Transcriptome assembly from long-read RNA-seq alignments with StringTie2

Transcriptome assembly from long-read RNA-seq alignments with StringTie2

(2019) 20:278 | Sam Kovaka, Aleksey V. Zimin, Geo M. Pertea, Roham Razaghi, Steven L. Salzberg, and Mihaela Pertea
StringTie2 is a transcriptome assembler that can handle both short and long RNA-seq reads, including full-length super-reads assembled from short reads. It addresses the challenges of long-read sequencing, such as high error rates and the need for reference genomes, by implementing new methods to correct errors and improve accuracy. StringTie2 outperforms other transcriptome assemblers like Scallop in terms of sensitivity, precision, and computational efficiency. It is particularly effective in handling noisy long reads, which can significantly improve the sensitivity of downstream analyses. The tool also includes features for using super-reads, which enhance the quality of short-read assemblies and improve the identification of novel transcripts. StringTie2's performance is demonstrated through simulations and real datasets, showing its ability to assemble transcripts more accurately and efficiently than comparable tools.StringTie2 is a transcriptome assembler that can handle both short and long RNA-seq reads, including full-length super-reads assembled from short reads. It addresses the challenges of long-read sequencing, such as high error rates and the need for reference genomes, by implementing new methods to correct errors and improve accuracy. StringTie2 outperforms other transcriptome assemblers like Scallop in terms of sensitivity, precision, and computational efficiency. It is particularly effective in handling noisy long reads, which can significantly improve the sensitivity of downstream analyses. The tool also includes features for using super-reads, which enhance the quality of short-read assemblies and improve the identification of novel transcripts. StringTie2's performance is demonstrated through simulations and real datasets, showing its ability to assemble transcripts more accurately and efficiently than comparable tools.
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