qtl (version 1.39-5)

inferredpartitions: Identify inferred partitions in mapping QTL to a phylogenetic tree

Description

Identify the inferred partitions for a chromosome from the results of scanPhyloQTL.

Usage

inferredpartitions(output, chr, lodthreshold, probthreshold=0.9)

Arguments

output

An object output by the function scanPhyloQTL.

chr

A character string indicating the chromosome to consider. (It can also be a number, but it's then converted to a character string.)

lodthreshold

LOD threshold; if maximum LOD score is less than this, the null model is considered.

probthreshold

Threshold on posterior probabilities. See Details below.

Value

A vector of character strings. If the null model (no QTL) is inferred, the output is "null". Otherwise, it is the set of inferred partitions.

Details

We consider a single chromosome, and take the maximum LOD score for each partition on that chromosome. The presence of a QTL is inferred if at least one partition has LOD score greater than lodthreshold. In this case, we then convert the LOD scores for the partitions to approximate posterior probabilities by taking $10^LOD$ and then rescaling them to sum to 1. These are sorted from largest to smallest, and we then take as the inferred partitions the smallest set whose posterior probabilities cumulatively add up to at least probthreshold.

References

Broman, K. W., Kim, S., An\'e, C. and Payseur, B. A. Mapping quantitative trait loci to a phylogenetic tree. In preparation.

See Also

scanPhyloQTL, plot.scanPhyloQTL, summary.scanPhyloQTL, max.scanPhyloQTL, simPhyloQTL

Examples

# example map; drop X chromosome
data(map10)           
map10 <- map10[1:19]


# simulate data
x <- simPhyloQTL(4, partition="AB|CD", crosses=c("AB", "AC", "AD"),
                 map=map10, n.ind=150,
                 model=c(1, 50, 0.5, 0))

# run calc.genoprob on each cross
## Not run: x <- lapply(x, calc.genoprob, step=2)


# scan genome, at each position trying all possible partitions
out <- scanPhyloQTL(x, method="hk")

# inferred partitions
inferredpartitions(out, chr=3, lodthreshold=3)

# inferred partitions with prob'y threshold = 0.95
inferredpartitions(out, chr=3, lodthreshold=3, probthreshold=0.95)