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Accurate quantification of transcriptome from RNA-Seq data by effective length normalization.

Nucleic acids research | Jan 24, 2011

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.

Pubmed ID: 21059678 RIS Download

Mesh terms: Algorithms | Cell Line | Computer Simulation | Gene Expression Profiling | Humans | Polymerase Chain Reaction | Protein Isoforms | RNA, Messenger | Reproducibility of Results | Sequence Analysis, RNA

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UCSC Genome Browser

A collection of genomes which include reference sequences and working draft assemblies, as well as a variety of tools to explore these sequences. The Genome Browser zooms and scrolls over chromosomes, showing the work of annotators worldwide. The Gene Sorter shows expression, homology and other information on groups of genes that can be related in many ways. Blat quickly maps your sequence to the genome. The Table Browser provides access to the underlying database. VisiGene lets you browse through a large collection of in situ mouse and frog images to examine expression patterns. Genome Graphs allows you to upload and display genome-wide data sets. Also provided is a portal to the Encyclopedia of DNA Elements (ENCODE) and Neandertal projects.

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