reduce the amount of data that needs to be fetched from main memory. Some compression methods were found that improve the performance of the solver and problem found in the HPCG benchmark, with an increase in floating point operations per second of up to 84%.