The 9th 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.

 

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REGISTRATION

There are no registration fees to attend RECOMB-Genetics2021  virtual satellite event  but registration is still required.

See registration page

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PRELIMINARY PROGRAM

(ALL TIMES US EASTERN TIME)

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Thursday, September 2

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9:45  - 9:50  WELCOME REMARKS

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9:50 -  10:50 KEYNOTE TALK 1

chair: Anna Sapfo Malaspinas

 

Functional variation in the human genome: lessons from the transcriptome

Tuuli Lappalainan

 

11:05 - 11:55  CONTRIBUTED SESSION 1

chair: Itsik Pe'er

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Towards haplotype-specific chromatin contact maps from GAM data

Julia Markowski

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SIEVE: Joint Inference of Tumor Phylogeny and Variant Calling from Single-cell DNA Sequencing Data

Senbai Kang

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Haplotype-aware inference of human chromosome abnormalities

Daniel Ariad

 

CONET: Copy number event tree model of evolutionary tumor history for single-cell data

Magda Markowska

 

12:10 - 12:50 CONTRIBUTED SESSION 2

chair: Sriram Sankararaman

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SPRISS: Approximating Frequent k-mers by Sampling Reads, and Applications

Fabio Vandin or Leonardo Pellegrina

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Quantifying negative selection on synonymous variants

Mikhail Gudkov

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Integration of Network-Based Functional Prediction and Imaging GWAS Identifies Candidate Genes for AD-Related Neurodegeneration

Jeffrey Brabec

 

13:00 - 14:00 KEYNOTE TALK 2

chair: Gillian Belbin

 

Polygenic prediction and evolution of complex traits

Iain Mathieson

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14:00 - 14:05 Concluding remarks

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INVITED SPEAKERS

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Tuuli Lappalainen,  New York Genome Center, KTH Royal Institute of Technology and SciLifeLab 

Iain Mathieson, University of Pennsylvania

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STEERING COMMITTEE

Anna Sapfo-Malaspinas

Itsik Peer

Gillain Belbin

Sriram Sankararaman

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CONTRIBUTED PAPERS

Paper submission is now closed. Papers will be chosen from submissions made to the main Conference.

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