User Manual for ReadSim V0.7
Contents
1. 8 ReadSim_linux_0_7 rpm 3 ReadSim macos O T sit 3 ReadSim_unix_0_7 sh 3 ReadSim_windows_0_7 exe 3 Sanger 4 Save As 8 Save Options 8 Select All 9 shotgun sequencing 4 source sequence 4 target sequence 4 Unix 3 4 Windows 3 4 132. entrant after pressing any of these three buttons requires the the program is closed and then re launched to get back to the option dialog 9 Console Window The command line version ReadSim cmdline writes all messages to the shell in which it was launched The other version ReadSim opens a Console window and writes all messages to it This window has the usual text related menu items The File menu contains the following file related items e The File Save As item saves the contents of the console window to a file The File gt Print item prints the contents of the console window e The File Close item quits the program The Edit menu contains the usual edit related items e The Edit Cut item is used to cut text in the console window e The Edit Copy item is used to copy text e The Edit gt Paste item is used to paste text e The Edit gt Select All item is used to select the whole text e The Edit Clear item is used to clear the console window 10 File Formats The program reads and writes sequence data in FastA format 10 1 Input file ReadSim requires that the input file contains a single FastA record of DNA sequence 10 2 Output file The output is written in FastA format one record per read The header line of each record is structured as follows gt lt read id gt beg lt start gt length lt length gt lt forward reverse gt lt original FastA header gt or alternatively if a mate pair exists gt
3. pairs and chimeric pairs are produced Typical values for Sanger sequencing is a mean read length of 700 bp and 7 fold coverage and insert sizes of 2kb 10kb 50kb or 150kb The options provided for this sequencing model follow those provided by the program celsim 6 6 The 454 Sequencing Model Here we describe the 454 sequencing model Recently 454 Life Sciences announced a new highly parallel sequencing system with significantly higher throughput than achievable with previous methods see 3 It uses emulsion based PCR amplification of a large number of DNA fragments and high throughput parallel pyro sequencing The system is reportedly able to sequence 25 million bases within four hours Cloning of the target DNA fragments is not necessary and the method is much cheaper per base than other existing methods Drawbacks of the method are shorter read lengths of about 100 bases in contrast to 800 bases using Sanger sequencing and a higher error rate Further sequencing of paired end reads is not yet possible The 454 sequencing approach promises to be very suitable for metagenomics projects as demon strated by 7 To develop and calibrate software to analyze the data arising in this context we have developed a program ReadSim that simulates the sequencing process by generating a collection of reads from a given target genome and introducing sequencing errors into the reads based on error models reflecting the properties of the sequ
4. A and then determining their sequence using fluorescent didesoxynucleotides for termination and capillary electrophoresis see 4 5 In paired end shotgun sequencing both ends of an insert are read see 8 New sequencing technology based on pyro sequencing as recently introduced by 454 Life Sciences 2 promises to be ideally suited for metagenomic projects that seek to determine the diversity of organisms in a given environment To develop and calibrate software to process the arising data a sequencing simulator is required that samples reads from a given known target sequence under an error model that reflects the performance of the sequencing technology Additionally to simplify the comparison of pyro sequencing and Sanger sequencing it is desirable that both approaches can be simulated by a single program The aim of ReadSim is to simulate the process of collecting reads from a target genome The current version of the program implements two different sequencing models The Sanger model simulates sequencing using Sanger sequencing The simulation strategy and error model is modeled on the celsim program 6 The 454 model simulates sequencing using the 454 approach as described in 2 The characteristics of this model differ substantially from the Sanger model e g the collected reads are much shorter and mate pairs are currently not available but can be simulated using this software The most important difference is that sequencing er
5. User Manual for ReadSim V0 7 Ramona Schmid Daniel H Huson May 4 2006 Contents Contents 1 Introduction 2 Getting Started 3 Obtaining and Installing the Program 4 Program Overview 5 The Sanger Sequencing Model 6 The 454 Sequencing Model 7 Command Line Options 8 Input Dialog 9 Console Window 10 File Formats NEI apa les ee MO e ee we eo ee Oo oe ee eed 10 9 Output Ble gt o secam 64 AAR E SE ea ee ee EE SES ERG A A SOE eS Wo COV DE na ie i hg BAe RE ke ee BS ae eS o qa ow SR Se ee 11 Examples 12 Acknowledgments References 10 Index 12 1 Introduction Disclaimer This software is provided AS IS without warranty of any kind This is develop mental code and we make no pretension as to it being bug free and totally reliable Use at your own risk We will accept no liability for any damages incurred through the use of this software Use of the ReadSim is free however the program is not open source How to cite If you publish results obtained in part by using ReadSim then we require that you acknowledge this by citing the program as follows e R Schmid S C Schuster M A Steel and D H Huson ReadSim A simula tor for Sanger and 454 sequencing in preparation software freely available from www ab informatik uni tuebingen de software readsim The predominant approach to sequencing large DNA molecules is Sanger sequencing using a shot gun approach that involves cloning small pieces or inserts of DN
