AI Article Synopsis
- Long-read sequencing can read whole RNA messages in one go, making it easier to understand and measure them compared to the shorter methods which can be confusing.
- New improvements in these long-read technologies help scientists discover new variations of RNA and better understand how RNA is put together.
- The article talks about 25 different tools for using long-read sequencing and suggests that we need better standard procedures to get more accurate results in RNA studies.
Article Abstract
Long-read sequencing technologies can capture entire RNA transcripts in a single sequencing read, reducing the ambiguity in constructing and quantifying transcript models in comparison to more common and earlier methods, such as short-read sequencing. Recent improvements in the accuracy of long-read sequencing technologies have expanded the scope for novel splice isoform detection and have also enabled a far more accurate reconstruction of complex splicing patterns and transcriptomes. Additionally, the incorporation and advancements of machine learning and deep learning algorithms in bioinformatic software have significantly improved the reliability of long-read sequencing transcriptomic studies. However, there is a lack of consensus on what bioinformatic tools and pipelines produce the most precise and consistent results. Thus, this review aims to discuss and compare the performance of available methods for novel isoform discovery with long-read sequencing technologies, with 25 tools being presented. Furthermore, this review intends to demonstrate the need for developing standard analytical pipelines, tools, and transcript model conventions for novel isoform discovery and transcriptomic studies.
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| http://dx.doi.org/10.1093/bfgp/elae031 | DOI Listing |
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