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Introduction to Unix
Introduction to Unix Rob Funk <[email protected]> University Technology Services Workstation Support http://wks.uts.ohio-state.edu/ University Technology Services Course Objectives • basic background in Unix structure • knowledge of getting started • directory navigation and control • file maintenance and display commands • shells • Unix features • text processing University Technology Services Course Objectives Useful commands • working with files • system resources • printing • vi editor University Technology Services In the Introduction to UNIX document 3 • shell programming • Unix command summary tables • short Unix bibliography (also see web site) We will not, however, be covering these topics in the lecture. Numbers on slides indicate page number in book. University Technology Services History of Unix 7–8 1960s multics project (MIT, GE, AT&T) 1970s AT&T Bell Labs 1970s/80s UC Berkeley 1980s DOS imitated many Unix ideas Commercial Unix fragmentation GNU Project 1990s Linux now Unix is widespread and available from many sources, both free and commercial University Technology Services Unix Systems 7–8 SunOS/Solaris Sun Microsystems Digital Unix (Tru64) Digital/Compaq HP-UX Hewlett Packard Irix SGI UNICOS Cray NetBSD, FreeBSD UC Berkeley / the Net Linux Linus Torvalds / the Net University Technology Services Unix Philosophy • Multiuser / Multitasking • Toolbox approach • Flexibility / Freedom • Conciseness • Everything is a file • File system has places, processes have life • Designed by programmers for programmers University Technology Services -
The Encodedb Portal: Simplified Access to ENCODE Consortium Data Laura L
Downloaded from genome.cshlp.org on September 30, 2021 - Published by Cold Spring Harbor Laboratory Press Resource The ENCODEdb portal: Simplified access to ENCODE Consortium data Laura L. Elnitski, Prachi Shah, R. Travis Moreland, Lowell Umayam, Tyra G. Wolfsberg, and Andreas D. Baxevanis1 Genome Technology Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland 20892, USA The Encyclopedia of DNA Elements (ENCODE) project aims to identify and characterize all functional elements in a representative chromosomal sample comprising 1% of the human genome. Data generated by members of The ENCODE Project Consortium are housed in a number of public databases, such as the UCSC Genome Browser, NCBI’s Gene Expression Omnibus (GEO), and EBI’s ArrayExpress. As such, it is often difficult for biologists to gather all of the ENCODE data from a particular genomic region of interest and integrate them with relevant information found in other public databases. The ENCODEdb portal was developed to address this problem. ENCODEdb provides a unified, single point-of-access to data generated by the ENCODE Consortium, as well as to data from other source databases that lie within ENCODE regions; this provides the user a complete view of all known data in a particular region of interest. ENCODEdb Genomic Context searches allow for the retrieval of information on functional elements annotated within ENCODE regions, including mRNA, EST, and STS sequences; single nucleotide polymorphisms, and UniGene clusters. Information is also retrieved from GEO, OMIM, and major genome sequence browsers. ENCODEdb Consortium Data searches allow users to perform compound queries on array-based ENCODE data available both from GEO and from the UCSC Genome Browser. -
Differential Gene Expression Profiling in Bed Bug (Cimex Lectularius L.) Fed on Ibuprofen and Caffeine in Reconstituted Human Blood Ralph B
