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While genetic variation measures the changes in the information encoded in the genome, gene expression measures how that information is used. As in genetic variation, there are NGS (RNA-seq) and microarray platforms available. RNA-seq provides a greater dynamic range than microarray and can be used to measure non-annotated genes and isoforms, but microarray offers a less expensive, faster way to profile gene expression, and recent arrays include measurements of gene splicing as well. Additionally, a number of experiments measure a subset of total RNA and can be used to target particular processes of interest. For example, GRO-seq selectively measures newly transcribed RNA, making it a more accurate read-out of transcriptional regulatory effects. Alternatively, CLIP-seq techniques isolate RNA on the basis of certain binding proteins and, among other uses, can isolate RNA bound to ribosomal complexes, quantifying actively translated RNA. We may also be interested in the expression of small regulatory RNAs, such as miRNA, and the post-transcriptional controls these exert on gene expression. The CRI provides analysis support for numerous transcriptomics experiments, including:

  • Gene expression quantification
  • Generation of quantitative expression profile and downstream analysis

  • Identification of deferentially expressed genes
  • Identification of the genes deferentially expressed among certain conditions and downstream pathway analysis

  • Identification of novel transcripts, or alternative splicing
  • Identification of novel transcript isoforms, or alternatively spliced transcripts.

  • RNA editing
  • Identification of the genetic variations in RNA molecule instead of DNA molecule

  • RNA fusion
  • Identification of RNA fusion encoded by a fusion gene