RNA sequencing (RNA-seq) is replacing expression microarrays for genome-wide assessment of gene expression abundance. Many sophisticated sta- tistical methods have been developed to map gene expression quantitative trait loci (eQTL) using microarray data. These methods can potentially be applied to RNA- seq data with minor modifications. However, they fail to exploit two types of novel information that are available from RNA-seq but not from microarrays: the allele- specific expression (ASE) and the isoform-specific expression (ISE). This chapter gives an overview of the statistical methods that are specifically designed for eQTL mapping using RNA-seq data, as well as the challenges and some future directions.
CITATION STYLE
Liu, P., & Si, Y. (2014). Cluster Analysis of RNA-Sequencing Data. In Statistical Analysis of Next Generation Sequencing Data (pp. 191–217). Springer International Publishing. https://doi.org/10.1007/978-3-319-07212-8_10
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