Conclusion
In this paper, we propose a statistical framework MLDA, based on the smoothed LDA to detect the differential usage of transcript isoforms for RNA-seq data. The experimental results show that our method performs competitively on the detection of DTU and obtain more accurate relative transcript abundance compared with other alternatives on both simulated and real data.
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Acknowledgements
This work was supported by the National Key R&D Program of China (2018YFC2001600, 2018YFC2001602).
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Li, J., Liu, X. & Zhang, D. Detecting differential transcript usage across multiple conditions for RNA-seq data based on the smoothed LDA model. Front. Comput. Sci. 15, 153319 (2021). https://doi.org/10.1007/s11704-020-9348-x
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DOI: https://doi.org/10.1007/s11704-020-9348-x