New Methods For Haplotyping And De Novo Assembly Of Genomes And Metagenomes

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New Methods for Haplotyping and de Novo Assembly of Genomes and Metagenomes

Author : Joshua N. Burton
Publisher :
ISBN 13 :
Total Pages : 212 pages
Book Rating : 4.:/5 (94 download)

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Book Synopsis New Methods for Haplotyping and de Novo Assembly of Genomes and Metagenomes by : Joshua N. Burton

Download or read book New Methods for Haplotyping and de Novo Assembly of Genomes and Metagenomes written by Joshua N. Burton and published by . This book was released on 2014 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: The study of genomics is made possible by the creation of genome assemblies: strings of sequences that represent the DNA content of a species, or an individual within a species. However, genome assemblies do not spring fully formed from DNA sequencing machines. Sequencing produces small fragments of DNA, and these fragments must be combined into a prediction of an organism's genome by a process called de novo assembly. The advent of "next-generation" DNA sequencing technologies over the past decade has vastly increased our capacity to sequence new genomes, but it has exacerbated the difficulty of de novo assembly, turning it into one of the foremost challenges in computational biology today. Especially problematic is the short length of many next-generation reads, which deprives genome assemblies of crucial information about sequence contiguity. Here I describe new methods for creating high-contiguity genome assemblies from short next-generation reads. I demonstrate that novel proper library preparation can create short reads that retain long-range contiguity information, and I develop novel algorithms to exploit this information for de novo genome assembly. First, I introduce the concept of using Hi-C for de novo genome assembly. I demonstrate that Hi-C produces signals of genomic contiguity that can be used for chromosome-scale scaffolding of de novo genome assemblies. Secondly, I show that Hi-C can also be used for metagenomic deconvolution. Finally, I use fosmid clone pools and copy number analysis to perform haplotype resolution on the genome of the famous HeLa cancer cell line. These approaches allow us to make productive use of the continual advances in next-generation sequencing and will improve standards for genome assemblies.

Haplotyping

Author : Brock A. Peters
Publisher : Springer Nature
ISBN 13 : 1071628194
Total Pages : 304 pages
Book Rating : 4.0/5 (716 download)

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Book Synopsis Haplotyping by : Brock A. Peters

Download or read book Haplotyping written by Brock A. Peters and published by Springer Nature. This book was released on 2022-11-06 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to be an introduction to haplotype information for both the wet and dry labs. Chapters detail co-barcoding and linked-reads based methods, third generation sequencing based methods, Hi-C based methods, single-cell and Strand-seq, and methods for using haplotype data once obtained. Written in the successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible protocols, and notes on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Haplotyping: Methods and Protocols aims to provide compréhensive and accessible methods to undergraduate, graduate, and established scientists.

Computational Methods for Next Generation Sequencing Data Analysis

Author : Ion Mandoiu
Publisher : John Wiley & Sons
ISBN 13 : 1119272165
Total Pages : 464 pages
Book Rating : 4.1/5 (192 download)

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Book Synopsis Computational Methods for Next Generation Sequencing Data Analysis by : Ion Mandoiu

Download or read book Computational Methods for Next Generation Sequencing Data Analysis written by Ion Mandoiu and published by John Wiley & Sons. This book was released on 2016-09-12 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces readers to core algorithmic techniques for next-generation sequencing (NGS) data analysis and discusses a wide range of computational techniques and applications This book provides an in-depth survey of some of the recent developments in NGS and discusses mathematical and computational challenges in various application areas of NGS technologies. The 18 chapters featured in this book have been authored by bioinformatics experts and represent the latest work in leading labs actively contributing to the fast-growing field of NGS. The book is divided into four parts: Part I focuses on computing and experimental infrastructure for NGS analysis, including chapters on cloud computing, modular pipelines for metabolic pathway reconstruction, pooling strategies for massive viral sequencing, and high-fidelity sequencing protocols. Part II concentrates on analysis of DNA sequencing data, covering the classic scaffolding problem, detection of genomic variants, including insertions and deletions, and analysis of DNA methylation sequencing data. Part III is devoted to analysis of RNA-seq data. This part discusses algorithms and compares software tools for transcriptome assembly along with methods for detection of alternative splicing and tools for transcriptome quantification and differential expression analysis. Part IV explores computational tools for NGS applications in microbiomics, including a discussion on error correction of NGS reads from viral populations, methods for viral quasispecies reconstruction, and a survey of state-of-the-art methods and future trends in microbiome analysis. Computational Methods for Next Generation Sequencing Data Analysis: Reviews computational techniques such as new combinatorial optimization methods, data structures, high performance computing, machine learning, and inference algorithms Discusses the mathematical and computational challenges in NGS technologies Covers NGS error correction, de novo genome transcriptome assembly, variant detection from NGS reads, and more This text is a reference for biomedical professionals interested in expanding their knowledge of computational techniques for NGS data analysis. The book is also useful for graduate and post-graduate students in bioinformatics.

