About this Biochemistry, Genetics and Molecular Biology article

RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome by Bo Li; Colin N Dewey is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.

## Background RNA-Seq is revolutionizing the way transcript abundances are measured. A key challenge in transcript quantification from RNA-Seq data is the handling of reads that map to multiple genes or isoforms. This issue is particularly important for quantification with de novo transcriptome assemblies in the absence of sequenced genomes, as it is difficult to determine which transcripts are isoforms of the same gene. A second significant issue is the design of RNA-Seq experiments, in terms of the number of reads, read length, and whether reads come from one or both ends of cDNA fragments. ## Results We present RSEM, an user-friendly software package for quantifying gene and isoform abundances from single-end or paired-end RNA-Seq data. RSEM outputs abundance estimates, 95% credibility intervals, and visualization files and can also simulate RNA-Seq data. In contrast to other existing tools, the software does not require a reference genome. Thus, in combination with a de novo transcriptome assembler, RSEM enables accurate transcript quantification for species without sequenced genomes. On simulated and real data sets, RSEM has superior or comparable performance to quantification

Author

Bo Li; Colin N Dewey

Publisher

Springer Science and Business Media LLC

Published

2011

Language

EN

Field

Biochemistry, Genetics and Molecular Biology (Life Sciences)