SQANTI-SIM – a simulator of controlled transcript novelty for lrRNA-seq benchmark

Long-read RNA sequencing has emerged as a powerful tool for transcript discovery, even in well-annotated organisms. However, assessing the accuracy of different methods in identifying annotated and novel transcripts remains a challenge. Researchers at the Spanish National Research Council have developed SQANTI-SIM, a versatile tool that wraps around popular long-read simulators to allow precise management of transcript novelty based on the structural categories defined by SQANTI3. By selectively excluding specific transcripts from the reference dataset, SQANTI-SIM effectively emulates scenarios involving unannotated transcripts. Furthermore, the tool provides customizable features and supports the simulation of additional types of data, representing the first multi-omics simulation tool for the lrRNA-seq field.

Flowchart of the SQANTI-SIM pipeline

Fig. 1

The first three steps simulate reads and accompanying datasets according to the user’s specifications. Simulated data is then used by the transcriptome reconstruction algorithm to predict transcripts. The last SQANTI-SIM module assesses performance by comparison to the simulated ground truth and provides a comprehensive evaluation report

Availability – SQANTI-SIM is available at https://github.com/ConesaLab/SQANTI-SIM

Mestre-Tomás J, Liu T, Pardo-Palacios F, Conesa A. (2023) SQANTI-SIM: a simulator of controlled transcript novelty for lrRNA-seq benchmark. Genome Biol 24(1):286. [article]

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