Computational Methods for Haplotype-aware De Novo Genome Assembly from Long Reads

Author : Xiao Luo
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (137 download)

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Book Synopsis Computational Methods for Haplotype-aware De Novo Genome Assembly from Long Reads by : Xiao Luo

Download or read book Computational Methods for Haplotype-aware De Novo Genome Assembly from Long Reads written by Xiao Luo and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Scalable Methods for Genome Assembly

Author : Priyanka Ghosh
Publisher :
ISBN 13 :
Total Pages : 155 pages
Book Rating : 4.:/5 (113 download)

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Book Synopsis Scalable Methods for Genome Assembly by : Priyanka Ghosh

Download or read book Scalable Methods for Genome Assembly written by Priyanka Ghosh and published by . This book was released on 2019 with total page 155 pages. Available in PDF, EPUB and Kindle. Book excerpt: De novo genome assembly is a fundamental problem in the field of computational biology. The goal is to reconstruct an unknown genome from short DNA fragments (called "reads") obtained from it. Over the last decade, with the advent of numerous next-generation sequencing (NGS) platforms (e.g., Illumina, 454 Roche), billions of reads can be generated in a matter of hours, leading to vast amounts of data accumulation per day. This has necessitated efficient parallelization of the assembly process to meet the growing data demands. While multiple parallel solutions to the problem have been proposed in the past, there still exists a gap in terms of the processing power between massively parallel NGS technologies and the ability of current state-of-the-art assemblers to analyze and assemble large and complex genomes. Conducting genome assembly at scale remains a challenge owing to the intense computational and memory requirements of the problem, coupled with inherent complexities in existing parallel tools associated with data movement, use of complex data structures, unstructured memory accesses and repeated I/O operations. In this dissertation, we address the challenges of conducting genome assembly at scale and develop new methods for conducting extreme-scale genome assembly for microbial and complex eukaryotic genomes. Our approach to the problem is two-fold, wherein we make the following contributions: i) FastEtch- a new method targeting fast and space-efficient assemblies, using probabilistic data structures (Count-Min sketch) that executes efficiently on shared-memory platforms with a minimal computational footprint (both memory and time). ii) PaKman- a fully distributed method that tackles assembly of large genomes through the combination of a novel data-structure (PaK-Graph) and algorithmic strategies to simplify the communication and I/O footprint during the assembly process. We present an extensive performance and qualitative evaluation of both our algorithms including comparisons to other state-of-the-art methods. Our results demonstrate that FastEtch can yield one of the best time-memory-quality trade-offs, when compared against many state-of-the-art genome assemblers. PaKman has shown the ability to achieve near-linear speedups on up to 8K cores; outperform state-of-the-art distributed and shared memory tools in performance while delivering comparable (if not better) quality; and reduce time to solution significantly.

