The Marra lab is pleased to announce the recent publication of a manuscript describing the use of RNA-seq data for alternative expression analysis.
The advance online publication can be found at Nature Methods here:
Griffith et al. 2010
Briefly, the method utilizes RNA-seq data to profile transcriptomes, identify transcript features expressed above background noise levels, identify differentially expressed genes, and identify alternatively processed transcripts. Particular emphasis is placed on comparisons between experimental conditions (tumor vs. normal, drug sensitive vs. resistant, etc.)
Results generated using this method/pipeline can be found here:
ALEXA-seq.
To date, 76 libraries corresponding to 16 projects have been analyzed by the ALEXA-seq approach.
Some specific examples of the output can be viewed here:
UMPS expression and splicing in 5-FU sensitive and resistant cell lines
CA12 expression and splicing among normal breast tissue sub-types
To view these examples, your browser must have SVG support (scalable vector graphics). FireFox produces the best results in my experience.
The advance online publication can be found at Nature Methods here:
Griffith et al. 2010
Briefly, the method utilizes RNA-seq data to profile transcriptomes, identify transcript features expressed above background noise levels, identify differentially expressed genes, and identify alternatively processed transcripts. Particular emphasis is placed on comparisons between experimental conditions (tumor vs. normal, drug sensitive vs. resistant, etc.)
Results generated using this method/pipeline can be found here:
ALEXA-seq.
To date, 76 libraries corresponding to 16 projects have been analyzed by the ALEXA-seq approach.
Some specific examples of the output can be viewed here:
UMPS expression and splicing in 5-FU sensitive and resistant cell lines
CA12 expression and splicing among normal breast tissue sub-types
To view these examples, your browser must have SVG support (scalable vector graphics). FireFox produces the best results in my experience.
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