CNV detection from exome sequencing data using a generative probabilistic model
Sprache des Vortragstitels:
Englisch
Original Tagungtitel:
13th International Meeting on Human Genome Variation and Complex Genome Analysis (HGV2012)
Sprache des Tagungstitel:
Englisch
Original Kurzfassung:
Next generation sequencing (NGS) has emerged to one of the key technologies for analyzing genome variations. In particular exome sequencing is widely used as a cost and time efficient technology to identify disease-causing genetic variants as about 85% are located around coding regions. One important category of genetic variants are copy number variants (CNVs) typically detected by whole genome sequencing (WGS). However, most methods finding CNVs in WGS data are not applicable to exome sequencing data, since their read distributions differ substantially due to enrichment effects.
The problem of read variations across targeted regions can be circumvented by locally modeling the read counts. For more see http://www.bioinf.jku.at/publications/2012/HGV2012_Klambauer.pdf
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