De Novo Methods for Characterizing Diversity in Populations of Genomes Using Next-generation Sequencing Data

Author : Raunaq Malhotra
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (959 download)

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Book Synopsis De Novo Methods for Characterizing Diversity in Populations of Genomes Using Next-generation Sequencing Data by : Raunaq Malhotra

Download or read book De Novo Methods for Characterizing Diversity in Populations of Genomes Using Next-generation Sequencing Data written by Raunaq Malhotra and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Next-generation sequencing (NGS) technologies have enabled fast profiling of diversity in population of closely related genomes over the past two decades in a high throughput fashion. Examples of such applications include reconstructing the haplotypes of viruses replicating within a host, identifying insertional polymorphisms of mobile elements amongst individuals in a species, and characterizing diversity in populations of cancer cell types in an individual. Although a plethora of methods use an existing or assembled reference sequence for characterizing diversity, the usage of de novo methods can be beneficial for studying diversity in a population of closely related genomes. This dissertation aims to develop de novo computational methods for studying diversity in such samples using NGS data. De novo methods rely only on the inherent NGS data collected from a sample and can be applied to study the diversity in organisms where limited prior knowledge is available. In the first part of the dissertation, I discuss a clustering pipeline for clustering NGS data that was obtained from sites of integration of a mobile element in the genome in a panel of individuals. Typically, reads from individuals can be mapped to a reference genome to determine the location of an element-host integration site. However, host regions flanking a mobile element can be modified by the presence of the element and reference genomes are not available for all species. Clustering methods provide an alternative for analyzing such integration site datasets. Here, each cluster ideally represents reads from a single integration site. The main contributions in this chapter are (i) A pipeline for clustering NGS reads from integration site junctions using UCLUST clustering algorithm that empirically determines the optimal clustering threshold; (ii) The optimal threshold is determined based on internal clustering measure, $I-index$, which assesses clusters for small intra-cluster diameters and large inter-cluster distance. We evaluate and test our proposed pipeline to determine the optimal clustering parameters and show improved results on simulated and real datasets. The second and major portion of the dissertation focuses on de novo reconstruction of viral haplotypes in a viral population using paired-end NGS data. We have proposed MLEHaplo, a maximum likelihood de novo assembly algorithm for reconstructing viral haplotypes. Using the pairing information of reads in our proposed Viral Path Reconstruction Algorithm (ViPRA), we generate a small subset of paths from a De Bruijn graph of reads that serve as candidate paths for true viral haplotypes. Our proposed method MLEHaplo then generates a maximum likelihood estimate of the viral population using the paths reconstructed by ViPRA. We evaluate and compare MLEHaplo on simulated datasets at different sequence coverage, and on real datasets. MLEHaplo reconstructs full length viral haplotypes in most of the small genome simulated viral populations. While reference based methods either under-estimate or over-estimate the viral haplotypes, MLEHaplo limits the over-estimation of the size of true viral haplotypes, and reconstructs the full phylogeny of the input viral population. As NGS data is fraught with sequencing errors which significantly impact de novo reconstruction of viral haplotypes, in Chapter 4 we proposed a frame-based representation of k-mers for detecting sequencing errors and rare variants for such data. Frames are sets of non-orthogonal basis functions, traditionally used in signal processing for noise removal. We define a frame for genomes and sequenced reads to consist of discrete spatial signals of every k-mer of a given size. We show that each k-mer in the sequenced data can be projected onto multiple frames and these projections are maximized for spatial signals corresponding to the k-mer's substrings. Our proposed classifier, MultiRes, is trained on the projections of k-mers as features used for marking k-mers as erroneous or true variations in the genome. We evaluate MultiRes on simulated and real viral population datasets and compare it to other error correction methods known in the literature. MultiRes has 4 to 500 times less false positive k-mer predictions compared to other methods, essential for accurate estimation of viral population diversity and their de novo assembly. It has high recall of the true k-mers, comparable to other error correction methods. MultiRes also has greater than 95% recall for detecting single nucleotide polymorphisms (SNPs), has low false positive SNP predictions, while detecting higher number of rare variants compared to other variant calling methods for viral populations.

