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Table 1 Transcriptome analysis.

From: The hepatic transcriptome in human liver disease

Open systems Advantages Disadvantages Comments
Representational differences analysis (RDA) • Sensitive method
• Sequence data obtained
• Alternately spliced transcripts can be easily identified
• "Hit and miss" approach
• Not suitable for transcriptome profiling
• Sequencing intensive
• Transcript representation may change and results need to be verified
• Typically used for identification of novel differentially expressed transcripts
• Most commonly used variant of this method is Suppression Subtractive Hybridization (SSH)
Differential display (DD) • Sensitive method
• Sequence data obtained
• High false positive rate
• Not suitable for transcriptome profiling
• Transcript representation may change and results need to be verified
• Not currently a widely favoured methodology
Serial analysis of gene expression (SAGE) • Transciptome profiling possible
• Transcript representation retained
• Limited sequence data obtained
• Sequencing intensive method
• Often fails to account for transcript alternate splicing
• SAGE suitability for transciptome profiling is reliant on extensive sequencing
Closed Systems Advantages Disadvantages Comments
Gene arrays • Characterized target sequences on the arrays
• Extremely small feature size
• Very high through put methodology
• Restricted gene pool that may sample rather than profile the transcriptome
• Variability
• Signal amplification often needed for biopsies
• Often fails to account for transcript alternate splicing
• Data generated can be a bioinformatics challenge
• Inconsistencies with analysis approaches
• Preferred transciptome profiling method
• Gene alternate splicing can be addressed by using "tilling arrays"
• MIAME is designed to overcome methodological inconsistencies