共查询到20条相似文献，搜索用时 31 毫秒
1.
Maochun Qin Biao Liu Jeffrey M Conroy Carl D Morrison Qiang Hu Yubo Cheng Mitsuko Murakami Adekunle O Odunsi Candace S Johnson Lei Wei Song Liu Jianmin Wang 《BMC bioinformatics》2015,16(1)
Background
Somatically acquired structure variations (SVs) and copy number variations (CNVs) can induce genetic changes that are directly related to tumor genesis. Somatic SV/CNV detection using next-generation sequencing (NGS) data still faces major challenges introduced by tumor sample characteristics, such as ploidy, heterogeneity, and purity. A simulated cancer genome with known SVs and CNVs can serve as a benchmark for evaluating the performance of existing somatic SV/CNV detection tools and developing new methods.Results
SCNVSim is a tool for simulating somatic CNVs and structure variations SVs. Other than multiple types of SV and CNV events, the tool is capable of simulating important features related to tumor samples including aneuploidy, heterogeneity and purity.Conclusions
SCNVSim generates the genomes of a cancer cell population with detailed information of copy number status, loss of heterozygosity (LOH), and event break points, which is essential for developing and evaluating somatic CNV and SV detection methods in cancer genomics studies. 相似文献2.
Adam C English William J Salerno Oliver A Hampton Claudia Gonzaga-Jauregui Shruthi Ambreth Deborah I Ritter Christine R Beck Caleb F Davis Mahmoud Dahdouli Singer Ma Andrew Carroll Narayanan Veeraraghavan Jeremy Bruestle Becky Drees Alex Hastie Ernest T Lam Simon White Pamela Mishra Min Wang Yi Han Feng Zhang Pawel Stankiewicz David A Wheeler Jeffrey G Reid Donna M Muzny Jeffrey Rogers Aniko Sabo Kim C Worley James R Lupski Eric Boerwinkle Richard A Gibbs 《BMC genomics》2015,16(1)
Background
Characterizing large genomic variants is essential to expanding the research and clinical applications of genome sequencing. While multiple data types and methods are available to detect these structural variants (SVs), they remain less characterized than smaller variants because of SV diversity, complexity, and size. These challenges are exacerbated by the experimental and computational demands of SV analysis. Here, we characterize the SV content of a personal genome with Parliament, a publicly available consensus SV-calling infrastructure that merges multiple data types and SV detection methods.Results
We demonstrate Parliament’s efficacy via integrated analyses of data from whole-genome array comparative genomic hybridization, short-read next-generation sequencing, long-read (Pacific BioSciences RSII), long-insert (Illumina Nextera), and whole-genome architecture (BioNano Irys) data from the personal genome of a single subject (HS1011). From this genome, Parliament identified 31,007 genomic loci between 100 bp and 1 Mbp that are inconsistent with the hg19 reference assembly. Of these loci, 9,777 are supported as putative SVs by hybrid local assembly, long-read PacBio data, or multi-source heuristics. These SVs span 59 Mbp of the reference genome (1.8%) and include 3,801 events identified only with long-read data. The HS1011 data and complete Parliament infrastructure, including a BAM-to-SV workflow, are available on the cloud-based service DNAnexus.Conclusions
HS1011 SV analysis reveals the limits and advantages of multiple sequencing technologies, specifically the impact of long-read SV discovery. With the full Parliament infrastructure, the HS1011 data constitute a public resource for novel SV discovery, software calibration, and personal genome structural variation analysis.Electronic supplementary material
The online version of this article (doi:10.1186/s12864-015-1479-3) contains supplementary material, which is available to authorized users. 相似文献3.