De Novo Approaches to Haplotype-aware Genome Assembly

Author :
Publisher :
ISBN 13 : 9789463237437
Total Pages : 131 pages
Book Rating : 4.2/5 (374 download)

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Book Synopsis De Novo Approaches to Haplotype-aware Genome Assembly by :

Download or read book De Novo Approaches to Haplotype-aware Genome Assembly written by and published by . This book was released on 2019 with total page 131 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Scalable Parallel Algorithms for Genome Analysis

Author : Evangelos Georganas
Publisher :
ISBN 13 :
Total Pages : 129 pages
Book Rating : 4.:/5 (972 download)

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Book Synopsis Scalable Parallel Algorithms for Genome Analysis by : Evangelos Georganas

Download or read book Scalable Parallel Algorithms for Genome Analysis written by Evangelos Georganas and published by . This book was released on 2016 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt: A critical problem for computational genomics is the problem of de novo genome assembly: the development of robust scalable methods for transforming short randomly sampled "shotgun" sequences, namely reads, into the contiguous and accurate reconstruction of complex genomes. These reads are significantly shorter (e.g. hundreds of bases long) than the size of chromosomes and also include errors. While advanced methods exist for assembling the small and haploid genomes of prokaryotes, the genomes of eukaryotes are more complex. Moreover, de novo assembly has been unable to keep pace with the flood of data, due to the dramatic increases in genome sequencer capabilities, combined with the computational requirements and the algorithmic complexity of assembling large scale genomes and metagenomes. In this dissertation, we address this challenge head on by developing parallel algorithms for de novo genome assembly with the ambition to scale to massive concurrencies. Our work is based on the Meraculous assembler, a state-of-the-art de novo assembler for short reads developed at JGI. Meraculous identifies non-erroneous overlapping substrings of length k (k-mers) with high quality extensions and uniquely assembles genome regions into uncontested sequences called contigs by constructing and traversing a de Bruijn graph of k-mers, a special graph that is used to represent overlaps among k-mers. The original reads are subsequently aligned onto the contigs to obtain information regarding the relative orientation of the contigs. Contigs are then linked together to create scaffolds, sequences of contigs that may contain gaps among them. Finally gaps are filled using localized assemblies based on the original reads. First, we design efficient scalable algorithms for k-mer analysis and contig generation. K-mer analysis is characterized by intensive communication and I/O requirements and our parallel algorithms successfully reduce the memory requirements by 7×. Then, contig generation relies on efficient parallelization of the de Bruijn graph construction and traversal, which necessitates a distributed hash table and is a key component of most de novo assemblers. We present a novel algorithm that leverages one-sided communication capabilities of the UPC to facilitate the requisite fine-grained, irregular parallelism and the avoidance of data hazards. The sequence alignment is characterized by intensive I/O and large computation requirements. We introduce mer-Aligner, a highly parallel sequence aligner that employs parallelism in all of its components. Finally, this thesis details the parallelization of the scaffolding modules, enabling the first massively scalable, high quality, complete end-to-end de novo assembly pipeline. Experimental large-scale results using human and wheat genomes demonstrate efficient performance and scalability on thousands of cores. Compared to the original Meraculous code, which requires approximately 48 hours to assemble the human genome, our pipeline called HipMer computes the assembly in only 4 minutes using 23,040 cores of Edison - an overall speedup of approximately 720×. In the last part of the dissertation we tackle the problem of metagenome assembly. Metagenomics is currently the leading technology to study the uncultured microbial diversity. While accessing an unprecedented number of environmental samples that consist of thousands of individual microbial genomes is now possible, the bottleneck is becoming computational, since the sequencing cost improvements exceed that of Moore's Law. Metagenome assembly is further complicated by repeated sequences across genomes, polymorphisms within a species and variable frequency of the genomes within the sample. In our work we repurpose HipMer components for the problem of metagenome assembly and we design a versatile, high-performance metagenome assembly pipeline that outperforms state-of-the-art tools in both quality and performance.

