PLEK: a tool for predicting long non-coding RNAs and messenger RNAs based on an improved k-mer scheme.

ABSTRACT:

Background

High-throughput transcriptome sequencing (RNA-seq) technology promises to discover novel protein-coding and non-coding transcripts, particularly the identification of long non-coding RNAs (lncRNAs) from de novo sequencing data. This requires tools that are not restricted by prior gene annotations, genomic sequences and high-quality sequencing.

Results

We present an alignment-free tool called PLEK (predictor of long non-coding RNAs and messenger RNAs based on an improved k-mer scheme), which uses a computational pipeline based on an improved k-mer scheme and a support vector machine (SVM) algorithm to distinguish lncRNAs from messenger RNAs (mRNAs), in the absence of genomic sequences or annotations. The performance of PLEK was evaluated on well-annotated mRNA and

SUBMITTER: Li A 

PROVIDER: S-EPMC4177586 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature