We propose a novel, efficient and intuitive approach of estimating mRNA 
abundances from the whole transcriptome shotgun sequencing (RNA-Seq) data. Our 
method, NEUMA (Normalization by Expected Uniquely Mappable Area), is based on 
effective length normalization using uniquely mappable areas of gene and mRNA 
isoform models. Using the known transcriptome sequence model such as RefSeq, 
NEUMA pre-computes the numbers of all possible gene-wise and isoform-wise 
informative reads: the former being sequences mapped to all mRNA isoforms of a 
single gene exclusively and the latter uniquely mapped to a single mRNA isoform. 
The results are used to estimate the effective length of genes and transcripts, 
taking experimental distributions of fragment size into consideration. 
Quantitative RT-PCR based on 27 randomly selected genes in two human cell lines 
and computer simulation experiments demonstrated superior accuracy of NEUMA over 
other recently developed methods. NEUMA covers a large proportion of genes and 
mRNA isoforms and offers a measure of consistency ('consistency coefficient') 
for each gene between an independently measured gene-wise level and the sum of 
the isoform levels. NEUMA is applicable to both paired-end and single-end 
RNA-Seq data. We propose that NEUMA could make a standard method in quantifying 
gene transcript levels from RNA-Seq data.