Background
Structural variations (SVs) are wide-spread in human genomes and may have important implications in disease-related and evolutionary studies. High-throughput sequencing (HTS) has become a major platform for SV detection and simulation serves as a powerful and cost-effective approach for benchmarking SV detection algorithms. Accurate performance assessment by simulation requires the simulator capable of generating simulation data with all important features of real data, such GC biases in HTS data and various complexities in tumor data. However, no available package has systematically addressed all issues in data simulation for SV benchmarking.Results
Pysim-sv is a package for simulating HTS data to evaluate performance of SV detection algorithms. Pysim-sv can introduce a wide spectrum of germline and somatic genomic variations. The package contains functionalities to simulate tumor data with aneuploidy and heterogeneous subclones, which is very useful in assessing algorithm performance in tumor studies. Furthermore, Pysim-sv can introduce GC-bias, the most important and prevalent bias in HTS data, in the simulated HTS data.Conclusions
Pysim-sv provides an unbiased toolkit for evaluating HTS-based SV detection algorithms.4.
Sean R Landman Tae Hyun Hwang Kevin AT Silverstein Yingming Li Scott M Dehm Michael Steinbach Vipin Kumar 《BMC genomics》2014,15(1)
Background
Personal genome assembly is a critical process when studying tumor genomes and other highly divergent sequences. The accuracy of downstream analyses, such as RNA-seq and ChIP-seq, can be greatly enhanced by using personal genomic sequences rather than standard references. Unfortunately, reads sequenced from these types of samples often have a heterogeneous mix of various subpopulations with different variants, making assembly extremely difficult using existing assembly tools. To address these challenges, we developed SHEAR (Sample Heterogeneity Estimation and Assembly by Reference; http://vk.cs.umn.edu/SHEAR), a tool that predicts SVs, accounts for heterogeneous variants by estimating their representative percentages, and generates personal genomic sequences to be used for downstream analysis.Results
By making use of structural variant detection algorithms, SHEAR offers improved performance in the form of a stronger ability to handle difficult structural variant types and better computational efficiency. We compare against the lead competing approach using a variety of simulated scenarios as well as real tumor cell line data with known heterogeneous variants. SHEAR is shown to successfully estimate heterogeneity percentages in both cases, and demonstrates an improved efficiency and better ability to handle tandem duplications.Conclusion
SHEAR allows for accurate and efficient SV detection and personal genomic sequence generation. It is also able to account for heterogeneous sequencing samples, such as from tumor tissue, by estimating the subpopulation percentage for each heterogeneous variant.Electronic supplementary material
The online version of this article (doi:10.1186/1471-2164-15-84) contains supplementary material, which is available to authorized users. 相似文献5.
Background
Next generation sequencing technology has allowed efficient production of draft genomes for many organisms of interest. However, most draft genomes are just collections of independent contigs, whose relative positions and orientations along the genome being sequenced are unknown. Although several tools have been developed to order and orient the contigs of draft genomes, more accurate tools are still needed.Results
In this study, we present a novel reference-based contig assembly (or scaffolding) tool, named as CAR, that can efficiently and more accurately order and orient the contigs of a prokaryotic draft genome based on a reference genome of a related organism. Given a set of contigs in multi-FASTA format and a reference genome in FASTA format, CAR can output a list of scaffolds, each of which is a set of ordered and oriented contigs. For validation, we have tested CAR on a real dataset composed of several prokaryotic genomes and also compared its performance with several other reference-based contig assembly tools. Consequently, our experimental results have shown that CAR indeed performs better than all these other reference-based contig assembly tools in terms of sensitivity, precision and genome coverage.Conclusions
CAR serves as an efficient tool that can more accurately order and orient the contigs of a prokaryotic draft genome based on a reference genome. The web server of CAR is freely available at http://genome.cs.nthu.edu.tw/CAR/ and its stand-alone program can also be downloaded from the same website.Electronic supplementary material
The online version of this article (doi:10.1186/s12859-014-0381-3) contains supplementary material, which is available to authorized users. 相似文献6.
7.
