Computational approaches for isoform detection and estimation: good and bad news.

ABSTRACT:

Background

The main goal of the whole transcriptome analysis is to correctly identify all expressed transcripts within a specific cell/tissue--at a particular stage and condition--to determine their structures and to measure their abundances. RNA-seq data promise to allow identification and quantification of transcriptome at unprecedented level of resolution, accuracy and low cost. Several computational methods have been proposed to achieve such purposes. However, it is still not clear which promises are already met and which challenges are still open and require further methodological developments.

Results

We carried out a simulation study to assess the performance of 5 widely used tools, such as: CEM, Cufflinks, iReckon, RSEM, and SLIDE. All of them have been used with def

SUBMITTER: Angelini C 

PROVIDER: S-EPMC4098781 | biostudies-literature | 2014 May

REPOSITORIES: biostudies-literature