Introduction

BACKGROUND: Long intergenic non-coding RNAs (lincRNAs) are emerging as a novel class of non-coding RNAs and potent gene regulators. High-throughput RNA-sequencing combined with de novo assembly promises quantity discovery of novel transcripts. However, the identification of lincRNAs from thousands of assembled transcripts is still challenging due to the difficulties of separating them from protein coding transcripts (PCTs). RESULTS: We have implemented iSeeRNA, a support vector machine (SVM)-based classifier for the identification of lincRNAs. iSeeRNA shows better performance compared to other software. A public available webserver for iSeeRNA is also provided for small size dataset. CONCLUSIONS: iSeeRNA demonstrates high prediction accuracy and runs several magnitudes faster than other similar programs. It can be integrated into the transcriptome data analysis pipelines or run as a web server, thus offering a valuable tool for lincRNA study.

Publications

  1. iSeeRNA: identification of long intergenic non-coding RNA transcripts from transcriptome sequencing data.
    Cite this
    Sun K, Chen X, Jiang P, Song X, Wang H, Sun H, 2013-01-01 - BMC genomics

Credits

  1. Kun Sun
    Developer

  2. Xiaona Chen
    Developer

  3. Peiyong Jiang
    Developer

  4. Xiaofeng Song
    Developer

  5. Huating Wang
    Developer

  6. Hao Sun
    Investigator

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Summary
AccessionBT003302
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesC++, Perl
User InterfaceTerminal Command Line
Download Count0
Submitted ByHao Sun