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transXpress: a Snakemake pipeline for streamlined de novo transcriptome assembly and annotation

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    0571021 - ÚOCHB 2024 RIV GB eng J - Journal Article
    Fallon, T. R. - Čalounová, Tereza - Mokrejš, Martin - Weng, J. K. - Pluskal, Tomáš
    transXpress: a Snakemake pipeline for streamlined de novo transcriptome assembly and annotation.
    BMC Bioinformatics. Roč. 24, č. 1 (2023), č. článku 133. ISSN 1471-2105. E-ISSN 1471-2105
    R&D Projects: GA ČR(CZ) GM21-11563M
    EU Projects: European Commission(XE) 891397 - KavaTarget
    Institutional support: RVO:61388963
    Keywords : de novo transcriptome assembly * RNA-seq * non-model organisms * transcriptome annotation * differential expression analysis * reproducible software * high-performance computing
    OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
    Impact factor: 3, year: 2022
    Method of publishing: Open access
    https://doi.org/10.1186/s12859-023-05254-8

    BACKGROUND: RNA-seq followed by de novo transcriptome assembly has been a transformative technique in biological research of non-model organisms, but the computational processing of RNA-seq data entails many different software tools. The complexity of these de novo transcriptomics workflows therefore presents a major barrier for researchers to adopt best-practice methods and up-to-date versions of software. RESULTS: Here we present a streamlined and universal de novo transcriptome assembly and annotation pipeline, transXpress, implemented in Snakemake. transXpress supports two popular assembly programs, Trinity and rnaSPAdes, and allows parallel execution on heterogeneous cluster computing hardware. CONCLUSIONS: transXpress simplifies the use of best-practice methods and up-to-date software for de novo transcriptome assembly, and produces standardized output files that can be mined using SequenceServer to facilitate rapid discovery of new genes and proteins in non-model organisms.
    Permanent Link: https://hdl.handle.net/11104/0342339


    Research data: Zenodo, NCBI SRA, NCBI SRA, NCBI SRA
     
    FileDownloadSizeCommentaryVersionAccess
    10.1186s12859-023-05254-8.pdf01.9 MBPublisher’s postprintopen-access
     
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