ArticleGigaScience2019
De novo transcriptome assembly: A comprehensive cross-species comparison of short-read RNA-Seq assemblers.
Article in GigaScience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 119 papers.
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Who cites it
119 citing papers in PubMed.
- Phylotranscriptomics Allows Distinguishing Major Gene Flow Events from Incomplete Lineage Sorting in Rapidly Diversifying Mimetic Orchids (Genus Ophrys).Genome biology and evolution · 2026Article
- Comparative Genomic and Functional Characterization ofInternational journal of molecular sciences · 2026Article
- HyDRA: A pipeline for integrating long- and short-read RNAseq data for custom transcriptome assembly.iScience · 2026Article
- Self-assembling proteins compose the chemically resistant shell biomaterial of planktonic tintinnid ciliates.Nature communications · 2026Article
- Comprehensive assessment of transcriptome assembly quality using CATS.Nature communications · 2026Article
- Metamorphosis and lncRNAs: A Close Relationship.Genesis (New York, N.Y. : 2000) · 2026Review
- Laryngeal Transcriptomic Insights into Echolocation Call Frequency Divergence in Closely RelatedBiology · 2026Article
- Probiotic Potential, Genomic Characterization, and In Silico Insights of FiveAntibiotics (Basel, Switzerland) · 2026Article
- Article
- A comprehensive evaluation of long-read de novo transcriptome assembly.Genome biology · 2026Article
- De novo genome assembly of Ansell's mole-rat (Fukomys anselli).G3 (Bethesda, Md.) · 2026Article
- Diversity of lncRNAs in the pan-transcriptome of maize inbred lines.BMC genomics · 2026Article
- Genomic characterization and biological activities of cell-free supernatant fromFrontiers in cellular and infection microbiology · 2026Article
- Interpreting fungal ecological contributions through taxonomic and functional profiling of metatranscriptomics.IMA fungus · 2026Review
- Oil trait and multi-omic analyses reveal the regulatory network of triacylglycerol and fatty acid accumulation in hexaploid Camellia oleifera across different harvesting stages.BMC plant biology · 2025Article
- Bioinformatics perspectives on transcriptomics: A comprehensive review of bulk and single-cell RNA sequencing analyses.Quantitative biology (Beijing, China) · 2025Review
- De novo assembly of plasmodium interspersed repeat (pir) genes from Plasmodium vivax RNAseq data suggests geographic conservation of sub-family transcription.BMC genomics · 2025Article
- Large-scale transcriptome mining enables macrocyclic diversification and improved bioactivity of the stephanotic acid scaffold.Nature communications · 2025Article
- Virome analysis of field-collected chilli samples reveals diverse viruses.Virology journal · 2025Article
- Establishing genome sequencing and assembly for non-model and emerging model organisms: a brief guide.Frontiers in zoology · 2025Review
59 more citing papers are in PubMed but not listed here.
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2 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundIn recent years, massively parallel complementary DNA sequencing (RNA sequencing [RNA-Seq]) has emerged as a fast, cost-effective, and robust technology to study entire transcriptomes in various manners. In particular, for non-model organisms and in the absence of an appropriate reference genome, RNA-Seq is used to reconstruct the transcriptome de novo. Although the de novo transcriptome assembly of non-model organisms has been on the rise recently and new tools are frequently developing, there is still a knowledge gap about which assembly software should be used to build a comprehensive de novo assembly.
resultsHere, we present a large-scale comparative study in which 10 de novo assembly tools are applied to 9 RNA-Seq data sets spanning different kingdoms of life. Overall, we built >200 single assemblies and evaluated their performance on a combination of 20 biological-based and reference-free metrics. Our study is accompanied by a comprehensive and extensible Electronic Supplement that summarizes all data sets, assembly execution instructions, and evaluation results. Trinity, SPAdes, and Trans-ABySS, followed by Bridger and SOAPdenovo-Trans, generally outperformed the other tools compared. Moreover, we observed species-specific differences in the performance of each assembler. No tool delivered the best results for all data sets.
conclusionsWe recommend a careful choice and normalization of evaluation metrics to select the best assembling results as a critical step in the reconstruction of a comprehensive de novo transcriptome assembly.
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