Steven N. Hart Vivekananda Sarangi Raymond Moore Saurabh Baheti Jaysheel D. Bhavsar Fergus J. Couch Jean-Pierre A. Kocher 《PloS one》2013,8(12)
Background
Structural variation (SV) represents a significant, yet poorly understood contribution to an individual’s genetic makeup. Advanced next-generation sequencing technologies are widely used to discover such variations, but there is no single detection tool that is considered a community standard. In an attempt to fulfil this need, we developed an algorithm, SoftSearch, for discovering structural variant breakpoints in Illumina paired-end next-generation sequencing data. SoftSearch combines multiple strategies for detecting SV including split-read, discordant read-pair, and unmated pairs. Co-localized split-reads and discordant read pairs are used to refine the breakpoints.Results
We developed and validated SoftSearch using real and synthetic datasets. SoftSearch’s key features are 1) not requiring secondary (or exhaustive primary) alignment, 2) portability into established sequencing workflows, and 3) is applicable to any DNA-sequencing experiment (e.g. whole genome, exome, custom capture, etc.). SoftSearch identifies breakpoints from a small number of soft-clipped bases from split reads and a few discordant read-pairs which on their own would not be sufficient to make an SV call.Conclusions
We show that SoftSearch can identify more true SVs by combining multiple sequence features. SoftSearch was able to call clinically relevant SVs in the BRCA2 gene not reported by other tools while offering significantly improved overall performance. 相似文献8.
Arthur Gilly Mathilde Etcheverry Mohammed-Amin Madoui Julie Guy Leandro Quadrana Adriana Alberti Antoine Martin Tony Heitkam Stefan Engelen Karine Labadie Jeremie Le Pen Patrick Wincker Vincent Colot Jean-Marc Aury 《BMC bioinformatics》2014,15(1)
Background
Transposable elements (TEs) are DNA sequences that are able to move from their location in the genome by cutting or copying themselves to another locus. As such, they are increasingly recognized as impacting all aspects of genome function. With the dramatic reduction in cost of DNA sequencing, it is now possible to resequence whole genomes in order to systematically characterize novel TE mobilization in a particular individual. However, this task is made difficult by the inherently repetitive nature of TE sequences, which in some eukaryotes compose over half of the genome sequence. Currently, only a few software tools dedicated to the detection of TE mobilization using next-generation-sequencing are described in the literature. They often target specific TEs for which annotation is available, and are only able to identify families of closely related TEs, rather than individual elements.Results
We present TE-Tracker, a general and accurate computational method for the de-novo detection of germ line TE mobilization from re-sequenced genomes, as well as the identification of both their source and destination sequences. We compare our method with the two classes of existing software: specialized TE-detection tools and generic structural variant (SV) detection tools. We show that TE-Tracker, while working independently of any prior annotation, bridges the gap between these two approaches in terms of detection power. Indeed, its positive predictive value (PPV) is comparable to that of dedicated TE software while its sensitivity is typical of a generic SV detection tool. TE-Tracker demonstrates the benefit of adopting an annotation-independent, de novo approach for the detection of TE mobilization events. We use TE-Tracker to provide a comprehensive view of transposition events induced by loss of DNA methylation in Arabidopsis. TE-Tracker is freely available at http://www.genoscope.cns.fr/TE-Tracker.Conclusions
We show that TE-Tracker accurately detects both the source and destination of novel transposition events in re-sequenced genomes. Moreover, TE-Tracker is able to detect all potential donor sequences for a given insertion, and can identify the correct one among them. Furthermore, TE-Tracker produces significantly fewer false positives than common SV detection programs, thus greatly facilitating the detection and analysis of TE mobilization events.Electronic supplementary material
The online version of this article (doi:10.1186/s12859-014-0377-z) contains supplementary material, which is available to authorized users. 相似文献9.
MetaSim: a sequencing simulator for genomics and metagenomics 总被引：1，自引：0，他引：1
Background
The new research field of metagenomics is providing exciting insights into various, previously unclassified ecological systems. Next-generation sequencing technologies are producing a rapid increase of environmental data in public databases. There is great need for specialized software solutions and statistical methods for dealing with complex metagenome data sets.Methodology/Principal Findings
To facilitate the development and improvement of metagenomic tools and the planning of metagenomic projects, we introduce a sequencing simulator called MetaSim. Our software can be used to generate collections of synthetic reads that reflect the diverse taxonomical composition of typical metagenome data sets. Based on a database of given genomes, the program allows the user to design a metagenome by specifying the number of genomes present at different levels of the NCBI taxonomy, and then to collect reads from the metagenome using a simulation of a number of different sequencing technologies. A population sampler optionally produces evolved sequences based on source genomes and a given evolutionary tree.Conclusions/Significance
MetaSim 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. 相似文献10.
