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Open Access

Analysis of Allele Specific Expression - A Survey

Feng Gu†( ), Xue Wang†
Department of Computer Science, The College of Staten Island, The City University of New York, Staten Island, NY 10314, USA.
Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224, USA.

† Both authors contribute equally to the work.

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Abstract

Allele specific expression is essential for cellular programming and development and the diversity of cellular phenotypes. Traditional analysis methods utilize RNA and depend on single nucleotide polymorphisms, thus to suffer from limited amount of materials for analysis. The rapid development of next-generation sequencing technologies provides more comprehensive and powerful approaches to analyze the genomic, epigenetic, and transcriptomic data, and further to detect and measure allele specific expressions. It will potentially enhance the understanding of the allele specific expressions, their complexities, and the effect on biological processes. In this paper, we extensively review the state-of-art enabling technologies and tools to analyze, detect, and measure allele specific expressions, compare their features, and point out the future trend of the methods.

Keywords

allele specific expressioncellular phenotypessequencing technologiesSingle Nucleotide Polymorphism (SNP)Single Nucleotide Variant (SNV)allele specific expressionstatistical methodstranscripts

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Tsinghua Science and Technology
Volume 20 Issue 5,
October 2015
Pages 513-529
DOI: 10.1109/TST.2015.7297750
Cite this article:
Gu F, Wang X. Analysis of Allele Specific Expression - A Survey. Tsinghua Science and Technology, 2015, 20(5): 513-529. https://doi.org/10.1109/TST.2015.7297750

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Received: 06 July 2015
Accepted: 06 August 2015
Published: 13 October 2015
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