Dates: 19-20 April, 2018
The 6th RECOMB Satellite on Computational Methods in Genetics will focus on current research at the intersection of genetics, computer science, statistics, and related fields in gathering and analyzing SNP and haplotype data and applying it to problems in medicine and basic research. Population genetics allows more refined understanding of the demographic history of our species, association analysis provides insights regarding the functional and molecular underpinnings of diseases and traits, while clinical applications suggest genetics as a trailblazer into personalized medicine. The complex bioinformatic questions arising range from inferring more nuanced statistical models of genetic information to algorithms that overcome the complexity challenges of analyzing millions of SNPs across millions of individuals, to systems level challenges of handling such Big Data repositories of genotypes and phenotypes.
Thursday April 19th
RECOMB Genetics I
Friday April 20th
RECOMB Genetics II
- Algorithms to modulate ARG by Selection
- Complex demographic histories of admixed populations reconstructed with Approximate Bayesian Computations
- Towards an Accurate and Efficient Heuristic for Species/Gene Tree Co-estimation – might not be able to present
- DataRemix: a universal data transformation for optimal inference from gene expression datasets
- Predicting complex diseases: performance and robustness
- Construction of individual recombination maps using linked-read sequencing data
- Estimating cell-type composition from DNA methylation sequencing data
- Allelic imbalances and variable clonal representation in GTEx Consortium data
- Investigating cancer risk germline mutations using eQTL networks
University of Bern, Switzerland
University of Queensland, Australia
Institut Pasteur, France
Institut Pasteur and CNRS, France
- A comparative study of genotype imputation programs.
- Pleiotropy between GWAS catalog traits and alcohol-related life events and substance-induced depressions in two independent populations.
- Tracking Top 20 Associations from Four Genome-Wide Association Study (GWAS) Programs with Varied Input Data Quantity.
Itsik Pe’er, Columbia University
Eleazar Eskin, University of California, Los Angeles
Program Committee Chairs
Simon Gravel, McGill University, Canada
Hugues Aschard, Institut Pasteur, France