💡 Cheng Lab at UC Davis

Our research interests are broadly involved in the development of statistical and computational methods for the (genetic) improvement of populations through more accurate, efficient, and biologically meaningful analysis. We have focused on the use of genomics, phenomics, pedigree, and other sources of big data in various species to better predict desired traits. These endeavours include

• 🧮 theoretical aspects of quantitative genetics including statistical models and computational algorithms (e.g., genomic prediction; genome-wide association studies)
• 💾 the development of software tools to apply these methods to real-life large genomic and phenomic data
• 🐖 the application of the software to data sets in routine analysis for a wide range of traits in various species.

🚢 Projects

We are working on interesting projects! Click the dropdown menu to find more.

Details

🧮 Software Tools

$$ Software\ Packages $$

<aside> 🧬 **JWAS**

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genotype  = get_genotypes("genotypes.csv")
pedigree  = get_pedigree("pedigree.csv")
model     = build_model("y = intercept + ID + genotype")
set_random(model,"ID",pedigree)
out       = runMCMC(model,phenotypes)

<aside> 🖥️ XSim

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#simulate sequence data and pedigree structures
build_genome(numChr,chrLength,nLoci,nQTL)
sires = sampleFounders(nfounders)
dams  = sampleFounders(nfounders)
sires1,dams1,gen1 = sampleRan(popSize, ngen, sires, dams)

<aside> 🔑 LPChoose

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#Optimizing Sequencing Resources in Genotyped Populations
LPChoose("data.csv",ninds)

$$ Interactive\ Web\ Apps $$

<aside> <img src="https://img.icons8.com/ios/250/000000/linkedin.png" alt="https://img.icons8.com/ios/250/000000/linkedin.png" width="40px" /> ShinyJWAS

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<aside> 🍋 LMMonBoard

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width="40px" /> Diagnostic Imaging

</aside>

🌎 Teaching

Poker Cards for Quantitative Genetics

🌎 People