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云之南

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专业背景:计算机科学 研究方向与兴趣: JavaEE-Web软件开发, 生物信息学, 数据挖掘与机器学习, 智能信息系统 目前工作: 基因组, 转录组, NGS高通量数据分析, 生物数据挖掘, 植物系统发育和比较进化基因组学

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八篇基因组组装软件评估文章  

2013-06-24 11:07:07|  分类: 生信分析软件 |  标签: |举报 |字号 订阅

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http://seq.cn/forum.php?mod=viewthread&tid=12235&reltid=13436&pre_thread_id=0&pre_pos=2&ext=
1. Bao, S., et al. (2011). "Evaluation of next-generation sequencing software in mapping and assembly." J Hum Genet.        Next-generation high-throughput DNA sequencing technologies have advanced progressively in sequence-based genomic research and novel biological applications with the promise of sequencing DNA at unprecedented speed. These new non-Sanger-based technologies feature several advantages when compared with traditional sequencing methods in terms of higher sequencing speed, lower per run cost and higher accuracy. However, reads from next-generation sequencing (NGS) platforms, such as 454/Roche, ABI/SOLiD and Illumina/Solexa, are usually short, thereby restricting the applications of NGS platforms in genome assembly and annotation. We presented an overview of the challenges that these novel technologies meet and particularly illustrated various bioinformatics attempts on mapping and assembly for problem solving. We then compared the performance of several programs in these two fields, and further provided advices on selecting suitable tools for specific biological applications.Journal of Human Genetics advance online publication, 28 April 2011; doi:10.1038/jhg.2011.43.
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2. Vezzi, F., et al. (2012). "Reevaluating assembly evaluations with feature response curves: GAGE and assemblathons." PLoS One 7(12): e52210.        In just the last decade, a multitude of bio-technologies and software pipelines have emerged to revolutionize genomics. To further their central goal, they aim to accelerate and improve the quality of de novo whole-genome assembly starting from short DNA sequences/reads. However, the performance of each of these tools is contingent on the length and quality of the sequencing data, the structure and complexity of the genome sequence, and the resolution and quality of long-range information. Furthermore, in the absence of any metric that captures the most fundamental "features" of a high-quality assembly, there is no obvious recipe for users to select the most desirable assembler/assembly. This situation has prompted the scientific community to rely on crowd-sourcing through international competitions, such as Assemblathons or GAGE, with the intention of identifying the best assembler(s) and their features. Somewhat circuitously, the only available approach to gauge de novo assemblies and assemblers relies solely on the availability of a high-quality fully assembled reference genome sequence. Still worse, reference-guided evaluations are often both difficult to analyze, leading to conclusions that are difficult to interpret. In this paper, we circumvent many of these issues by relying upon a tool, dubbed [Formula: see text], which is capable of evaluating de novo assemblies from the read-layouts even when no reference exists. We extend the FRCurve approach to cases where lay-out information may have been obscured, as is true in many deBruijn-graph-based algorithms. As a by-product, FRCurve now expands its applicability to a much wider class of assemblers - thus, identifying higher-quality members of this group, their inter-relations as well as sensitivity to carefully selected features, with or without the support of a reference sequence or layout for the reads. The paper concludes by reevaluating several recently conducted assembly competitions and the datasets that have resulted from them.  M! l- @; z. Y5 N& i$ j

3. Salzberg, S. L., et al. (2012). "GAGE: A critical evaluation of genome assemblies and assembly algorithms." Genome Res 22(3): 557-567.
        New sequencing technology has dramatically altered the landscape of whole-genome sequencing, allowing scientists to initiate numerous projects to decode the genomes of previously unsequenced organisms. The lowest-cost technology can generate deep coverage of most species, including mammals, in just a few days. The sequence data generated by one of these projects consist of millions or billions of short DNA sequences (reads) that range from 50 to 150 nt in length. These sequences must then be assembled de novo before most genome analyses can begin. Unfortunately, genome assembly remains a very difficult problem, made more difficult by shorter reads and unreliable long-range linking information. In this study, we evaluated several of the leading de novo assembly algorithms on four different short-read data sets, all generated by Illumina sequencers. Our results describe the relative performance of the different assemblers as well as other significant differences in assembly difficulty that appear to be inherent in the genomes themselves. Three overarching conclusions are apparent: first, that data quality, rather than the assembler itself, has a dramatic effect on the quality of an assembled genome; second, that the degree of contiguity of an assembly varies enormously among different assemblers and different genomes; and third, that the correctness of an assembly also varies widely and is not well correlated with statistics on contiguity. To enable others to replicate our results, all of our data and methods are freely available, as are all assemblers used in this study.7 d6 F1 u  ?/ O6 s, {$ I& c& G
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4. Zhang, W., et al. (2011). "A practical comparison of de novo genome assembly software tools for next-generation sequencing technologies." PLoS One 6(3): e17915." D/ I* F2 R, v/ @
        The advent of next-generation sequencing technologies is accompanied with the development of many whole-genome sequence assembly methods and software, especially for de novo fragment assembly. Due to the poor knowledge about the applicability and performance of these software tools, choosing a befitting assembler becomes a tough task. Here, we provide the information of adaptivity for each program, then above all, compare the performance of eight distinct tools against eight groups of simulated datasets from Solexa sequencing platform. Considering the computational time, maximum random access memory (RAM) occupancy, assembly accuracy and integrity, our study indicate that string-based assemblers, overlap-layout-consensus (OLC) assemblers are well-suited for very short reads and longer reads of small genomes respectively. For large datasets of more than hundred millions of short reads, De Bruijn graph-based assemblers would be more appropriate. In terms of software implementation, string-based assemblers are superior to graph-based ones, of which SOAPdenovo is complex for the creation of configuration file. Our comparison study will assist researchers in selecting a well-suited assembler and offer essential information for the improvement of existing assemblers or the developing of novel assemblers., M3 Z8 v5 {) I1 @) j
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5. Narzisi, G. and B. Mishra (2011). "Comparing de novo genome assembly: the long and short of it." PLoS One 6(4): e19175.
        Recent advances in DNA sequencing technology and their focal role in Genome Wide Association Studies (GWAS) have rekindled a growing interest in the whole-genome sequence assembly (WGSA) problem, thereby, inundating the field with a plethora of new formalizations, algorithms, heuristics and implementations. And yet, scant attention has been paid to comparative assessments of these assemblers' quality and accuracy. No commonly accepted and standardized method for comparison exists yet. Even worse, widely used metrics to compare the assembled sequences emphasize only size, poorly capturing the contig quality and accuracy. This paper addresses these concerns: it highlights common anomalies in assembly accuracy through a rigorous study of several assemblers, compared under both standard metrics (N50, coverage, contig sizes, etc.) as well as a more comprehensive metric (Feature-Response Curves, FRC) that is introduced here; FRC transparently captures the trade-offs between contigs' quality against their sizes. For this purpose, most of the publicly available major sequence assemblers - both for low-coverage long (Sanger) and high-coverage short (Illumina) reads technologies - are compared. These assemblers are applied to microbial (Escherichia coli, Brucella, Wolbachia, Staphylococcus, Helicobacter) and partial human genome sequences (Chr. Y), using sequence reads of various read-lengths, coverages, accuracies, and with and without mate-pairs. It is hoped that, based on these evaluations, computational biologists will identify innovative sequence assembly paradigms, bioinformaticists will determine promising approaches for developing "next-generation" assemblers, and biotechnologists will formulate more meaningful design desiderata for sequencing technology platforms. A new software tool for computing the FRC metric has been developed and is available through the AMOS open-source consortium.! f. v7 w% U. A5 b3 N0 m' d: I

