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HPC-T-Annotator: an HPC tool for de novo transcriptome assembly annotation
- Source :
- BMC Bioinformatics, Vol 25, Iss 1, Pp 1-14 (2024)
- Publication Year :
- 2024
- Publisher :
- BMC, 2024.
-
Abstract
- Abstract Background The availability of transcriptomic data for species without a reference genome enables the construction of de novo transcriptome assemblies as alternative reference resources from RNA-Seq data. A transcriptome provides direct information about a species’ protein-coding genes under specific experimental conditions. The de novo assembly process produces a unigenes file in FASTA format, subsequently targeted for the annotation. Homology-based annotation, a method to infer the function of sequences by estimating similarity with other sequences in a reference database, is a computationally demanding procedure. Results To mitigate the computational burden, we introduce HPC-T-Annotator, a tool for de novo transcriptome homology annotation on high performance computing (HPC) infrastructures, designed for straightforward configuration via a Web interface. Once the configuration data are given, the entire parallel computing software for annotation is automatically generated and can be launched on a supercomputer using a simple command line. The output data can then be easily viewed using post-processing utilities in the form of Python notebooks integrated in the proposed software. Conclusions HPC-T-Annotator expedites homology-based annotation in de novo transcriptome assemblies. Its efficient parallelization strategy on HPC infrastructures significantly reduces computational load and execution times, enabling large-scale transcriptome analysis and comparison projects, while its intuitive graphical interface extends accessibility to users without IT skills.
Details
- Language :
- English
- ISSN :
- 14712105
- Volume :
- 25
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- BMC Bioinformatics
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.f24ef9c0bacc4e249d8e5cd4f4cd3ba9
- Document Type :
- article
- Full Text :
- https://doi.org/10.1186/s12859-024-05887-3