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Usually microarray techniques provide a valuable way of characterizing the molecular nature of disease but the expense and limited specimen availability often lead to studies with small sample sizes.
High-throughput approaches, such as microarray techniques, provide an opportunity to investigate gene expression of whole genomes simultaneously, allowing studies of how different genes respond to a certain environmental stimuli and the general gene expression patterns among various gene families that were categorized into different cellular functions on genome-wide scales [ 57].
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Basically, the reliable identification of regulated genes by a high-throughput method such as the DNA microarray technique provides a solid base for further experimental analysis.
Recently, microarray-based techniques provide a powerful tool to map methylation patterns in multiple genes and multiple CpG sites within genes [ 17, 18].
The combined use of these approaches together with conventional cDNA library sequencing and microarray-based techniques provides a more solid assessment of gene expression than would each method alone.
Microarray techniques have provided an unbiased tool to generate hypotheses of potential disease-related genes and pathways, and have identified many dramatic genomic modifications in psoriasis compared with non-lesional and normal skin (Zhou et al., 2003; Gudjonsson et al., 2009; Suarez-Farinas et al., 2010a).
Deep sequencing techniques provide considerable advantage over microarrays that have been frequently used in transcriptome analysis [ 26– 28].
Both techniques provide highly consistent, highly reproducible gene expression measurements in adult human brain, with RNA-Seq slightly outperforming microarray results overall.
These techniques provide complementary viewpoints.
Alternatively, simulation techniques provide a convenient option.
NGS is potentially advantageous over microarray techniques as it provides greater coverage, demonstrates sequence independence and has the potential to identify novel miRNAs.
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