SPATA: A Seeding and Patching Algorithm for Hybrid Transcriptome Assembly
Tin Chi Nguyen, Zhiyu Zhao, Dongxiao Zhu

TL;DR
SPATA is a hybrid transcriptome assembly algorithm that combines local alignment and de novo assembly to improve accuracy without relying on splice-aware aligners, suitable for incomplete reference genomes.
Contribution
The paper introduces SPATA, a novel hybrid approach that localizes reads to genomic loci and performs targeted de novo assembly, addressing limitations of existing methods.
Findings
High accuracy and precision demonstrated in simulations
Effective for species with incomplete reference genomes
Open-source software available for use
Abstract
Transcriptome assembly from RNA-Seq reads is an active area of bioinformatics research. The ever-declining cost and the increasing depth of RNA-Seq have provided unprecedented opportunities to better identify expressed transcripts. However, the nonlinear transcript structures and the ultra-high throughput of RNA-Seq reads pose significant algorithmic and computational challenges to the existing transcriptome assembly approaches, either reference-guided or de novo. While reference-guided approaches offer good sensitivity, they rely on alignment results of the splice-aware aligners and are thus unsuitable for species with incomplete reference genomes. In contrast, de novo approaches do not depend on the reference genome but face a computational daunting task derived from the complexity of the graph built for the whole transcriptome. In response to these challenges, we present a hybrid…
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Taxonomy
TopicsRNA Research and Splicing · RNA modifications and cancer · RNA and protein synthesis mechanisms