De Novo Repeats Construction: Methods and Applications

Author : Chong Chu
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (119 download)

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Book Synopsis De Novo Repeats Construction: Methods and Applications by : Chong Chu

Download or read book De Novo Repeats Construction: Methods and Applications written by Chong Chu and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Repeat elements are important components of eukaryotic genomes. The dropping cost of the second and third generation sequencing technologies provides opportunities to study repeat elements of hundreds of species and thousands of individuals of one species. Based on the quality of the assembled genomes, generally there are two obstacles for studying repeat elements: (1) For species with high repetitive or complex genomes that do not have high quality genomes assembled, how do we construct de novo repeat elements? (2) For species with high quality genomes assembled, how to detect mobile elements insertions (one type of repeat elements) of different individuals of the species? It is known that most of the gaps on draft genomes are caused by repeat elements, thus a following-up question is: (3) With the understanding of repeats on genome, can we better close the gaps on draft genomes? To address the first problem that reference genomes are incomplete and often contain missing data in highly repetitive regions, we propose a method (called REPdenovo) to construct repeats directly from short sequencing reads. REPdenovo can construct various types of repeats that are highly repetitive and have low sequence divergence within copies. We show that REPdenovo is substantially better than existing methods both in terms of the number and the completeness of the repeat sequences that it recovers. The key advantage of REPdenovo is that it can reconstruct long repeats from short sequence reads. We apply the method to human data and discover a number of potentially new repeats sequences that have been missed by previous repeat annotations. Next we present an improved version of REPdenovo, which is able to reconstruct more divergent and lower frequency repeats from short sequencing reads. Comparing with the original REPdenovo, this improved approach uses more repeat-related k-mers. In addition, the new approach improves repeat assembly quality using a consensus-based k-mer processing method. We compare the performance of the new method with REPdenovo and RepARK on Human and Arabidopsis thaliana short sequencing data. The results show that the improved REPdenovo can assemble more complete repeats than REPdenovo (and also RepARK). We apply the improved REPdenovo on Hummingbird which has no known repeat library, and construct many repeat elements that are validated using PacBio long reads. Many of these repeats are likely to be true that are not in public repeat libraries. To answer the second question, we develop a novel method (called REPdenovo-MEI) for detecting mobile element insertions (MEIs) with given reference genome and alignments of different individuals. Different from all existing tools, REPdenovo-MEI does not rely on any repeats library and can call MEIs efficiently and accurately. Besides calling out insertion sites, REPdenovo-MEI has a local assembly step to construct the inserted copy and a classification based approach for calling genotypes. In addition, the third-generation sequencing technology generates long reads of thousands of bases long, which usually is long enough to contain the whole repeat elements in the reads, thus can help to construct the MEIs completely. Thus, besides short reads, REPdenovo-MEI can also work with long reads to infer the inserted copies. Results on both simulated and real data show that REPdenovo-MEI outperforms existing tools on both accuracy and the number of constructed high divergent MEIs. To solve the third problem of closing gaps on draft genomes, we propose a new method (called GAPPadder) that can sensitively close gaps for large and complex genomes. Different from existing approaches, GAPPadder collects more gap originated reads, especially repeat associated reads, and better utilize the information of different insert sizes of PE and MP reads. Finally, GAPPadder provides higher quality of local assembly with an extra contigs merging step. We show GAPPadder can close more gaps on one bacterial genome, Human chromosome 14 and Human whole genome. Besides closing gaps on draft genome assembled only from short sequence reads, GAPPadder can also be used to close gaps for draft genomes assembled with long reads. We show GAPPadder can close gaps on the bed bug genome and the Asian sea bass genome that are assembled partially and fully with long reads respectively. We also show GAPPadder is efficient in both time and memory usage.

Data-efficient De Novo Genome Assembly Algorithm

Author : Ka-Kit Lam
Publisher :
ISBN 13 :
Total Pages : 153 pages
Book Rating : 4.:/5 (957 download)

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Book Synopsis Data-efficient De Novo Genome Assembly Algorithm by : Ka-Kit Lam

