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 methods that rely on a 
reference genome. Taking advantage of RSEM's ability to effectively use 
ambiguously-mapping reads, we show that accurate gene-level abundance estimates 
are best obtained with large numbers of short single-end reads. On the other 
hand, estimates of the relative frequencies of isoforms within single genes may 
be improved through the use of paired-end reads, depending on the number of 
possible splice forms for each gene.
CONCLUSIONS: RSEM is an accurate and user-friendly software tool for quantifying 
transcript abundances from RNA-Seq data. As it does not rely on the existence of 
a reference genome, it is particularly useful for quantification with de novo 
transcriptome assemblies. In addition, RSEM has enabled valuable guidance for 
cost-efficient design of quantification experiments with RNA-Seq, which is 
currently relatively expensive.