Prediction of uORFs in varying tissues / stages, using the ORFik package as back-end and the presumption that active / translated uORFs should have similar Ribo-seq patterns to (coding sequences) CDS'. Uses a Random forrest (from H2o.ai) trained on Ribo-seq features.
Package details |
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Author | Hakon Tjeldnes |
Bioconductor views | Alignment Coverage DataImport FunctionalGenomics ImmunoOncology RNASeq RiboSeq Sequencing Software |
Maintainer | |
License | MIT + file LICENSE |
Version | 0.2.2 |
Package repository | View on GitHub |
Installation |
Install the latest version of this package by entering the following in R:
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