6. ab informatik uni tuebingen de software readsim There are four different installers targeting different operating systems e ReadSim_windows_0_7 exe provides an installer for Windows e ReadSimmacos 0 7 sit provides an installer for Mac OS e ReadSim_linux_0_7 rpm provides a RPM package for Linux e ReadSim_unix_0_7 sh provides a shell installer for Linux MacOS and Unix The executable program is called ReadSim The unix and linux installers additionally provide an executable called ReadSim cmdline 4 Program Overview In this section we give an overview of the main design goals and features of this program Basic knowledge of the underlying design of the program should make it easier to use the program ReadSim is written in the programming language Java The advantages of this is that we can provide versions that run under the Linux MacOS Windows and Unix operating systems A potential draw back is that an algorithm implemented in Java will generally run slower than the same algorithm implemented in C or C The program is designed to be run from the command line using switches such as i genome fasta to set all aspects of a simulation However for the convenience of use on operating systems that do not provide easy access to the command line such as Windows by default the program provides an Input dialog to enter the configuration options and a Console window to report the progress of the program 5 The Sanger Sequencing Mod
7. are implemented in our software A negative flow is a flow of nucleotides in which the sequence it not elongated Light intensities of negative flows follow a log normal distribution with mean u 0 23 and standard deviation o 0 15 see 3 A random variable X is lognormally distributed if and only if the random variable In X is normally distributed Let u and o be the mean and standard deviation of X and let m and s be the mean and standard deviation of In X Then m n ies and s wo 2 a The probability density function of a lognormal distributed random variable is usually specified with mean m and standard deviation s of the underlying normally distributed In X as stated in the following 4 nm 2 Cl ifr gt 0 Ho 4 EO 0 otherwise Based on this we simulate base calling intensities of negative flows and model the miss interpretation of null mers as homopolymers of length 1 Our algorithm takes the order of the nucleotide flows into account and so after a given base only two specific negative flows in a specific order are allowed since the nucleotides are cyclicly flowed in the order T A C G We have implemented two different methods of base calling In the intersection model the inter sections of the density functions fN r o and fiv ro x of the normal distributions for different homopolymer lengths r and r are calculated and stored in an intersection matriz M These values are used to decide which homop
8. ection of 10 x coverage of 454 reads The file human mtdna sanger reads contains a collection of 10 x coverage of Sanger reads from inserts 12 Acknowledgments We would like to thank Gene Myers Jonathan Rothberg Lei Du and Erick Matsen for helpful discussions References 1 O Delgado Friedrichs T Dezulian and D H Huson A meta viewer for biomolecular data GI Jahrestagung 1 375 380 2003 2 M Margulies M Egholm W E Altman S Attiya J S Bader L A Bemben J Berka M S Braverman Y J Chen Z Chen S B Dewell L D J M Fierro X V Gomes B C Godwin W He S Helgesen C H Ho G P Irzyk S C Jando M L I Alenquer T P Jarvie K B Jirage J B Kim J R Knight J R Lanza J H Leamon S M Lefkowitz M Lei J Li K L Lohman H Lu V B Makhijani K E McDade M P McKenna E W Myers E Nickerson J R Nobile R Plant B P Puc M T Ronan G T Roth G J Sarkis J F Simons J W Simpson M Srinivasan K R Tartaro A Tomasz K A Vogt G A Volkmer S H Wang Y Wang M P Weiner P Yu R F Begley and J M Rothberg Genome sequencing in microfabricated high density picolitre reactors Nature 437 7057 376 380 2005 3 M Margulies and et al Genome sequencing in microfabricated high density picolitre reactors Nature 437 7057 376 380 2005 10 D Meldrum Automation for genomics part one Preparation for sequencing Genome Re search 10 8 1081 1092 2000 D Meldrum Automa