Download or read book Data-efficient De Novo Genome Assembly Algorithm written by Ka-Kit Lam and published by . This book was released on 2016 with total page 153 pages. Available in PDF, EPUB and Kindle. Book excerpt: We study data-efficient and also practical de-novo genome assembly algorithm. Due to the advancement in high-throughput sequencing, the cost of read data has gone down rapidly in recent years. Thus, there is a growing need to do genome assembly in a cost effective manner on a large scale. However, the state-of-the-art assemblers are not designed to be data-efficient. This leads to wastage of read data, which translates to a significant monetary loss for large scale sequencing projects. Moreover, as technology advances, the nature of the read data also evolves. This makes the old assemblers insufficient for discovering all the information behind the data. Therefore, there is a need to re-invent genome assemblers to suit the growing demand. In this dissertation, we address the data efficiency aspect of genome assembly as follows. First, we show that even when there is noise in the reads, one can successfully reconstruct the genomes with information requirements close to the noiseless fundamental limit. We develop a new assembly algorithm, X-phased Multibridging, is designed based on a probabilistic model of the genome. We show, through analysis that it performs well on the model, and through simulation that it performs well on real genomes. Second, we introduce FinisherSC, a repeat-aware and scalable tool for upgrading de-novo haploid genome assembly using long and noisy reads. Experiments with real data suggest that FinisherSC can provide longer and higher quality contigs than existing tools while maintaining high concordance. Thus, FinisherSC achieves higher data efficiency than state-of-the-art haploid genome assembly pipelines. Third, we study whether post-processing metagenomic assemblies with the original input long reads can result in quality improvement. Previous approaches have focused on pre-processing reads and optimizing assemblers. We introduce BIGMAC, which takes an alternative perspective to focus on the post-processing step. Using both the assembled contigs and original long reads as input, BIGMAC first breaks the contigs at potentially mis-assembled locations and subsequently scaffolds contigs. Our experiments on metagenomes assembled from long reads show that BIGMAC can improve assembly quality by reducing the number of mis-assemblies while maintaining/increasing N50 and N75. Thus, BIGMAC achieves higher data efficiency than state-of-the-art metagenomic assembly pipelines. Moreover, we also discuss some theoretical work regarding genome assembly in terms of data, time and space efficiency; and a promising post-processing tool POSTME in improving metagenomic assembly using both short and long reads.

Resolving Genome Complexity: Computational and Technological Methods

Author : Matthew Pendleton
Publisher :
ISBN 13 :
Total Pages : 163 pages
Book Rating : 4.:/5 (984 download)

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Book Synopsis Resolving Genome Complexity: Computational and Technological Methods by : Matthew Pendleton

Download or read book Resolving Genome Complexity: Computational and Technological Methods written by Matthew Pendleton and published by . This book was released on 2017 with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the post-human genome era we have amassed endless genome sequencing data, but our ability to address variation between genomes has been largely restricted to small indels and single nucleotide variations. More complex regions of the genome, such as highly repetitive regions or those containing structural variation, have been largely ignored. This proposal aims to help elucidate these regions via a combination of computational and experimental approaches.First, we seek to build computational tools for identifying and computing large genomic differences by taking advantage of “third-generation” DNA sequencing technologies. This is done, in part, using a novel structural variation tool which uses a systematic framework for interrogating sequence “dot plots” (or groups of sequence “dot plots”) which have been historically used for visual identification of genome rearrangements, especially for complex comparative genomics. We combine these approaches with established tools for identifying single nucleotide variations (SNVs), to calculate multi-event co-variance in two constrained cancer projects: HCV viral quasispecies analysis in liver cancer, and FLT3 tyrosine kinase variation in acute myelogenous leukemia (AML). We then apply and extend these methods (along with existing methods for assembly, scaffolding, and phasing) in the context of the first amplification-free, diploid human genome assembly. In addition to enumerating far more structural variation than has been previously seen, this work provides the first human assembly that combines single molecule real time sequencing on Pacific BioSciences’ SMRT RT II sequencing platform with optical mapping generated by BioNano Genomics Irys mapping system. This hybrid strategy results in a de novo assembled genome that approaches reference quality.Second, to target the most complicated regions of the genome, we propose a pair of new amplification-free enrichment technologies. One approach combines an old mainstay of human genomics, the pulsed field gel electrophoresis, with the power of RNA guided cas9 endonuclease to enable enrichment of high molecular weight DNA from genome intervals that are difficult to manipulate with BAC cloning methods. The other approach employs an inactivated Cas9 protein engineered to permit bead based pull-down of a targeted region. We believe these approaches fill-in a needed gap, where resolution of structural variants, unambiguous haplotypic resolution and complete assembly would be impossible with existing targeting approaches but prohibitively expensive using high depth, long read whole genome sequencing.

