ArticlePloS one2012
Evaluating de Bruijn graph assemblers on 454 transcriptomic data.
Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- transXpress: a Snakemake pipeline for streamlined de novo transcriptome assembly and annotation.BMC bioinformatics · 2023Article
- Barrettides: A Peptide Family Specifically Produced by the Deep-Sea SpongeJournal of natural products · 2021Article
- Whole-Genome Analysis Illustrates Global Clonal Population Structure of the Ubiquitous Dermatophyte PathogenGenetics · 2018Article
- Enriching Genomic Resources and Marker Development from Transcript Sequences ofInternational journal of genomics · 2017Article
- Transcriptome sequencing and de novo characterization of Korean endemic land snail, Koreanohadra kurodana for functional transcripts and SSR markers.Molecular genetics and genomics : MGG · 2016Article
- De novo transcriptome assembly for a non-model species, the blood-sucking bug Triatoma brasiliensis, a vector of Chagas disease.Genetica · 2015Article
- Nuclear genomic signals of the 'microturbellarian' roots of platyhelminth evolutionary innovation.eLife · 2015Article
- Host Subtraction, Filtering and Assembly Validations for Novel Viral Discovery Using Next Generation Sequencing Data.PloS one · 2015Article
- Genome-Wide Transcriptional Profiling and Metabolic Analysis Uncover Multiple Molecular Responses of the Grass Species Lolium perenne Under Low-Intensity Xenobiotic Stress.Frontiers in plant science · 2015Article
- Evaluation of de novo transcriptome assemblies from RNA-Seq data.Genome biology · 2014Article
- Comparison of different assembly and annotation tools on analysis of simulated viral metagenomic communities in the gut.BMC genomics · 2014Article
- Towards decrypting cryptobiosis--analyzing anhydrobiosis in the tardigrade Milnesium tardigradum using transcriptome sequencing.PloS one · 2014Article
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Authors and funding
7 authors.
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Abstract
Next generation sequencing (NGS) technologies have greatly changed the landscape of transcriptomic studies of non-model organisms. Since there is no reference genome available, de novo assembly methods play key roles in the analysis of these data sets. Because of the huge amount of data generated by NGS technologies for each run, many assemblers, e.g., ABySS, Velvet and Trinity, are developed based on a de Bruijn graph due to its time- and space-efficiency. However, most of these assemblers were developed initially for the Illumina/Solexa platform. The performance of these assemblers on 454 transcriptomic data is unknown. In this study, we evaluated and compared the relative performance of these de Bruijn graph based assemblers on both simulated and real 454 transcriptomic data. The results suggest that Trinity, the Illumina/Solexa-specialized transcriptomic assembler, performs the best among the multiple de Bruijn graph assemblers, comparable to or even outperforming the standard 454 assembler Newbler which is based on the overlap-layout-consensus algorithm. Our evaluation is expected to provide helpful guidance for researchers to choose assemblers when analyzing 454 transcriptomic data.
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