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SUMMARY:Modeling allele-specific expression from RNA-seq data - Clark\, A 
 (University of Cornell)
DTSTART:20100713T135000Z
DTEND:20100713T143000Z
UID:TALK25505@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:RNA seq data can address a wide range of functional attributes
  of the expressed genome\, including quantitation of levels of expression\
 , patterns of splicing\, and differential allelic expression. In the case 
 of differential allelic expression\, the assumption is that each gene that
  is amenable to this analysis is heterozygous in the examined individuals\
 , and a reasonable null hypothesis is that there is a binomial distributio
 n of counts of transcripts of the two alleles with parameter . This talk w
 ill explore the violations of this model displayed by RNA-seq data\, and w
 ill seek to identify the causes. Stochastic variation\, differential promo
 ter activities\, X-chromosome inactivation\, and genomic imprinting are so
 me of the biological factors that can be modeled and inferred from RNA-seq
  data. Interspecific F1 hybrids provide particularly rich for exploring ci
 s-regulatory divergence. Illustrations from human\, mouse\, horse\, donkey
 \, and Drosophila will be given.
LOCATION:Seminar Room 1\, Newton Institute
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