Genomics in Non-Model Organisms: How to build an ortholog map *Peer-to-Peer* Fall season 2023
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Genomics in Non-Model Organisms: How to build an ortholog map *Peer-to-Peer* Fall season 2023 In-Person
Description:
Non-traditional animal models in genomics refer to species that are not typically used as the primary subjects of genetic and genomic research, in contrast to well-established model organisms like mice, fruit flies, and nematodes. These non-traditional models encompass a diverse range of animal species, including those from various taxonomic groups, ecological niches, and evolutionary histories. Working with non-traditional animal models in genomics contributes to a more comprehensive understanding of genetics, genomics, and evolutionary biology. Research with these models must address specific challenges related to data acquisition, analysis, and interpretation, as these species often lack well-annotated reference genomes and data resources. To overcome some of these challenges, join us to learn how to build an ortholog map that will help you establish evolutionary relationships between genes in non-traditional animal models and well-studied organisms. This invaluable tool aids in transferring functional annotations, leveraging knowledge from established model species to enhance our understanding of gene function, pathways, and evolutionary dynamics in non-traditional models.
You will learn how to:
- Address specific challenges in genomics of non-traditional models.
- Build a high-quality ortholog map using pairwise orthologs in R.
- Evaluate the quality of an ortholog pair.
Requirements:
You can follow this workshop as a demonstration or bring your laptop installed with R Studio and the libraries: biomart and tidyverse. The code will be provided for attendees to build their own ortholog map.
- Date:
- Thursday, December 7, 2023
- Time:
- 10:00am - 12:00pm
- Time Zone:
- Eastern Time - US & Canada (change)
- Location:
- SHM L 111, Cushing/Whitney Medical Library, 333 Cedar Street
- Campus:
- Medical School
- Categories:
- Bioinformatics