It appears you don't have support to open PDFs in this web browser. To view this file, Open with your PDF reader
Abstract
Long-read sequencing technologies have improved significantly since their emergence. Their read lengths, potentially spanning entire transcripts, is advantageous for reconstructing transcriptomes. Existing long-read transcriptome assembly methods are primarily reference-based and to date, there is little focus on reference-free transcriptome assembly. We introduce “RNA-Bloom2 [https://github.com/bcgsc/RNA-Bloom]”, a reference-free assembly method for long-read transcriptome sequencing data. Using simulated datasets and spike-in control data, we show that the transcriptome assembly quality of RNA-Bloom2 is competitive to those of reference-based methods. Furthermore, we find that RNA-Bloom2 requires 27.0 to 80.6% of the peak memory and 3.6 to 10.8% of the total wall-clock runtime of a competing reference-free method. Finally, we showcase RNA-Bloom2 in assembling a transcriptome sample of Picea sitchensis (Sitka spruce). Since our method does not rely on a reference, it further sets the groundwork for large-scale comparative transcriptomics where high-quality draft genome assemblies are not readily available.
Most existing long-read transcriptome assembly methods rely on reference genomes and transcript annotations, while reference-free methods remain scarce. Here, Nip et al. introduce RNA-Bloom2, a reference-free method that requires substantially less memory and runtime than other reference-free methods.
You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer
Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer
Details
; Hafezqorani, Saber 1
; Gagalova, Kristina K. 1
; Chiu, Readman 2
; Yang, Chen 1
; Warren, René L. 2
; Birol, Inanc 3
1 Canada’s Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, Canada (GRID:grid.434706.2) (ISNI:0000 0004 0410 5424); University of British Columbia, Bioinformatics Graduate Program, Vancouver, Canada (GRID:grid.17091.3e) (ISNI:0000 0001 2288 9830)
2 Canada’s Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, Canada (GRID:grid.434706.2) (ISNI:0000 0004 0410 5424)
3 Canada’s Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, Canada (GRID:grid.434706.2) (ISNI:0000 0004 0410 5424); University of British Columbia, Department of Medical Genetics, Vancouver, Canada (GRID:grid.17091.3e) (ISNI:0000 0001 2288 9830)




