Normalizing bead-based microRNA expression data: a measurement error model-based approach | Zendy

Bin Wang | Zendy; Xiaofeng Wang | Zendy; Yaguang Xi | Zendy

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Normalizing bead-based microRNA expression data: a measurement error model-based approach

Author(s) -

Bin Wang,

Xiaofeng Wang,

Yaguang Xi

Publication year - 2011

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btr180

Subject(s) - normalization (sociology) , dna microarray , computer science , microrna , computational biology , database normalization , data mining , reproducibility , biology , gene expression , mathematics , statistics , pattern recognition (psychology) , artificial intelligence , gene , genetics , sociology , anthropology

Compared with complementary DNA (cDNA) or messenger RNA (mRNA) microarray data, microRNA (miRNA) microarray data are harder to normalize due to the facts that the total number of miRNAs is small, and that the majority of miRNAs usually have low expression levels. In bead-based microarrays, the hybridization is completed in several pools. As a result, the number of miRNAs tested in each pool is even smaller, which poses extra difficulty to intrasample normalization and ultimately affects the quality of the final profiles assembled from various pools. In this article, we consider a measurement error model-based method for bead-based microarray intrasample normalization.

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