Algorithms for Population Genomics and Cancer Genomics
summary
Covers algorithmic methods for analyzing population genomics and cancer genomics data, focusing on computational approaches developed or used by Serafim Batzoglou at Stanford. Discusses algorithms applicable to large-scale genomic datasets in both population genetics and cancer studies, though no specific techniques or datasets are listed in the programme entry.
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chapters (20)
- 0:00Intro
- 0:26Lichee: Automated Inference of Multi-Sample Cancer Phylogenies
- 1:47Population Sequencing
- 3:29Previous Methods
- 4:58Informative Neighbors
- 7:44Genetic distance between NNs
- 8:44Overview of Reveel
- 11:07Performance on 1KGP Trios
- 12:35Improved genotyping performance using a reference panel
- 12:49Performance on 1000 Genomes data using UK10K data as reference panel
- 13:44Using a reference panel lowers the requirement of coverage level
- 14:29Shortcomings of Short Reads
- 16:3310x System
- 17:10Read Clouds
- 19:05Identifying Variation in Segmental Duplications
- 21:51MRF-based Realignment
- 22:36Validation on Simulations
- 23:31Phasing,- an MCMC approach
- 25:2010X on NA12878 - Phasing
- 25:5210X on NA12878 - SNV detection
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