Non-SOT Event: Quantitative Genomics Training: Methods and tools for whole-genome and transcriptome

This two-day intensive workshop presented by the Columbia University Mailman School of Public Health will provide a rigorous introduction to several different techniques to analyze whole-genome sequencing and transcriptome data. Led by a team of experts in statistical genomics and bioinformatics, who have developed their own methods to analyze such data, the training will integrate seminar lectures with hands-on computer lab sessions to put concepts into practice. The training will focus on reviewing existing approaches based on predicted expression association with traits, colocalization of causal variants, and Mendelian Randomization, including discussion on how they relate to each other, and their advantages and limitations. Emphasis will also be given to reviewing integrative sequence-based association studies for whole-genome sequencing data, and functional annotation of variants in noncoding regions of the genome.

Investigators at all career stages are welcome to attend, and we particularly encourage trainees and early-stage investigators to participate. There are three requirements to attend this workshop:

1. Each participant must have an introductory background in statistics and genetics, and/or in the statistical analysis of genetic data.
2. Experience using R is recommended to get the most out of lab sessions.
3. Each participant should have a laptop with R/RStudio downloaded and installed prior to the first day of training. All lab sessions will be done using Posit Cloud (formerly RStudio Cloud).

Capacity is limited. Paid registration is required to attend.