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Implements a probabilistic model of the evolution of RNA-, DNA-, or protein-like sequences. Rose allows for varying rates of mutation within the sequences, making it possible to establish so-called sequence motifs. The data created by Rose are suitable for the evaluation of methods in multiple sequence alignment computation and the prediction of phylogenetic relationships. It can also be useful when teaching courses in or developing models of sequence evolution and in the study of evolutionary processes
A targeted re-sequencing simulator that generates synthetic exome sequencing reads from a given sample genome. Wessim emulates conventional exome capture technologies, including Agilent's SureSelect and NimbleGen's SeqCap, to generate DNA fragments from genomic target regions. The target regions can be either specified by genomic coordinates or inferred from in silico probe hybridization. Coupled with existing next-generation sequencing simulators, Wessim generates a realistic artificial exome sequencing data, which is essential for developing and evaluating exome-targeted variant callers.
GGRaSP / Gaussian Genome Representative Selector with Prioritization
Builds a list of prioritized representative genomes from either supervised or unsupervised clustering of related genomes. GGRaSP can reduce the loss of information by prioritizing medoids as representative genomes. It employs supervised methods such as specifying the number of clusters or the cluster cut-off distance to cluster genomes. This tool can serve for the identification of a cut-off value that separates the most closely related genomes from the more diverse genomes.
A set of programs aimed at simulating ancient DNA fragments. Gargamel can simulate most common features of a DNA sequences, including post-mortem DNA damage and base misincorporations. It simulates base compositional bias due to the molecular tools used in library preparation, sequencing bias against GC-rich fragments and errors introduced by the sequencing platform. Gargammel provides researchers with the opportunity to perform various inquiries to evaluate the robustness of various analyses to a DNA properties.
Creates prokaryotic pseudo-genomes. Simulome provides options that can be used in combination to create mutated variants of the simulated genome, which allows for controlled testing of specific genomic conditions. It can be used in combination with real reads generated from next-generation sequencing (NGS) platforms, or with simulated reads. The tool allows to analyze the effect of specific mutation types on a large scale, providing researchers with the ability to investigate the efficacy of analysis methodologies on a large number of genes that contain similar mutation events.
Generates raw read data from mutated genomes simulated under a known phylogeny. TreeToReads allows direct comparisons of simulated and observed data in a controlled environment. It allows researchers to test the joint effects of multiple parameter values on the ability of any analysis pipeline to recover the signal and infer the correct tree. The user can vary parameters of interest to assess the effects of various parameter values on correctly calling single nucleotides polymorphisms (SNPs) and reconstructing an accurate tree.
An application for simulation of 454 data at high speed and accuracy. The program is multi-thread capable and is available as C++ source code or pre-compiled binaries. Sequence reads are simulated by 454sim using a set of statistical models for each chemistry. 454sim simulates recorded peak intensities, peak quality deterioration and it calculates quality values. All three generations of the Roche 454 chemistry ('GS20', 'GS FLX' and 'Titanium') are supported and defined in external text files for easy access and tweaking.
Enables users to assess the quality of NGS datasets. FASTQSim provides information about read length, read quality, repetitive and non-repetitive indel profiles, and single base pair substitutions. It allows the user to simulate individual read datasets that can be used as standardized test scenarios for planning sequencing projects or for benchmarking metagenomic software. In this regard, in silico datasets generated with the FASTQsim tool hold several advantages over natural datasets: they are sequencing platform independent, extremely well characterized, and less expensive to generate. Such datasets are valuable in a number of applications, including the training of assemblers for multiple platforms, benchmarking bioinformatics algorithm performance, and creating challenge datasets for detecting genetic engineering toolmarks, etc.
A skilled FASTQ read simulation tool, flexible, portable (does not need a reference sequence) and tunable in terms of sequence complexity. XS handles Ion Torrent, Roche-454, Illumina and ABI-SOLiD simulation sequencing types. It has several running modes, depending on the time and memory available, and is aimed at testing computing infrastructures, namely cloud computing of large-scale projects, and testing FASTQ compression algorithms. Moreover, XS offers the possibility of simulating the three main FASTQ components individually (headers, DNA sequences and quality-scores).
Generates standardized sequencing results. SiLiCO simulates both PacBio and Oxford Nanopore read sequencing results by stochastically generating genomic coordinates and extracting corresponding nucleotide sequences from a reference assembly. SiLiCO also is easily scaled up to a Monte-Carlo simulation, affording the end user the ability to construct empirical distributions of various genomic features. Analysis of simulated results confirmed that SiLiCO produces read lengths consistent with log-normal and gamma distributions and produced even coverage across all chromosomes at the user specified level.
A flexible short read simulator. ShotGun generates sequence data with user-specified read length and average depth, accommodates to cycle specific sequencing error rates, allows the read depth distribution to be either the ideal Poisson or Negative Binomial to model the overdispersion observed with real sequencing data. In addition, ShotGun performs computationally efficient Single Nucleotide Polymorphism (SNP) discovery using a statistic aggregated across all sequenced samples.
A small tool for simulating sequence reads from a reference genome. It is able to simulate diploid genomes with SNPs and insertion/deletion (INDEL) polymorphisms, and simulate reads with uniform substitution sequencing errors. It does not generate INDEL sequencing errors, but this can be partly compensated by simulating INDEL polymorphisms. Wgsim outputs the simulated polymorphisms, and writes the true read coordinates as well as the number of polymorphisms and sequencing errors in read names.
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