6. Lin, Y., et al. (2011). "Comparative Studies of de novo Assembly Tools for Next-generation Sequencing Technologies." Bioinformatics.% j9 C+ k. i; k1 _& c
        MOTIVATION: Several new de novo assembly tools have been developed recently to assemble short sequencing reads generated by next-generation sequencing platforms. However, the performance of these tools under various conditions has not been fully investigated, and sufficient information is not currently available for informed decisions to be made regarding the tool that would be most likely to produce the best performance under a specific set of conditions. RESULTS: We studied and compared the performance of commonly used de novo assembly tools specifically designed for next-generation sequencing data, including SSAKE, VCAKE, Euler-sr, Edena, Velvet, ABySS and SOAPdenovo. Tools were compared using several performance criteria, including N50 length, sequence cover-age, and assembly accuracy. Various properties of read data, including single-end/paired-end, sequence GC content, depth of coverage and base calling error rates, were investigated for their effects on the performance of different assembly tools. We also compared the computation time and memory usage of these seven tools. Based on the results of our comparison, the relative perform-ance of individual tools are summarized and tentative guidelines for optimal selection of different assembly tools, under different condi-tions, are provided. CONTACT: hdeng2@tulane.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available.+ ]/ [$ R# z  C* C& O; P

7. Finotello, F., et al. (2011). "Comparative analysis of algorithms for whole-genome assembly of pyrosequencing data." Brief Bioinform., G$ Y% x* a6 J. Y; T- K+ P- u" _& e+ k
        Next-generation sequencing technologies have fostered an unprecedented proliferation of high-throughput sequencing projects and a concomitant development of novel algorithms for the assembly of short reads. In this context, an important issue is the need of a careful assessment of the accuracy of the assembly process. Here, we review the efficiency of a panel of assemblers, specifically designed to handle data from GS FLX 454 platform, on three bacterial data sets with different characteristics in terms of reads coverage and repeats content. Our aim is to investigate their strengths and weaknesses in the reconstruction of the reference genomes. In our benchmarking, we assess assemblers' performance, quantifying and characterizing assembly gaps and errors, and evaluating their ability to solve complex genomic regions containing repeats. The final goal of this analysis is to highlight pros and cons of each method, in order to provide the final user with general criteria for the right choice of the appropriate assembly strategy, depending on the specific needs. A further aspect we have explored is the relationship between coverage of a sequencing project and quality of the obtained results. The final outcome suggests that, for a good tradeoff between costs and results, the planned genome coverage of an experiment should not exceed 20-30 x.
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8. Earl, D. A., et al. (2011). "Assemblathon 1: A competitive assessment of de novo short read assembly methods." Genome Res.
        Low cost short read sequencing technology has revolutionised genomics, though it is only just becoming practical for the high quality de novo assembly of a novel large genome. We describe the Assemblathon 1 competition, which aimed to comprehensively assess the state of the art in de novo assembly methods when applied to current sequencing technologies. In a collaborative effort teams were asked to assemble a simulated Illumina HiSeq dataset of an unknown, simulated diploid genome. A total of 41 assemblies from 17 different groups were received. Novel haplotype aware assessments of coverage, contiguity, structure, base calling and copy number were made. We establish that within this benchmark (1) it is possible to assemble the genome to a high level of coverage and accuracy, and that (2) large differences exist between the assemblies, suggesting room for further improvements in current methods.
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