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LncADeep performance on full-length transcripts

Nature Machine Intelligence volume 3, pages 197–198 (2021)Cite this article

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Matters Arising to this article was published on 13 January 2020

The Original Article was published on 13 May 2019

arising from N. Amin et al. Nature Machine Intelligence https://www.nature.com/articles/s42256-019-0051-2 (2019)

Long non-coding RNAs (lncRNAs; transcripts with lengths exceeding 200 nucleotides) exert crucial biological roles and have been implicated in cancers1,2. In a recent study, Amin et al.3 evaluated three lncRNA identification tools including LncADeep4, and concluded that “The LncADeep PR (precision recall) curve is just above the no-skill model” and “LncADeep showed poor overall performance”. However, according to our evaluation, LncADeep’s default setting achieved the best performance overall, indicating that LncADeep was much underestimated in the evaluation by Amin and colleagues.

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Fig. 1: lncRNA identification ROC and PR curves for lncRNAnet, LncADeep and lncFinder.

Data availability

The results of the evaluation of LncADeep are available at https://github.com/cyang235/lncadeep.results/.

References

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Author notes

  1. These authors contributed equally: Cheng Yang, Man Zhou.

Authors and Affiliations

  1. Department of Biomedical Engineering, College of Engineering, and Centre for Quantitative Biology, Peking University, Beijing, China

    Cheng Yang, Man Zhou & Huaiqiu Zhu

  2. Beijing Branch, China Development Bank, Beijing, China

    Cheng Yang

  3. Peking University-Tsinghua University-National Institute of Biological Sciences (PTN) joint PhD program and College of Life Sciences, Peking University, Beijing, China

    Haoling Xie & Huaiqiu Zhu

Authors
  1. Cheng Yang
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  2. Man Zhou
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Contributions

All authors contributed to the manuscript. H.Z. and C.Y. conceived the idea. M.Z. performed the experiment. C.Y. wrote the paper. H.X. and H.Z. revised the manuscript.

Corresponding author

Correspondence to Huaiqiu Zhu.

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Yang, C., Zhou, M., Xie, H. et al. LncADeep performance on full-length transcripts. Nat Mach Intell 3, 197–198 (2021). https://doi.org/10.1038/s42256-019-0108-2

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