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Cassavabase SolGS presentation PAG 2016
The document describes solGS, a web-based tool for genomic selection in plant and animal breeding. solGS allows users to store genotype and phenotype data, compose training populations, build prediction models using RR-BLUP or GBLUP, predict breeding values for selection candidates, and perform additional analyses like estimating genetic correlations and calculating selection indices. The tool addresses challenges of large genomic data volumes and enables data cleaning, imputation, statistical modeling, and interactive visualization. Models are fitted using 10-fold cross-validation, and solGS provides options for composing training populations by trait, trial, or custom individual lists.
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Cassavabase SolGS presentation PAG 2016
- 1. solGS: A Web-based Solution for Genomic Selection Isaak Y Tecle, Naama Menda, Guillaume Bauchet, Lukas Mueller Tecle et al. Bioinformatics 2014, 15:398
- 2. Phenotyped & genotyped individuals Genomic selection… Prediction model Predicted breeding Values (GEBVs) Genotyped selection candidates Training population
- 3. Challenges… n Data volume, storage n Data structuring, cleaning, imputation n Statistical analysis complexity n visualization and sharing
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- 5. What you can do with solGS… n Store data n Chado Natural Diversity schema n Compose training populations n Build models and predict breeding values of selection candidates n Test model accuracy
- 6. What you can do with solGS… n Explore phenotype data, population structure n Check on relationship between GEBVs vs observed phenotypes n Calculate selection indices, correlation n Visualize data on interactive plots
- 7. What is the statistical approach behind solGS?
- 8. …preparing data n Omits individuals completely missing phenotype values n Adjusts phenotype values for block effects n Averages across multiple trials after adjusting for block effects n Imputes missing marker data n Median substitution
- 9. …statistical modeling n Univariate nRR-BLUP n Endelman, Plant Genome (2010) n GBLUP n Marker-based realized relationship matrix n Prediction accuracy n Based on 10-fold cross-validation
- 10. How does solGS work?
- 12. Composing a training population: Fitting a prediction model... 3 options
- 14. Fitting a prediction model… Option 1: Search using a trait name
- 26. Estimating breeding values of selection candidates Applying the model…
- 29. Fitting a prediction model… Option 2: Search for trials
- 36. Estimating breeding values of a selection candidates for multiple traits Applying the models…
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- 43. Fitting a prediction model… Option 3: use your own list of individuals
- 46. To sum up… nStore data n Build prediction models n Estimate breeding values n Additional analyses: n Correlation analysis n Population structure n Selection indices n http://cassavabase.org/solgs n Open source code
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- 49. Many thanks!! Background image: nextgencassava.org