12 SNP Panels & Genotyping

12.1 Partial Genotyping

# Only genotype 80% of individuals
pop <- breeding.diploid(
  pop,
  genotyping.gen = 3,
  share.genotyped = 0.8
)

# Check who's genotyped
genotyped_status <- get.genotyped(pop, gen = 3)

12.2 Genotyping Arrays (Chips)

# Define which SNPs are on chip
chip_snps <- seq(1, 50000, by = 10)  # Every 10th SNP

pop <- creating.diploid(
  nsnp = 50000,
  nindi = 500,
  genotyped.s = rep(0, 50000)  # Start with none genotyped
)

# Set chip SNPs as genotyped
pop$info$snp$genotyped[chip_snps] <- 1

12.3 Genotyping Costs

# Track costs
costs <- compute.costs.cohorts(
  pop,
  cohorts = "Gen5",
  cost.genotyping = 50,      # $50 per sample
  cost.phenotyping = 200     # $200 per phenotype
)

print(costs$total.costs)

12.4 Summary

Partial genotyping strategies
SNP chip simulation
Cost tracking

Continue to Chapter 13: Genomic Prediction!

# SNP Panels & Genotyping {#sec-snp-panels}

## Partial Genotyping

```{r}
#| eval: false
# Only genotype 80% of individuals
pop <- breeding.diploid(
  pop,
  genotyping.gen = 3,
  share.genotyped = 0.8
)

# Check who's genotyped
genotyped_status <- get.genotyped(pop, gen = 3)
```

## Genotyping Arrays (Chips)

```{r}
#| eval: false
# Define which SNPs are on chip
chip_snps <- seq(1, 50000, by = 10)  # Every 10th SNP

pop <- creating.diploid(
  nsnp = 50000,
  nindi = 500,
  genotyped.s = rep(0, 50000)  # Start with none genotyped
)

# Set chip SNPs as genotyped
pop$info$snp$genotyped[chip_snps] <- 1
```

## Genotyping Costs

```{r}
#| eval: false
# Track costs
costs <- compute.costs.cohorts(
  pop,
  cohorts = "Gen5",
  cost.genotyping = 50,      # $50 per sample
  cost.phenotyping = 200     # $200 per phenotype
)

print(costs$total.costs)
```

## Summary
- Partial genotyping strategies
- SNP chip simulation
- Cost tracking

Continue to [Chapter 13: Genomic Prediction](13-genomic-prediction.qmd)!