A statistical framework for the analysis of ChIP-Seq data
Duration: 35 mins 8 secs
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| Description: |
Gottardo, R (University of British Columbia)
Friday 16 July 2010, 11:30-12:00 |
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| Created: | 2010-07-20 12:51 | ||
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| Collection: | Statistical Challenges Arising from Genome Resequencing | ||
| Publisher: | Isaac Newton Institute | ||
| Copyright: | Gottardo, R | ||
| Language: | eng (English) | ||
| Distribution: |
World
(downloadable)
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| Credits: |
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| Categories: |
iTunes - Mathematics - Advanced Mathematics |
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| Explicit content: | No | ||
| Aspect Ratio: | 4:3 | ||
| Screencast: | No | ||
| Bumper: | /sms-ingest/static/1280x960-4x3-sms-bumper.mp4 | ||
| Trailer: | /sms-ingest/static/1280x960-4x3-sms-trailer.mp4 | ||
| Abstract: | 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. |
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