Background
Metagenomics has a great potential to discover previously unattainable information about microbial communities. An important prerequisite for such discoveries is to accurately estimate the composition of microbial communities. Most of prevalent homology-based approaches utilize solely the results of an alignment tool such as BLAST, limiting their estimation accuracy to high ranks of the taxonomy tree.Results
We developed a new homology-based approach called Taxonomic Analysis by Elimination and Correction (TAEC), which utilizes the similarity in the genomic sequence in addition to the result of an alignment tool. The proposed method is comprehensively tested on various simulated benchmark datasets of diverse complexity of microbial structure. Compared with other available methods designed for estimating taxonomic composition at a relatively low taxonomic rank, TAEC demonstrates greater accuracy in quantification of genomes in a given microbial sample. We also applied TAEC on two real metagenomic datasets, oral cavity dataset and Crohn’s disease dataset. Our results, while agreeing with previous findings at higher ranks of the taxonomy tree, provide accurate estimation of taxonomic compositions at the species/strain level, narrowing down which species/strains need more attention in the study of oral cavity and the Crohn’s disease.Conclusions
By taking account of the similarity in the genomic sequence TAEC outperforms other available tools in estimating taxonomic composition at a very low rank, especially when closely related species/strains exist in a metagenomic sample.Electronic supplementary material
The online version of this article (doi:10.1186/1471-2105-15-242) contains supplementary material, which is available to authorized users. 相似文献11.
12.
Background
Metagenomics is a powerful methodology to study microbial communities, but it is highly dependent on nucleotide sequence similarity searching against sequence databases. Metagenomic analyses with next-generation sequencing technologies produce enormous numbers of reads from microbial communities, and many reads are derived from microbes whose genomes have not yet been sequenced, limiting the usefulness of existing sequence similarity search tools. Therefore, there is a clear need for a sequence similarity search tool that can rapidly detect weak similarity in large datasets.Results
We developed a tool, which we named CLAST (CUDA implemented large-scale alignment search tool), that enables analyses of millions of reads and thousands of reference genome sequences, and runs on NVIDIA Fermi architecture graphics processing units. CLAST has four main advantages over existing alignment tools. First, CLAST was capable of identifying sequence similarities ~80.8 times faster than BLAST and 9.6 times faster than BLAT. Second, CLAST executes global alignment as the default (local alignment is also an option), enabling CLAST to assign reads to taxonomic and functional groups based on evolutionarily distant nucleotide sequences with high accuracy. Third, CLAST does not need a preprocessed sequence database like Burrows–Wheeler Transform-based tools, and this enables CLAST to incorporate large, frequently updated sequence databases. Fourth, CLAST requires <2 GB of main memory, making it possible to run CLAST on a standard desktop computer or server node.Conclusions
CLAST achieved very high speed (similar to the Burrows–Wheeler Transform-based Bowtie 2 for long reads) and sensitivity (equal to BLAST, BLAT, and FR-HIT) without the need for extensive database preprocessing or a specialized computing platform. Our results demonstrate that CLAST has the potential to be one of the most powerful and realistic approaches to analyze the massive amount of sequence data from next-generation sequencing technologies.Electronic supplementary material
The online version of this article (doi:10.1186/s12859-014-0406-y) contains supplementary material, which is available to authorized users. 相似文献13.
