Title |
A mixture model for expression deconvolution from RNA-seq in heterogeneous tissues
|
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Published in |
BMC Bioinformatics, April 2013
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DOI | 10.1186/1471-2105-14-s5-s11 |
Pubmed ID | |
Authors |
Yi Li, Xiaohui Xie |
Abstract |
RNA-seq, a next-generation sequencing based method for transcriptome analysis, is rapidly emerging as the method of choice for comprehensive transcript abundance estimation. The accuracy of RNA-seq can be highly impacted by the purity of samples. A prominent, outstanding problem in RNA-seq is how to estimate transcript abundances in heterogeneous tissues, where a sample is composed of more than one cell type and the inhomogeneity can substantially confound the transcript abundance estimation of each individual cell type. Although experimental methods have been proposed to dissect multiple distinct cell types, computationally "deconvoluting" heterogeneous tissues provides an attractive alternative, since it keeps the tissue sample as well as the subsequent molecular content yield intact. |
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