Herpe y & tolo og g l y: o C th i u Narain et al., Entomol Ornithol Herpetol 2015, 4:3 n r r r e O n , t y R g DOI: 10.4172/2161-0983.1000160 e o l s o e a m r o c t h n E Entomology, Ornithology & Herpetology ISSN: 2161-0983 ResearchResearch Article Article OpenOpen Access Access Differential Gene Expression Profiling in Bed Bug (Cimex Lectularius L.) Fed on Ibuprofen and Caffeine in Reconstituted Human Blood Ralph B. Narain, Haichuan Wang and Shripat T. Kamble* Department of Entomology, University of Nebraska, Lincoln, NE 68583, USA Abstract The recent resurgence of the common bed bug (Cimex lectularius L.) infestations worldwide has created a need for renewed research on biology, behavior, population genetics and management practices. Humans serve as exclusive hosts to bed bugs in urban environments. Since a majority of humans consume Ibuprofen (as pain medication) and caffeine (in coffee and other soft drinks) so bug bugs subsequently acquire Ibuprofen and caffeine through blood feeding. However, the effect of these chemicals at genetic level in bed bug is unknown. Therefore, this research was conducted to determine differential gene expression in bed bugs using RNA-Seq analysis at dosages of 200 ppm Ibuprofen and 40 ppm caffeine incorporated into reconstituted human blood and compared against the control. Total RNA was extracted from a single bed bug per replication per treatment and sequenced. Read counts obtained were analyzed using Bioconductor software programs to identify differentially expressed genes, which were then searched against the non-redundant (nr) protein database of National Center for Biotechnology Information (NCBI). -
07 07 Unixintropart2 Lucio Week 3
Unix Basics Command line tools Daniel Lucio Overview • Where to use it? • Command syntax • What are commands? • Where to get help? • Standard streams(stdin, stdout, stderr) • Pipelines (Power of combining commands) • Redirection • More Information Introduction to Unix Where to use it? • Login to a Unix system like ’kraken’ or any other NICS/ UT/XSEDE resource. • Download and boot from a Linux LiveCD either from a CD/DVD or USB drive. • http://www.puppylinux.com/ • http://www.knopper.net/knoppix/index-en.html • http://www.ubuntu.com/ Introduction to Unix Where to use it? • Install Cygwin: a collection of tools which provide a Linux look and feel environment for Windows. • http://cygwin.com/index.html • https://newton.utk.edu/bin/view/Main/Workshop0InstallingCygwin • Online terminal emulator • http://bellard.org/jslinux/ • http://cb.vu/ • http://simpleshell.com/ Introduction to Unix Command syntax $ command [<options>] [<file> | <argument> ...] Example: cp [-R [-H | -L | -P]] [-fi | -n] [-apvX] source_file target_file Introduction to Unix What are commands? • An executable program (date) • A command built into the shell itself (cd) • A shell program/function • An alias Introduction to Unix Bash commands (Linux) alias! crontab! false! if! mknod! ram! strace! unshar! apropos! csplit! fdformat! ifconfig! more! rcp! su! until! apt-get! cut! fdisk! ifdown! mount! read! sudo! uptime! aptitude! date! fg! ifup! mtools! readarray! sum! useradd! aspell! dc! fgrep! import! mtr! readonly! suspend! userdel! awk! dd! file! install! mv! reboot! symlink! -
Roof Rail Airbag Folding Technique in LS-Prepost ® Using Dynfold Option
14th International LS-DYNA Users Conference Session: Modeling Roof Rail Airbag Folding Technique in LS-PrePost® Using DynFold Option Vijay Chidamber Deshpande GM India – Tech Center Wenyu Lian General Motors Company, Warren Tech Center Amit Nair Livermore Software Technology Corporation Abstract A requirement to reduce vehicle development timelines is making engineers strive to limit lead times in analytical simulations. Airbags play a crucial role in the passive safety crash analysis. Hence they need to be designed, developed and folded for CAE applications within a short span of time. Therefore a method/procedure to fold the airbag efficiently is of utmost importance. In this study the RRAB (Roof Rail AirBag) folding is carried out in LS-PrePost® by DynFold option. It is purely a simulation based folding technique, which can be solved in LS-DYNA®. In this paper we discuss in detail the RRAB folding process and tools/methods to make this effective. The objective here is to fold the RRAB to include modifications in the RRAB, efficiently and realistically using common analysis tools ( LS-DYNA & LS-PrePost), without exploring a third party tool , thus reducing the turnaround time. Introduction To meet the regulatory and consumer metrics requirements, multiple design iterations are required using advanced CAE simulation models for the various safety load cases. One of the components that requires frequent changes is the roof rail airbag (RRAB). After any changes to the geometry or pattern in the airbag have been made, the airbag needs to be folded back to its design position. Airbag folding is available in a few pre-processors; however, there are some folding patterns that are difficult to be folded using the pre-processor folding modules. -