9. el Most major sequencing projects are based on the same experimental technique called shotgun sequencing based on the method originally developed by Fred Sanger and his group We will refer to this as the Sanger sequencing model This technique is based on automated gel sequencers that use electrophoresis and fluorescent mark ers to determine the sequence of the nucleotides The ability of these machines to read consecutive pieces of DNA degrades quickly with the length of the sequence and today a sequencing machine can read up to 1000 consecutive base pairs of a fragment of DNA depending on the degree of accuracy desired The sequence of a fragment determined in this way is called a read The fragments are sampled from a stretch of DNA that is often referred to as the source sequence the sequence that we take the fragment from or as the target sequence the sequence we want to reconstruct from the reads To model Sanger sequencing the ReadSim program is supplied with a target genome sequence Fragments are then sampled from the target sequence To simulate the sequencing process the length of reads is randomly chosen under a uniform or normal distribution and sequencing errors are introduced into the reads The frequency of sequencing errors is position dependent following a ramp distribution Additionally to simulate paired end sequencing the length of inserts is randomly chosen under a uniform or normal distribution and failed
10. encing technology Our program simulates both Sanger sequencing and 454 sequencing and in both cases can simulator pair end sequencing although the latter is not yet possible with 454 technology In pyro sequencing the intensity of emitted light is used to estimate the length of homopolymers i e runs of identical nucleotides in a sequence During sequencing the four DNA composing nucleotides are periodically flowed over the inserts to be sequenced Within each flow the intensity of the signal emitted reflects the number of nucleotides incorporated and thus the length of the homopolymer under consideration For chemical and technical reasons this signal is subject to fluctuations that lead to sequencing errors 3 report an error rate of about 3 The ReadSim simulator produces reads with normally or uniformly distributed lengths They are randomly sampled from the target sequence and then subjected to a simulation of sequencing errors as follows Let r denote the length of a given homopolymer We model the emitted light intensity using a normal distribution N u o with mean yu r and standard deviation o k r where k is a fixed proportionality factor Following 3 by default we use k 0 15 Although basic statistics implies that the standard deviation should grow with the square root of r in 3 the standard deviation of the light intensity emitted during 454 sequencing is reported to be o k r Both variants of the calculation
11. lt read id gt beg lt start gt length lt length gt lt forward reverse gt matePair lt read id mate gt chimeric lt true false gt lt original FastA header gt There lt read id gt obviously is the id generated for the read belongig to that entry lt start gt states the position within the source sequence the read is taken from lt length gt states the length of the produced read lt forward reverse gt tells you whether the read is taken form the forward or the reverse strand lt read id mate gt holds the id of the mate pair if applicable lt true false gt is set to true if the mate pair is a chimeric one else to false lt original FastA header gt holds the origial FastaA header of the input sequence The sequence of the read is stated in the following lines 10 3 CGViz file Optionally the simulator can write information in CGViz format using the cgv op tion This file can be opened using the CG Viz program 1 and provides an in teractive visualization of the sampled reads The CGViz program is obtainable from www ab informatik uni tuebingen de software cgviz 11 Examples Example files are provided with the program They are contained in the examples sub directory of the installation directory The precise location of the installation directory depends upon your operating system The file human mtdna fasta contains the complete sequence of a human mtDNA genome The file human mtdna 454 reads contains a coll
12. olymer length is called Each entry of the matrix holds the x value of the intersection of two normal distributions i e M r r 1 holds the intersection of fw r o and fn r 1 0 where o is set according to the chosen intensity calculation The intersection weight method extends intersection base calling by using an additional binary experiment with probabilities weighted by fw ro i and fw r 1 0 i where i is the intensity of light generated according to the chosen N r o distribution 7 Command Line Options The ReadSim program is controlled by options that are either provided on the command line or using the Options dialog Here we list all available options Use the h option to obtain a listing of all options directly from the program Main options i name Name of input file containing source genome When set source genome is treated as circular o name Name of output file Default is readsim out or When set existing output file is replaced model model Sequencing model either 454 or sanger Options for read sequencing x number n number modlr model minlr number maxlr number meanlr number stdlr number f number Desired sequencing x coverage If set overrides option n Number of reads to generate Default is 2000 Read length model either uniform or normal Default is uniform Minimal length of read uniform model Default is 80 Maximal length of read uniform model Default i