LARGE GENOME DE NOVO ASSEMBLY

Author : Binghang Liu
Publisher : Open Dissertation Press
ISBN 13 : 9781361033463
Total Pages : 62 pages
Book Rating : 4.0/5 (334 download)

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Book Synopsis LARGE GENOME DE NOVO ASSEMBLY by : Binghang Liu

Download or read book LARGE GENOME DE NOVO ASSEMBLY written by Binghang Liu and published by Open Dissertation Press. This book was released on 2017-01-26 with total page 62 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation, "Large Genome De Novo Assembly With Bi-directional BWT" by Binghang, Liu, 劉兵行, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: De novo genome assembly is a fundamental problem in genomics research. When assembling large genomes, time is often a very important concern, and one might have no choice but to use a more efficient assembler like SOAPden-ovo2 instead of a high-quality but prohibitively slow assembler (e.g., SPAdes). Yet SOAPdenovo2 has inherent difficulty to utilize the full advantage of longer reads (say, 150bp to 250bp from Illumina HiSeq and MiSeq). Other assemblers that are based on string graphs (e.g., SGA), though less popular and also very slow, are indeed more favorable for longer reads. In this thesis, I mainly present a new contig assembler called BASE, based on a seed-extension approach. It exploits an efficient indexing of reads to generate adaptive seeds with high probability of unique appearance in the genome and high sequencing quality. Guided by these seeds, BASE constructs extension trees and gradually removes the branches with a method called reverse validation, which utilizes information about read coverage and paired-end relationship to obtain consensus sequences of reads sharing the seeds. These consensus sequences are further extended to form high quality contigs. Benchmark on several bacteria and human datasets demonstrates the performance advantage of BASE in speed and assembly quality when longer reads are used. Our first benchmark was based on two datasets of deeply sequenced bacteria genomes (240X) with read length of 100bp and 250bp. Especially for 250bp reads, BASE performs much better than SOAPdenovo2 and SGA and is similar to SPAdes in performance. Regarding speed, BASE is consistently a few times faster than SPAdes and SGA, but still slower than SOAPdenovo2. We have further compared BASE and SOAPdenovo2 using human genome datasets with read length 100bp, 150bp and 250bp. BASE consistently achieves a higher N50 for all datasets; while the improvement becomes more significant when read length reaches 250bp. SOAPdenovo2 uses relatively more memory when sequencing error is high. BASE is an efficient assembler for contig construction, with significant improvement in quality for long NGS reads. It could be easily extended to support scaffolding in the near future. Subjects: Nucleotide sequence - Data processing Data compression (Computer science)

Functional Metagenomics: Tools and Applications

Author : Trevor C. Charles
Publisher : Springer
ISBN 13 : 3319615106
Total Pages : 256 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Functional Metagenomics: Tools and Applications by : Trevor C. Charles

Download or read book Functional Metagenomics: Tools and Applications written by Trevor C. Charles and published by Springer. This book was released on 2017-10-09 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, the latest tools available for functional metagenomics research are described.This research enables scientists to directly access the genomes from diverse microbial genomes at one time and study these “metagenomes”. Using the modern tools of genome sequencing and cloning, researchers have now been able to harness this astounding metagenomic diversity to understand and exploit the diverse functions of microorganisms. Leading scientists from around the world demonstrate how these approaches have been applied in many different settings, including aquatic and terrestrial habitats, microbiomes, and many more environments. This is a highly informative and carefully presented book, providing microbiologists with a summary of the latest functional metagenomics literature on all specific habitats.

Genome-Scale Algorithm Design

Author : Veli Mäkinen
Publisher : Cambridge University Press
ISBN 13 : 1009341219
Total Pages : 470 pages
Book Rating : 4.0/5 (93 download)

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Book Synopsis Genome-Scale Algorithm Design by : Veli Mäkinen

Download or read book Genome-Scale Algorithm Design written by Veli Mäkinen and published by Cambridge University Press. This book was released on 2023-10-12 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: Guided by standard bioscience workflows in high-throughput sequencing analysis, this book for graduate students, researchers, and professionals in bioinformatics and computer science offers a unified presentation of genome-scale algorithms. This new edition covers the use of minimizers and other advanced data structures in pangenomics approaches.

