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xPore: Identification of differential RNA modifications from nanopore direct RNA sequencing

Authors: Ploy N. Pratanwanich; Fei Yao; Ying Chen; Casslynn W.Q. Koh; Yuk Kei Wan; Christopher Hendra; Polly Poon; +8 Authors

xPore: Identification of differential RNA modifications from nanopore direct RNA sequencing

Abstract

xPore is a Python package for identification and quantification of differential RNA modifications from direct RNA sequencing. The detailed usage is documented at https://xpore.readthedocs.io/en/latest, while all scripts and source code are available at https://github.com/GoekeLab/xpore. All the preprocessed datasets used in the paper are provided here. Please cite our paper below when using these data. Ploy N. Pratanwanich et al. "Detection of differential RNA modifications from direct RNA sequencing of human cell lines." bioRxiv (2020).

{"references": ["Ploy N. Pratanwanich et al. \"Detection of differential RNA modifications from direct RNA sequencing of human cell lines.\" bioRxiv (2020)."]}

Keywords

Nanopore, Statistical machine learning, RNA modification

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citations
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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