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.
|Bioconductor views||Alignment Coverage DataImport FunctionalGenomics ImmunoOncology RNASeq RiboSeq Sequencing Software|
|License||MIT + file LICENSE|
|Package repository||View on GitHub|
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