Transcript profiling ("Transcriptomics") is a widely used technique that obtains information on the abundance of multiple mRNA transcripts within a biological sample simultaneously. Therefore, when a number of such samples are analysed, as in a scientific experiment, large and complex data sets are gene-rated. Here, we describe the use of one method commonly used to generate transcriptomics data, namely the use of Affymetrix GeneChip microarrays. Data generated in transcriptomics experiments can be analysed using a multitude of approaches, but a common goal is to identify those transcripts whose abundance is altered by the experimental conditions, or which differ between sets of samples. Here, we describe a simple approach, the calculation of the volcano score, which identifies transcripts with altered abundance, taking into account both the magnitude of the alteration and its statistical significance.
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http://dx.doi.org/10.1007/978-1-60761-849-2_10 | DOI Listing |
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