Quantification of Experimentally Induced Nucleotide Conversions in High-Throughput Sequencing Datasets Tobias Neumann1* , Veronika A
Neumann et al. BMC Bioinformatics (2019) 20:258 https://doi.org/10.1186/s12859-019-2849-7 RESEARCH ARTICLE Open Access Quantification of experimentally induced nucleotide conversions in high-throughput sequencing datasets Tobias Neumann1* , Veronika A. Herzog2, Matthias Muhar1, Arndt von Haeseler3,4, Johannes Zuber1,5, Stefan L. Ameres2 and Philipp Rescheneder3* Abstract Background: Methods to read out naturally occurring or experimentally introduced nucleic acid modifications are emerging as powerful tools to study dynamic cellular processes. The recovery, quantification and interpretation of such events in high-throughput sequencing datasets demands specialized bioinformatics approaches. Results: Here, we present Digital Unmasking of Nucleotide conversions in K-mers (DUNK), a data analysis pipeline enabling the quantification of nucleotide conversions in high-throughput sequencing datasets. We demonstrate using experimentally generated and simulated datasets that DUNK allows constant mapping rates irrespective of nucleotide-conversion rates, promotes the recovery of multimapping reads and employs Single Nucleotide Polymorphism (SNP) masking to uncouple true SNPs from nucleotide conversions to facilitate a robust and sensitive quantification of nucleotide-conversions. As a first application, we implement this strategy as SLAM-DUNK for the analysis of SLAMseq profiles, in which 4-thiouridine-labeled transcripts are detected based on T > C conversions. SLAM-DUNK provides both raw counts of nucleotide-conversion containing reads as well as a base-content and read coverage normalized approach for estimating the fractions of labeled transcripts as readout. Conclusion: Beyond providing a readily accessible tool for analyzing SLAMseq and related time-resolved RNA sequencing methods (TimeLapse-seq, TUC-seq), DUNK establishes a broadly applicable strategy for quantifying nucleotide conversions. -
Unix Programmer's Manual
There is no warranty of merchantability nor any warranty of fitness for a particu!ar purpose nor any other warranty, either expressed or imp!ied, a’s to the accuracy of the enclosed m~=:crials or a~ Io ~helr ,~.ui~::~::.j!it’/ for ~ny p~rficu~ar pur~.~o~e. ~".-~--, ....-.re: " n~ I T~ ~hone Laaorator es 8ssumg$ no rO, p::::nS,-,,.:~:y ~or their use by the recipient. Furln=,, [: ’ La:::.c:,:e?o:,os ~:’urnes no ob~ja~tjon ~o furnish 6ny a~o,~,,..n~e at ~ny k:nd v,,hetsoever, or to furnish any additional jnformstjcn or documenta’tjon. UNIX PROGRAMMER’S MANUAL F~ifth ~ K. Thompson D. M. Ritchie June, 1974 Copyright:.©d972, 1973, 1974 Bell Telephone:Laboratories, Incorporated Copyright © 1972, 1973, 1974 Bell Telephone Laboratories, Incorporated This manual was set by a Graphic Systems photo- typesetter driven by the troff formatting program operating under the UNIX system. The text of the manual was prepared using the ed text editor. PREFACE to the Fifth Edition . The number of UNIX installations is now above 50, and many more are expected. None of these has exactly the same complement of hardware or software. Therefore, at any particular installa- tion, it is quite possible that this manual will give inappropriate information. The authors are grateful to L. L. Cherry, L. A. Dimino, R. C. Haight, S. C. Johnson, B. W. Ker- nighan, M. E. Lesk, and E. N. Pinson for their contributions to the system software, and to L. E. McMahon for software and for his contributions to this manual. -
Counting Mountain-Valley Assignments for Flat Folds