Ludmila A. Kasatkina Vitaliy P. Gumenyuk Eva M. Sturm Akos Heinemann Tytus Bernas Irene O. Trikash 《Biochimica et Biophysica Acta (BBA)/General Subjects》2018,1862(12):2701-2713
Background
Neurosecretion is the multistep process occurring in separate spatial and temporal cellular boundaries which complicates its comprehensive analysis. Most of the research are focused on one distinct stage of synaptic vesicle recycling. Here, we describe approaches for complex analysis of synaptic vesicle (SV) endocytosis and separate steps of exocytosis at the level of presynaptic bouton and highly purified SVs.Methods
Proposed fluorescence-based strategies and analysis of neurotransmitter transport provided the advantages in studies of exocytosis steps. We evaluated SV docking/tethering, their Ca2+-dependent fusion and release of neurotransmitters gamma-aminobutyric acid (GABA) and glutamate in two animal models.Results
Approaches enabled us to study: 1) endocytosis/Ca2+-dependent release of fluorescent carbon nanodots (CNDs) during stimulation of nerve terminals; 2) the action of levetiracetam, modulator of SV glycoprotein SV2, on fusion competence of SVs and stimulated release of GABA and glutamate; 3) impairments of several steps of neurosecretion under vitamin D3 deficiency.Conclusions
Our algorithm enabled us to verify the method validity for multidimensional analysis of SV turnover. By increasing SV docking and the size of readily releasable pool (RRP), levetiracetam is able to selectively enhance the stimulated GABA secretion in hippocampal neurons. Findings suggest that SV2 regulates RRP through impact on the number of docked/primed SVs.General significance
Methodology can be widely applied to study the stimulated neurosecretion in presynapse, regulation of SV docking, their Ca2+-dependent fusion with target membranes, quantitative analysis of expression of neuron-specific proteins, as well as for testing the efficiency of pre-selected designed neuroactive substances. 相似文献14.
15.
Background
The correct taxonomic assignment of bacterial genomes is a primary and challenging task. With the availability of whole genome sequences, the gene content based approaches appear promising in inferring the bacterial taxonomy. The complete genome sequencing of a bacterial genome often reveals a substantial number of unique genes present only in that genome which can be used for its taxonomic classification.Results
In this study, we have proposed a comprehensive method which uses the taxon-specific genes for the correct taxonomic assignment of existing and new bacterial genomes. The taxon-specific genes identified at each taxonomic rank have been successfully used for the taxonomic classification of 2,342 genomes present in the NCBI genomes, 36 newly sequenced genomes, and 17 genomes for which the complete taxonomy is not yet known. This approach has been implemented for the development of a tool ‘Microtaxi’ which can be used for the taxonomic assignment of complete bacterial genomes.Conclusion
The taxon-specific gene based approach provides an alternate valuable methodology to carry out the taxonomic classification of newly sequenced or existing bacterial genomes.Electronic supplementary material
The online version of this article (doi:10.1186/s12864-015-1542-0) contains supplementary material, which is available to authorized users. 相似文献16.
Background
Genome assembly is typically a two-stage process: contig assembly followed by the use of paired sequencing reads to join contigs into scaffolds. Scaffolds are usually the focus of reported assembly statistics; longer scaffolds greatly facilitate the use of genome sequences in downstream analyses, and it is appealing to present larger numbers as metrics of assembly performance. However, scaffolds are highly prone to errors, especially when generated using short reads, which can directly result in inflated assembly statistics.Results
Here we provide the first independent evaluation of scaffolding tools for second-generation sequencing data. We find large variations in the quality of results depending on the tool and dataset used. Even extremely simple test cases of perfect input, constructed to elucidate the behaviour of each algorithm, produced some surprising results. We further dissect the performance of the scaffolders using real and simulated sequencing data derived from the genomes of Staphylococcus aureus, Rhodobacter sphaeroides, Plasmodium falciparum and Homo sapiens. The results from simulated data are of high quality, with several of the tools producing perfect output. However, at least 10% of joins remains unidentified when using real data.Conclusions
The scaffolders vary in their usability, speed and number of correct and missed joins made between contigs. Results from real data highlight opportunities for further improvements of the tools. Overall, SGA, SOPRA and SSPACE generally outperform the other tools on our datasets. However, the quality of the results is highly dependent on the read mapper and genome complexity. 相似文献17.
