A statistical framework for the analysis of ChIP-Seq data

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• Gottardo, R (University of British Columbia)
• Friday 16 July 2010, 11:30-12:00
• Seminar Room 1, Newton Institute.

If you have a question about this talk, please contact Mustapha Amrani.

Statistical Challenges Arising from Genome Resequencing

ChIP-seq, which combines chromatin immunoprecipitation with massively parallel short-read sequencing, can profile in vivo genome-wide transcription factor-DNA association with higher sensitivity, specificity and spatial resolution than ChIP- chip. While it presents new opportunities for research, ChIP-seq poses new challenges for statistical analysis that derive from the complexity of the biological systems characterized and the variability and biases in its digital sequence data. In this talk I will review some of the common problems with the analysis of such data and I will describe a pipeline for the integrated analysis of ChIP-Seq that we have developed in my lab.

This talk is part of the Isaac Newton Institute Seminar Series series.

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