Counting Mountain-Valley Assignments for Flat Folds∗ Thomas Hull Department of Mathematics Merrimack College North Andover, MA 01845 Abstract We develop a combinatorial model of paperfolding for the pur- poses of enumeration. A planar embedding of a graph is called a crease pattern if it represents the crease lines needed to fold a piece of paper into something. A flat fold is a crease pattern which lies flat when folded, i.e. can be pressed in a book without crumpling. Given a crease pattern C =(V,E), a mountain-valley (MV) assignment is a function f : E → {M,V} which indicates which crease lines are con- vex and which are concave, respectively. A MV assignment is valid if it doesn’t force the paper to self-intersect when folded. We examine the problem of counting the number of valid MV assignments for a given crease pattern. In particular we develop recursive functions that count the number of valid MV assignments for flat vertex folds, crease patterns with only one vertex in the interior of the paper. We also provide examples, especially those of Justin, that illustrate the difficulty of the general multivertex case. 1 Introduction The study of origami, the art and process of paperfolding, includes many arXiv:1410.5022v1 [math.CO] 19 Oct 2014 interesting geometric and combinatorial problems. (See [3] and [6] for more background.) In origami mathematics, a fold refers to any folded paper object, independent of the number of folds done in sequence. The crease pattern of a fold is a planar embedding of a graph which represents the creases that are used in the final folded object. -
Produktinformation LS 373, LS
Product Information LS 373 LS 383 Incremental Linear Encoders 04/2021 LS 300 series (46) 88 K 1±0.3 80 CL 3 74 32 13 5.3 5 0.05/13 A A K 12 18 18 ±5 P M4 4 P ±5 0.3 5.5 3 5.5 ± 0.1/80 F K 0 0.1 F K K 1) 2) 0.03 Specifications LS 383 LS 373 Measuring standard Glass scale –6 –1 ML+105 Coefficient of linear expansion Þtherm 8 · 10 K 5.5 (ML+94) ±0.4 K Accuracy grade ±5 µm 40±20 0.1 F K 65±20 P P 6 Measuring length ML* 70 120 170 220 270 320 370 420 470 520 570 620 670 720 in mm 770 820 870 920 970 1020 1140 1240 16.3 (26.3) Reference marks LS 3x3: 1 reference mark in the middle 4.8 LS 3x3 C: distance-coded SW8 4 0.1/80 F 4 0±2 4.5 K The LS 477 and LS 487 are available as 4.3 SW8 12 56 Interface C replacement devices on short notice. 1 VPP TTL ML Signal period 20 µm Cable with metal armor: LS 383, LS 373 PUR cable: LS 477, LS 487 Integrated interpolation – 1-fold 5-fold 10-fold 20-fold Measuring step – 5 µm 1 µm 0.5 µm 0.25 µm 4 8.5 12 56 7.3 Supply voltage 5 V ±0.25 V/< 150 mA F = Machine guideway 88 CL 97.5 Without load ML = Measuring length 115 P = Measuring point for mounting = 0 to ML Electrical connection PUR cable and PUR cable with metal armor; cable outlet to the right on the mounting block C = Cable CL = Cable length 127 Cable length 3 m, 6 m K = Required mating dimensions PUR cable with metal armor: LS 477, LS 487 Connecting element 15-pin D-sub connector (male) 15-pin D-sub connector (male) 15-pin D-sub connector (female) 9-pin D-sub connector (male) 12-pin M23 connector (male) 12-pin M23 connector (male) Traversing speed 60 m/min Required moving force 5 N Vibration 55 Hz to 2000 Hz 100 m/s2 Shock 6 ms 200 m/s2 Operating temperature 0 °C to 50 °C Protection IEC 60529 IP53 Mass without cable 0.3 kg + 0.57 kg/m of measuring length * Please select when ordering 1) The LS 487 is also available through the HEIDENHAIN Service department on short notice. -
Penguin: a Tool for Predicting Pseudouridine Sites in Direct RNA Nanopore Sequencing Data
