title: Digital sorting of complex tissues for cell type-specific gene expression profiles.
abstract: BACKGROUND
  Cellular heterogeneity is present in almost all gene expression profiles. However, transcriptome analysis of tissue specimens often ignores the cellular heterogeneity present in these samples. Standard deconvolution algorithms require prior knowledge of the cell type frequencies within a tissue or their in vitro expression profiles. Furthermore, these algorithms tend to report biased estimations.
  
  
  RESULTS
  Here, we describe a Digital Sorting Algorithm (DSA) for extracting cell-type specific gene expression profiles from mixed tissue samples that is unbiased and does not require prior knowledge of cell type frequencies.
  
  
  CONCLUSIONS
  The results suggest that DSA is a specific and sensitivity algorithm in gene expression profile deconvolution and will be useful in studying individual cell types of complex tissues.
authors.affiliation: Department of Pediatrics, Neurological Research Institute, Baylor College of Medicine, Houston, TX, USA.
authors.forename: Yi
authors.initials: Y
authors.lastname: Zhong
authors.forename: Ying-Wooi
authors.initials: YW
authors.lastname: Wan
authors.forename: Kaifang
authors.initials: K
authors.lastname: Pang
authors.forename: Lionel M L
authors.initials: LM
authors.lastname: Chow
authors.forename: Zhandong
authors.initials: Z
authors.lastname: Liu
mesh_terms: D000465:Algorithms; D020869:Gene Expression Profiling / Q000379:methods*; D020411:Oligonucleotide Array Sequence Analysis