Background
Evidence about relevant outcomes is required in the evaluation of clinical interventions for children with autism spectrum disorders (ASD). However, to date, the variety of outcome measurement tools being used, and lack of knowledge about the measurement properties of some, compromise conclusions regarding the most effective interventions.Objectives
This two-stage systematic review aimed to identify the tools used in studies evaluating interventions for anxiety for high-functioning children with ASD in middle childhood, and then to evaluate the tools for their appropriateness and measurement properties.Methods
Electronic databases including Medline, PsychInfo, Embase, and the Cochrane database and registers were searched for anxiety intervention studies for children with ASD in middle childhood. Articles examining the measurement properties of the tools used were then searched for using a methodological filter in PubMed, and the quality of the papers evaluated using the COSMIN checklist.Results
Ten intervention studies were identified in which six tools measuring anxiety and one of overall symptom change were used as primary outcomes. One further tool was included as it is recommended for standard use in UK children''s mental health services. Sixty three articles on the properties of the tools were evaluated for the quality of evidence, and the quality of the measurement properties of each tool was summarised.Conclusions
Overall three questionnaires were found robust in their measurement properties, the Spence Children''s Anxiety Scale, its revised version – the Revised Children''s Anxiety and Depression Scale, and also the Screen for Child Anxiety Related Emotional Disorders. Crucially the articles on measurement properties provided almost no evidence on responsiveness to change, nor on the validity of use of the tools for evaluation of interventions for children with ASD.PROSPERO Registration number
CRD42012002684. 相似文献18.
Background
The rapid accumulation of whole-genome data has renewed interest in the study of using gene-order data for phylogenetic analyses and ancestral reconstruction. Current software and web servers typically do not support duplication and loss events along with rearrangements.Results
MLGO (Maximum Likelihood for Gene-Order Analysis) is a web tool for the reconstruction of phylogeny and/or ancestral genomes from gene-order data. MLGO is based on likelihood computation and shows advantages over existing methods in terms of accuracy, scalability and flexibility.Conclusions
To the best of our knowledge, it is the first web tool for analysis of large-scale genomic changes including not only rearrangements but also gene insertions, deletions and duplications. The web tool is available from http://www.geneorder.org/server.php. 相似文献19.
Shaw SY Lorway RR Deering KN Avery L Mohan HL Bhattacharjee P Reza-Paul S Isac S Ramesh BM Washington R Moses S Blanchard JF 《PloS one》2012,7(3):e31705
Objectives
There is a lack of information on sexual violence (SV) among men who have sex with men and transgendered individuals (MSM-T) in southern India. As SV has been associated with HIV vulnerability, this study examined health related behaviours and practices associated with SV among MSM-T.Design
Data were from cross-sectional surveys from four districts in Karnataka, India.Methods
Multivariable logistic regression models were constructed to examine factors related to SV. Multivariable negative binomial regression models examined the association between physician visits and SV.Results
A total of 543 MSM-T were included in the study. Prevalence of SV was 18% in the past year. HIV prevalence among those reporting SV was 20%, compared to 12% among those not reporting SV (p = .104). In multivariable models, and among sex workers, those reporting SV were more likely to report anal sex with 5+ casual sex partners in the past week (AOR: 4.1; 95%CI: 1.2–14.3, p = .029). Increased physician visits among those reporting SV was reported only for those involved in sex work (ARR: 1.7; 95%CI: 1.1–2.7, p = .012).Conclusions
These results demonstrate high levels of SV among MSM-T populations, highlighting the importance of integrating interventions to reduce violence as part of HIV prevention programs and health services. 相似文献20.
Min Wang Christine R Beck Adam C English Qingchang Meng Christian Buhay Yi Han Harsha V Doddapaneni Fuli Yu Eric Boerwinkle James R Lupski Donna M Muzny Richard A Gibbs 《BMC genomics》2015,16(1)