Genomics Data Analysis Course: ConGen 2026 Theme: Applications of genomics in ecology, evolution, and conservation. see: www.umt.edu/congen/ Course Objective: To provide training in conceptual and practical approaches using genomic data to address key research questions. You will learn the coalescent-, Bayesian-, and likelihood-based approaches. We emphasize next-generation sequencing data analysis (RAD-seq, DNA-capture, whole genomes) and the interpretation of output from important statistical approaches, pipelines, and software, taught by 15 + expert instructors. You'll learn R and Linux and take raw reads through to genotype calling, assemble a genome, estimate pop effective sizes (Ne), inbreeding, detect selection (landscape genomics), estimate gene flow & dispersal rates, parentage, & more. Who should apply: Advanced undergraduates, M.S. and Ph.D. students, post-docs, faculty, and PIs with a basic understanding of population genetics. We teach R and Linux skills the first weeks to ensure your success. Overseas participation is common, strongly encouraged, and facilitated by video-recordings of lectures. Where: Online (Zoom). Lectures are video-recorded for asynchronous participation (e.g., by overseas participants). When: Monday, Wednesday & Friday, 8-9:50 AM (Mountain time, USA), Sept 24th - Nov. 13th (20 + lectures) Instructors: Eric Anderson, Ellie Armstrong, Chris Funk, Marty Kardos, Brenna Forester, Will Hemstrom, Paul Hohenlohe, Gordon Luikart, Rena Schweizer, Arun Sethuraman, Bruce Rannala, Steve Spear, Robin Waples, Schuyler Liphardt, and more... For more details and to Apply see: www.umt.edu/congen/ Registration: costs $890 and includes all lectures and video-recorded Q&A sessions for later viewing, hands-on exercises with worksheets & genomic datasets, PowerPoint slides, recommended readings, and individual advice from instructors on your research. Course credit: 3 course credits are available through The Univ of Montana (BIOB 595 Pop Gen Data Analysis). Selected lecture topics: see www.umt.edu/congen/. The history and role of genomics in population genetic and conservation - a thorough overview! Pop genomics: Concepts and tools to answer eco-evo questions R & Linux basics, FastQ file format for next-generation sequencing data Scripting, data handling, & organizing bioinformatics projects Probability, Bayesian statistics, MCMC, and genotype likelihood calculations The Coalescent: Theory and applications Raw sequence read filtering and genotype calling (with and without a reference genome) Filtering (QC) best practices, and effects of Filtering choices on downstream analyses Inbreeding and runs of homozygosity (RoH) Genome sequencing and assembly: Conceptual and practical aspects *PacBio, and Nanopore representatives will present recent technologies and services Inferring population structure and conservation units Effective population size estimation Assignment tests for quantifying gene flow, dispersal, and forensics testing (WGSassign, GeneClass) Gene flow estimation (BayesAss - a new version) Hybridization quantification (IM models) Detecting local adaptation and adaptive loci (Landscape Genomics) Phylogeny and phylogenomics eDNA Metabarcoding applications (biodiversity monitoring, diet analysis, microbiomes, etc.) Past course review publications: Hendricks et al. 2018: https://onlinelibrary.wiley.com/doi/full/10.1111/eva.12659; Rena Schweizer et al. 2021: https://doi.org/10.1093/jhered/esab019 Schiebelhut et al 2023: doi.org/10.1111/1755-0998.13893 ; Hemstrom et al. 2024: Next-generation data filtering. doi: 10.1038/s41576-024-00738-6 *We teach a similar course in Ecuador in Jan. 2028 (with optional trip to the Galapagos Islands, & a cloud forest field station) "gordon.luikart@mso.umt.edu" (to subscribe/unsubscribe the EvolDir send mail to golding@mcmaster.ca)