13. rors arise in a different way and usually involves the length of homopolymer runs ReadSim is a command line program and is completely controlled by command line options How ever for convenience we also supply a console mode in which an Input dialog is presented and output is written to a Console window This document provides both an introduction and a reference manual for ReadSim 2 Getting Started This section describes how to get started First download an installer for the program from www ab informatik uni tuebingen de software readsim see Section 3 for details The executable program is called ReadSim The unix and linux installers additionally provide an executable called ReadSim cmdline Upon startup of ReadSim a dialog is presented that can be used to set all command line parameters Press the Help button to list a summary of all available options Use the i option to specify an input file containing a target DNA sequence in FastA format Use the x option to specify the x coverage desired Use the option model to choose between the 454 model and sanger model By default the program will use the 454 model and will write all collected reads to a file named readsim out 3 Obtaining and Installing the Program ReadSim is written in Java and requires a Java runtime environment version 1 5 or newer freely available from www java org ReadSim is installed using an installer program that is freely available from www
14. s 120 Mean length of reads to generate normal model Default is 100 Standard deviation as proportion of mean normal model Default is 0 1 Probability that read is chosen from forward strand Default is 0 5 Options for insert sequencing modli model minli number maxli number meanli number stdli number pf number pc number Insert length model either uniform or normal Default is uniform Minimal length of insert uniform model Default is 1600 Maximal length of insert uniform model Default is 2400 Mean length of insert lengths normal model Default is 2000 Standard deviation as proportion of mean normal model Default is 0 1 Proportion of reads that won t be paired Default is 0 1 Proportion of chimeric inserts Default is 0 05 Options for the Sanger sequencing model eb number ee number pd number pi number Single base error rate at start of a read Default is 0 01 Single base error rate at end of a read Default is 0 02 Proportion of errors that are deletions Default is 0 2 Proportion of errors that are insertions Default is 0 2 Options for the 454 sequencing model sqrt If set use o k x length else use k x length Default is set k number Proportionality factor for calculating standard deviation proportional to sqrt homopolymer length Default is 0 15 bc model Base calling options inter calculate intersection of normal density curves inter
15. tion for genomics part two Sequencers microarrays and future trends Genome Research 10 9 1288 1303 2000 G Myers A dataset generator for whole genome shotgun sequencing In Proc Int Conf Intell Syst Mol Biol pages 202 10 1999 H N Poinar C Schwarz Ji Qi B Shapiro R D E MacPhee B Buigues A Tikhonov D H Huson L P Tomsho A Auch M Rampp W Miller and S C Schuster Metagenomics to Paleogenomics Large Scale Sequencing of Mammoth DNA Science 331 392 394 2006 J L Webber and E W Myers Human whole genome shotgun sequencing Genome Research 7 5 401 409 1997 11 Index 454mate 7 V 8 be 7 c 6 cgv 8 eb 7 ee 7 f 7 h 8 i 6 k 7 maxli 7 maxlr 7 meanli 7 meanlr 7 minli 7 minlr 7 model 6 modli 7 modlr 7 n 7 0 6 or 6 pc 7 pd 7 pf 7 pi 7 pre 8 seed 8 sqrt 7 start 8 stdli 7 stdlr 7 v 8 x 7 454 4 Apply 8 Cancel 8 CGViz 10 Clear 9 Close 8 Console 8 Copy 9 Cut 8 Disclaimer 2 Edit 8 Edit Clear 9 Edit Copy 9 Edit Cut 8 Edit Paste 9 Edit Select All 9 examples 10 File 8 File Close 8 File Print 8 File Save As 8 Help 8 How to cite 2 human mtdna 454 reads 10 human mtdna sanger reads 10 human mtdna fasta 10 i 7 input area 8 Linux 3 4 Mac OS 3 MacOS 3 4 Options 8 Paste 9 Print 8 R 3 8 read 4 Read Options
16. w intersection weight and nearest rounds to nearest integer Default is inter 454mate If set enable generation of mate pairs for 454 model else disabel Additional options pre label Prefix for read identifiers Default is read start number Number of first read identifier Default is 1 cgv name Save CGViz graphics to this file if provided seed number If non zero use as seed for random number generator v Verbose show settings of command line arguments V Show version information h Show usage and quit 8 Input Dialog The command line version ReadSim cmdline is configured by specifying options on the command line when launching the program At startup the other version ReadSim opens an Options dialog which must be used to configure the program The Options dialog is modal and will only close when either the Help Cancel or Apply button is pressed Options are typed into the input area in the same syntax as used for command line options as described in Section 7 Options typed into this area can be saved to a file using the Save Options button or read from a file using the Read Options button Pressing the Help button will close the dialog and request the program to provide a list of all options in the console window Pressing the Cancel button will close the dialog without setting any options Pressing the Apply button run the program using all options specified in the input area As the program is currently not re
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