Format

Send to

Choose Destination
Nucleic Acids Res. 2019 Feb 11. doi: 10.1093/nar/gkz087. [Epub ahead of print]

CPPred: coding potential prediction based on the global description of RNA sequence.

Author information

1
School of Physics, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China.

Abstract

The rapid and accurate approach to distinguish between coding RNAs and ncRNAs has been playing a critical role in analyzing thousands of novel transcripts, which have been generated in recent years by next-generation sequencing technology. Previously developed methods CPAT, CPC2 and PLEK can distinguish coding RNAs and ncRNAs very well, but poorly distinguish between small coding RNAs and small ncRNAs. Herein, we report an approach, CPPred (coding potential prediction), which is based on SVM classifier and multiple sequence features including novel RNA features encoded by the global description. The CPPred can better distinguish not only between coding RNAs and ncRNAs, but also between small coding RNAs and small ncRNAs than the state-of-the-art methods due to the addition of the novel RNA features. A recent study proposes 1335 novel human coding RNAs from a large number of RNA-seq datasets. However, only 119 transcripts are predicted as coding RNAs by the CPPred. In fact, almost all proposed novel coding RNAs are ncRNAs (91.1%), which is consistent with previous reports. Remarkably, we also reveal that the global description of encoding features (T2, C0 and GC) plays an important role in the prediction of coding potential.

PMID:
30753596
DOI:
10.1093/nar/gkz087

Supplemental Content

Full text links

Icon for Silverchair Information Systems
Loading ...
Support Center