pIRS: Profile-based Illumina pair-end reads simulator

Hu, Xuesong; Yuan, Jianying; Shi, Yujian; Lu, Jianliang; Liu, Binghang; Li, Zhenyu; Chen, Yanxiang; Mu, Desheng; Zhang, Hao; Li, Nan; Yue, Zhen; Bai, Fan; Li, Heng; Fan, Wei

doi:10.1093/bioinformatics/bts187

Cited by 177 publications

(151 citation statements)

References 9 publications

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“…In parallel, we used DAWG v1.2 17 to simulate evolution of intergenic regions using the same GTR matrix parameters and previously estimated intergenic SNP to INDEL rate 15 . We combined the resulting sequences of coding and non-coding regions at tips of the phylogeny while accounting for gene loss and transfer, and finally generated error prone Illumina reads from these sequences using pIRS v1.11 18 .…”

Section: Methodsmentioning

confidence: 99%

Evaluation of phylogenetic reconstruction methods using bacterial whole genomes: a simulation based study

Lees¹,

Kendall²,

Parkhill³

et al. 2018

Wellcome Open Res

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Background: Phylogenetic reconstruction is a necessary first step in many analyses which use whole genome sequence data from bacterial populations. There are many available methods to infer phylogenies, and these have various advantages and disadvantages, but few unbiased comparisons of the range of approaches have been made. Methods: We simulated data from a defined “true tree” using a realistic evolutionary model. We built phylogenies from this data using a range of methods, and compared reconstructed trees to the true tree using two measures, noting the computational time needed for different phylogenetic reconstructions. We also used real data from Streptococcus pneumoniae alignments to compare individual core gene trees to a core genome tree. Results: We found that, as expected, maximum likelihood trees from good quality alignments were the most accurate, but also the most computationally intensive. Using less accurate phylogenetic reconstruction methods, we were able to obtain results of comparable accuracy; we found that approximate results can rapidly be obtained using genetic distance based methods. In real data we found that highly conserved core genes, such as those involved in translation, gave an inaccurate tree topology, whereas genes involved in recombination events gave inaccurate branch lengths. We also show a tree-of-trees, relating the results of different phylogenetic reconstructions to each other. Conclusions: We recommend three approaches, depending on requirements for accuracy and computational time. Quicker approaches that do not perform full maximum likelihood optimisation may be useful for many analyses requiring a phylogeny, as generating a high quality input alignment is likely to be the major limiting factor of accurate tree topology. We have publicly released our simulated data and code to enable further comparisons.

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Section: Methodsmentioning

confidence: 99%

Evaluation of phylogenetic reconstruction methods using bacterial whole genomes: a simulation based study

Lees¹,

Kendall²,

Parkhill³

et al. 2018

Wellcome Open Res

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show abstract

“…Thus, simulation is used to evaluate performance of bioinformatics tools [227,228], design sequencing projects [229] and computational tools [230]. It is also very useful for evaluating of assemblies [231], gene prediction [232], and genotyping and haplotype reconstruction [154,233].…”

Section: Ngs Error Models and Simulationsmentioning

confidence: 99%

Computational Errors and Biases in Short Read Next Generation Sequencing

Abnizova¹,

Boekhorst²,

Orlov³

2017

J Proteomics Bioinform

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“…RSVSim biased SVs to certain types of repeat regions and corresponding mechanisms of formation, such as non-allelic homologous recombination, based on several studies (Chen et al 2008;Lam et al 2010;Mills et al 2011;Ou et al 2011;Pang et al 2013). We then used pIRS (Hu et al 2012) to simulate 100-base Illumina paired-end reads with 500 base inserts and read coverage above ten. pIRS is designed to simulate Illumina basecalling error profiles and GC bias.…”

Section: Datasetsmentioning

confidence: 99%

GROM-RD: Resolving genomic biases to improve read depth detection of copy number variants

Smith

Kawash

Grigoriev

2014

Preprint

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Amplifications or deletions of genome segments, known as copy number variants (CNVs), have been associated with many diseases. Read depth analysis of next-generation sequencing (NGS) is an essential method of detecting CNVs. However, genome read coverage is frequently distorted by various biases of NGS platforms, which reduce predictive capabilities of existing approaches. Additionally, the use of read depth tools has been somewhat hindered by imprecise breakpoint identification. We developed GROM-RD, an algorithm that analyzes multiple biases in read coverage to detect CNVs in NGS data. We found non-uniform variance across distinct GC regions after using existing GC bias correction methods and developed a novel approach to normalize such variance. Although complex and repetitive genome segments complicate CNV detection, GROM-RD adjusts for repeat bias and uses a two-pipeline masking approach to detect CNVs in complex and repetitive segments while improving sensitivity in less complicated regions. To overcome a typical weakness of RD methods, GROM-RD employs a CNV search using size-varying overlapping windows to improve breakpoint resolution. We compared our method to two widely used programs based on read depth methods, CNVnator and RDXplorer, and observed improved CNV detection and breakpoint accuracy for GROM-RD. GROM-RD is available at

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pIRS: Profile-based Illumina pair-end reads simulator

Abstract: pIRS is written in C++ and Perl, and is freely available at ftp://ftp.genomics.org.cn/pub/pIRS/.

Cited by 177 publications

References 9 publications

Evaluation of phylogenetic reconstruction methods using bacterial whole genomes: a simulation based study

Evaluation of phylogenetic reconstruction methods using bacterial whole genomes: a simulation based study

Computational Errors and Biases in Short Read Next Generation Sequencing

GROM-RD: Resolving genomic biases to improve read depth detection of copy number variants

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