<i>De novo</i> meta-assembly of ultra-deep sequencing data

Mirebrahim, Hamid; Close, Timothy J.; Lonardi, Stefano

doi:10.1093/bioinformatics/btv226

Cited by 25 publications

(13 citation statements)

References 26 publications

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“…However, consistent with our exploratory analysis here, some studies suggest that greater depth does not necessarily afford more contiguous assemblies and that ultra-deep sequencing (>1000× coverage) may actually be counterproductive if not explicitly handled using specialized assembly algorithms [171,172], due, in part, to the amplification of read duplication events and other sequencing errors [56]. From a practical standpoint, even if pre-processing steps successfully address the issues associated with ultra-deep sequencing, the significantly compounded cost of 10× more sequencing depth may not translate to greater information.…”

Section: Challenges In Biosynthetic Pathway Assembly and Product Psupporting

confidence: 73%

Interpreting Microbial Biosynthesis in the Genomic Age: Biological and Practical Considerations

2017

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Genome mining has become an increasingly powerful, scalable, and economically accessible tool for the study of natural product biosynthesis and drug discovery. However, there remain important biological and practical problems that can complicate or obscure biosynthetic analysis in genomic and metagenomic sequencing projects. Here, we focus on limitations of available technology as well as computational and experimental strategies to overcome them. We review the unique challenges and approaches in the study of symbiotic and uncultured systems, as well as those associated with biosynthetic gene cluster (BGC) assembly and product prediction. Finally, to explore sequencing parameters that affect the recovery and contiguity of large and repetitive BGCs assembled de novo, we simulate Illumina and PacBio sequencing of the Salinispora tropica genome focusing on assembly of the salinilactam (slm) BGC.

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Section: Challenges In Biosynthetic Pathway Assembly and Product Psupporting

confidence: 73%

Interpreting Microbial Biosynthesis in the Genomic Age: Biological and Practical Considerations

2017

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“…It was released only shortly before SOAPdenovo2 was published and incorporates SOAPdenovo v1.05 and v1.06 as integral assembly components, using optimized parameters and revised error correction as well as scaffolding steps. SLICEMBLER [55] is a pipeline designed for ultra deep sequencing datasets using a “divide and conquer” approach. The read dataset is evenly divided into subsets, which are then assembled independently using an assembler of choice.…”

Section: Introductionmentioning

confidence: 99%

Comparing and Evaluating Metagenome Assembly Tools from a Microbiologist’s Perspective - Not Only Size Matters!

2017

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With the constant improvement in cost-efficiency and quality of Next Generation Sequencing technologies, shotgun-sequencing approaches -such as metagenomics- have nowadays become the methods of choice for studying and classifying microorganisms from various habitats. The production of data has dramatically increased over the past years and processing and analysis steps are becoming more and more of a bottleneck. Limiting factors are partly the availability of computational resources, but mainly the bioinformatics expertise in establishing and applying appropriate processing and analysis pipelines. Fortunately, a large diversity of specialized software tools is nowadays available. Nevertheless, choosing the most appropriate methods for answering specific biological questions can be rather challenging, especially for non-bioinformaticians. In order to provide a comprehensive overview and guide for the microbiological scientific community, we assessed the most common and freely available metagenome assembly tools with respect to their output statistics, their sensitivity for low abundant community members and variability in resulting community profiles as well as their ease-of-use. In contrast to the highly anticipated "Critical Assessment of Metagenomic Interpretation" (CAMI) challenge, which uses general mock community-based assembler comparison we here tested assemblers on real Illumina metagenome sequencing data from natural communities of varying complexity sampled from forest soil and algal biofilms. Our observations clearly demonstrate that different assembly tools can prove optimal, depending on the sample type, available computational resources and, most importantly, the specific research goal. In addition, we present detailed descriptions of the underlying principles and pitfalls of publically available assembly tools from a microbiologist’s perspective, and provide guidance regarding the user-friendliness, sensitivity and reliability of the resulting phylogenetic profiles.

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“…Also, for both SGVar and SGA-PDBG, there was a bigger loss of precision at 200×, compared with the lower coverage data ( Supplementary Figure S3 ). It has been found that the assembly quality would decrease once the sequencing depth goes too high [ 40–42 ], likely because of the accumulation of uncorrected sequencing errors.…”

Section: Resultsmentioning

confidence: 99%

Comparative analysis of de novo assemblers for variation discovery in personal genomes

Tian

Yan

Klee

et al. 2017

Briefings in Bioinformatics

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Current variant discovery approaches often rely on an initial read mapping to the reference sequence. Their effectiveness is limited by the presence of gaps, potential misassemblies, regions of duplicates with a high-sequence similarity and regions of high-sequence divergence in the reference. Also, mapping-based approaches are less sensitive to large INDELs and complex variations and provide little phase information in personal genomes. A few de novo assemblers have been developed to identify variants through direct variant calling from the assembly graph, micro-assembly and whole-genome assembly, but mainly for whole-genome sequencing (WGS) data. We developed SGVar, a de novo assembly workflow for haplotype-based variant discovery from whole-exome sequencing (WES) data. Using simulated human exome data, we compared SGVar with five variation-aware de novo assemblers and with BWA-MEM together with three haplotype- or local de novo assembly-based callers. SGVar outperforms the other assemblers in sensitivity and tolerance of sequencing errors. We recapitulated the findings on whole-genome and exome data from a Utah residents with Northern and Western European ancestry (CEU) trio, showing that SGVar had high sensitivity both in the highly divergent human leukocyte antigen (HLA) region and in non-HLA regions of chromosome 6. In particular, SGVar is robust to sequencing error, k-mer selection, divergence level and coverage depth. Unlike mapping-based approaches, SGVar is capable of resolving long-range phase and identifying large INDELs from WES, more prominently from WGS. We conclude that SGVar represents an ideal platform for WES-based variant discovery in highly divergent regions and across the whole genome.

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De novo meta-assembly of ultra-deep sequencing data

Cited by 25 publications

References 26 publications

Interpreting Microbial Biosynthesis in the Genomic Age: Biological and Practical Considerations

Interpreting Microbial Biosynthesis in the Genomic Age: Biological and Practical Considerations

Comparing and Evaluating Metagenome Assembly Tools from a Microbiologist’s Perspective - Not Only Size Matters!

Comparative analysis of de novo assemblers for variation discovery in personal genomes

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