bioRxiv preprint doi: https://doi.org/10.1101/2021.03.31.437901; this version posted June 9, 2021. 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-NC 4.0 International license. Penguin: A Tool for Predicting Pseudouridine Sites in Direct RNA Nanopore Sequencing Data Doaa Hassan1,4, Daniel Acevedo1,5, Swapna Vidhur Daulatabad1, Quoseena Mir1, Sarath Chandra Janga1,2,3 1. Department of BioHealth Informatics, School of Informatics and Computing, Indiana University Purdue University, 535 West Michigan Street, Indianapolis, Indiana 46202 2. Department of Medical and Molecular Genetics, Indiana University School of Medicine, Medical Research and Library Building, 975 West Walnut Street, Indianapolis, Indiana, 46202 3. Centre for Computational Biology and Bioinformatics, Indiana University School of Medicine, 5021 Health Information and Translational Sciences (HITS), 410 West 10th Street, Indianapolis, Indiana, 46202 4. Computers and Systems Department, National Telecommunication Institute, Cairo, Egypt. 5. Computer Science Department, University of Texas Rio Grande Valley Keywords: RNA modifications, Pseudouridine, Nanopore *Correspondence should be addressed to: Sarath Chandra Janga ([email protected]) Informatics and Communications Technology Complex, IT475H 535 West Michigan Street Indianapolis, IN 46202 317 278 4147 bioRxiv preprint doi: https://doi.org/10.1101/2021.03.31.437901; this version posted June 9, 2021. 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-NC 4.0 International license. -
Gnu Coreutils Core GNU Utilities for Version 6.9, 22 March 2007
gnu Coreutils Core GNU utilities for version 6.9, 22 March 2007 David MacKenzie et al. This manual documents version 6.9 of the gnu core utilities, including the standard pro- grams for text and file manipulation. Copyright c 1994, 1995, 1996, 2000, 2001, 2002, 2003, 2004, 2005, 2006 Free Software Foundation, Inc. Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or any later version published by the Free Software Foundation; with no Invariant Sections, with no Front-Cover Texts, and with no Back-Cover Texts. A copy of the license is included in the section entitled \GNU Free Documentation License". Chapter 1: Introduction 1 1 Introduction This manual is a work in progress: many sections make no attempt to explain basic concepts in a way suitable for novices. Thus, if you are interested, please get involved in improving this manual. The entire gnu community will benefit. The gnu utilities documented here are mostly compatible with the POSIX standard. Please report bugs to [email protected]. Remember to include the version number, machine architecture, input files, and any other information needed to reproduce the bug: your input, what you expected, what you got, and why it is wrong. Diffs are welcome, but please include a description of the problem as well, since this is sometimes difficult to infer. See section \Bugs" in Using and Porting GNU CC. This manual was originally derived from the Unix man pages in the distributions, which were written by David MacKenzie and updated by Jim Meyering. -
Reference Genomes and Common File Formats Overview
Reference genomes and common file formats Overview ● Reference genomes and GRC ● Fasta and FastQ (unaligned sequences) ● SAM/BAM (aligned sequences) ● Summarized genomic features ○ BED (genomic intervals) ○ GFF/GTF (gene annotation) ○ Wiggle files, BEDgraphs, BigWigs (genomic scores) Why do we need to know about reference genomes? ● Allows for genes and genomic features to be evaluated in their genomic context. ○ Gene A is close to gene B ○ Gene A and gene B are within feature C ● Can be used to align shallow targeted high-throughput sequencing to a pre-built map of an organism Genome Reference Consortium (GRC) ● Most model organism reference genomes are being regularly updated ● Reference genomes consist of a mixture of known chromosomes and unplaced contigs called as Genome Reference Assembly ● Genome Reference Consortium: ○ A collaboration of institutes which curate and maintain the reference genomes of 4 model organisms: ■ Human - GRCh38.p9 (26 Sept 2016) ■ Mouse - GRCm38.p5 (29 June 2016) ■ Zebrafish - GRCz10 (12 Sept 2014) ■ Chicken - Gallus_gallus-5.0 (16 Dec 2015) ○ Latest human assembly is GRCh38, patches add information to the assembly without disrupting the chromosome coordinates ● Other model organisms are maintained separately, like: ○ Drosophila - Berkeley Drosophila Genome Project Overview ● Reference genomes and GRC ● Fasta and FastQ (unaligned sequences) ● SAM/BAM (aligned sequences) ● Summarized genomic features ○ BED (genomic intervals) ○ GFF/GTF (gene annotation) ○ Wiggle files, BEDgraphs, BigWigs (genomic scores) The