Setegn Worku Alemu - Quantitative Geneticist

Hello.

I am a quantitative geneticist specializing in advanced statistical methods for genetic analysis.

I have extensive experience in linear mixed models, Bayesian statistics, and developing professional Shiny applications for genetic data analysis.

Research Interests

Genomic selection and prediction models in diverse species
Implementation of applied genomic selection in international breeding programs
Integration of multi-omics data for improved genetic predictions
Statistical methods for complex trait analysis in livestock and crops
Development of computational tools for large-scale genetic data analysis
Climate-smart breeding strategies and genetic approaches to sustainability

Current Focus: Climate-Smart Breeding

Genomics-driven methane reduction in sheep breeding.

Incorporating genomics, RNA, and microbiome data to enhance prediction accuracy for methane emissions in sheep, contributing to climate change mitigation efforts.

Expertise in Quantitative Genetics

Advanced Statistical Methods

Proficient in applying and developing advanced statistical methods for genetic analysis, including linear mixed models, Bayesian approaches, and machine learning techniques in genetics.

Computational Skills

Experienced in developing efficient algorithms and software for large-scale genetic data analysis, with a focus on R, Python, Julia, and JavaScript for high-performance computing in genetics.

Specialized Software and Tools

ASReml, BLUPF90, DMU: For mixed model analysis and genetic evaluations
JWAS, GCTA: For genomic analyses
R Shiny: For developing interactive web applications
Django: For web-based genetic data management systems
Leaflet & D3: For geographical visualization of genetic data

Shiny Applications for Quantitative Genetics

Genomic Prediction using Functional SNP
Integrates functional genomic information to enhance genomic prediction accuracy.
Linkage Disequilibrium for Crossbred Populations
Analyzes and visualizes LD patterns in complex crossbred populations.
Genomic Selection in Broiler
Implements genomic selection models specifically tailored for broiler breeding programs.
ACGG Project Data Analysis
Comprehensive dashboard for analyzing and visualizing data from the African Chicken Genetic Gains project.
Climate-Integrated Genetic Analysis
Incorporates climate data into genetic analyses to study gene-environment interactions.

Get In Touch

For collaborations or inquiries about quantitative genetics research.

I am passionate about advancing quantitative genetics and its applications in breeding programs.

CONTACT ME