Biological Sequence Analysis

Author : Richard Durbin
Publisher : Cambridge University Press
ISBN 13 : 113945739X
Total Pages : 372 pages
Book Rating : 4.1/5 (394 download)

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Book Synopsis Biological Sequence Analysis by : Richard Durbin

Download or read book Biological Sequence Analysis written by Richard Durbin and published by Cambridge University Press. This book was released on 1998-04-23 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probabilistic models are becoming increasingly important in analysing the huge amount of data being produced by large-scale DNA-sequencing efforts such as the Human Genome Project. For example, hidden Markov models are used for analysing biological sequences, linguistic-grammar-based probabilistic models for identifying RNA secondary structure, and probabilistic evolutionary models for inferring phylogenies of sequences from different organisms. This book gives a unified, up-to-date and self-contained account, with a Bayesian slant, of such methods, and more generally to probabilistic methods of sequence analysis. Written by an interdisciplinary team of authors, it aims to be accessible to molecular biologists, computer scientists, and mathematicians with no formal knowledge of the other fields, and at the same time present the state-of-the-art in this new and highly important field.

A Tale of Three Next Generation Sequencing Platforms

Author : Applied Research Press
Publisher : Createspace Independent Publishing Platform
ISBN 13 : 9781515216209
Total Pages : 42 pages
Book Rating : 4.2/5 (162 download)

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Book Synopsis A Tale of Three Next Generation Sequencing Platforms by : Applied Research Press

Download or read book A Tale of Three Next Generation Sequencing Platforms written by Applied Research Press and published by Createspace Independent Publishing Platform. This book was released on 2015-07-24 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt: Next generation sequencing (NGS) technology has revolutionized genomic and genetic research. The pace of change in this area is rapid with three major new sequencing platforms having been released in 2011: Ion Torrent's PGM, Pacific Biosciences' RS and the Illumina MiSeq. Here we compare the results obtained with those platforms to the performance of the Illumina HiSeq, the current market leader. In order to compare these platforms, and get sufficient coverage depth to allow meaningful analysis, we have sequenced a set of 4 microbial genomes with mean GC content ranging from 19.3 to 67.7%. Together, these represent a comprehensive range of genome content. Here we report our analysis of that sequence data in terms of coverage distribution, bias, GC distribution, variant detection and accuracy. All three fast turnaround sequencers evaluated here were able to generate usable sequence. However there are key differences between the quality of that data and the applications it will support. Proceeds from the sale of this book go to the support of an elderly disabled person.

A New Algorithm for de Novo Genome Assembly

Author : Md. Bahlul Haider
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (16 download)

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Book Synopsis A New Algorithm for de Novo Genome Assembly by : Md. Bahlul Haider

Download or read book A New Algorithm for de Novo Genome Assembly written by Md. Bahlul Haider and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The enormous amount of short reads produced by next generation sequencing (NGS) techniques such as Roche/454, Illumina/Solexa and SOLiD sequencing opened the possibility of de novo genome assembly. Some of the de novo genome assemblers (e.g., Edena, SGA) use an overlap graph approach to assemble a genome, while others (e.g., ABySS and SOAPdenovo) use a de Bruijn graph approach. Currently, the approaches based on the de Bruijn graph are the most successful, yet their performance is far from being able to assemble entire genomic sequences. We developed a new overlap graph based genome assembler called Paired-End Genome ASsembly Using Short-sequences (PEGASUS) for paired-end short reads produced by NGS techniques. PEGASUS uses a minimum cost network flow approach to predict the copy count of the input reads more precisely than other algorithms. With the help of accurate copy count and mate pair support, PEGASUS can accurately unscramble the paths in the overlap graph that correspond to DNA sequences. PEGASUS exhibits comparable and in many cases better performance than the leading genome assemblers.