Characterization of the RNA transcriptome by next-generation sequencing can produce an unprecedented yield of information that provides novel biologic insights. I describe four approaches for sequencing different aspects of the transcriptome and provide computational tools to analyze the resulting data. Methods that query the dynamic range of gene expression, low expressing transcripts, micro RNA levels, and start-site usage of transcripts are described.
Identifer | oai:union.ndltd.org:harvard.edu/oai:dash.harvard.edu:1/11156672 |
Date | 08 October 2013 |
Creators | Christodoulou, Danos C. |
Contributors | Seidman, Jonathan G., Seidman, Christine Edry |
Publisher | Harvard University |
Source Sets | Harvard University |
Language | en_US |
Detected Language | English |
Type | Thesis or Dissertation |
Rights | open |
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