R: Summarize the results of a genome scans

summary.scanone {qtl} | R Documentation

## Summarize the results of a genome scans

### Description

Print the rows of the output from `scanone` that correspond to the maximum LOD for each chromosome, provided that they exceed some specified thresholds.

### Usage

    ## S3 method for class 'scanone'
    summary(object, threshold,
            format=c("onepheno", "allpheno", "allpeaks", "tabByCol", "tabByChr"),
            perms, alpha, lodcolumn=1, pvalues=FALSE,
            ci.function=c("lodint", "bayesint"), ...)

### Arguments

`object` | An object output by the function `scanone`.
`threshold` | LOD score thresholds. Only peaks with LOD score above this value will be returned. This could be a single number or (for formats other than `"onepheno"`) a threshold for each LOD score column. If `alpha` is specified, `threshold` should not be.
`format` | Format for the output. See Details, below.
`perms` | Optional permutation results used to derive thresholds or to calculate genome-scan-adjusted p-values. This must be consistent with the `object` input, in that it must have the same number of LOD score columns, though it can have just one column of permutation results, in which case they are reused for all LOD score columns in the `scanone` output, `object`. (These can also be permutation results from `scantwo`, which permutations for a one-dimensional scan.)
`alpha` | If perms are included, this is the significance level used to calculate thresholds for determining which peaks to pull out. If `threshold` is specified, `alpha` should not be.
`lodcolumn` | If `format="onepheno"`, this indicates the LOD score column to focus on. This should be a single number between 1 and the number of LOD columns in the object input.
`pvalues` | If TRUE, include columns with genome-scan-adjusted p-values in the results. This requires that `perms` be provided.
`ci.function` | For formats `"tabByCol"` and `"tabByChr"`, indicates the function to use to get approximate confidence intervals for QTL location.
`...` | For formats `"tabByCol"` and `"tabByChr"`, additional arguments are passed to the function indicated by `ci.function` (for example, `drop` for `lodint` or `prob` for `bayesint`, or `expandtomarkers` for either).

### Details

This function is used to report loci deemed interesting from a one-QTL genome scan (by `scanone`).

For `format="onepheno"`, we focus on a single LOD score column, indicated by `lodcolumn`. The single largest LOD score peak on each chromosome is extracted. If `threshold` is specified, only those peaks with LOD meeting the threshold will be returned. If `perms` and `alpha` are specified, a threshold is calculated based on the permutation results in `perms` for the significance level `alpha`. If neither `threshold` nor `alpha` are specified, the peak on each chromosome is returned. Again note that with this format, only the LOD score column indicated by `lodcolumn` is considered in deciding which chromosomes to return, but the LOD scores from other columns, at the position with maximum LOD score in the `lodcolumn` column, are also returned.

For `format="allpheno"`, we consider all LOD score columns, and pull out the position, on each chromosome, showing the largest LOD score. The output thus may contain multiple rows for a chromosome. Here `threshold` may be a vector of LOD score thresholds, one for each LOD score column, in which case only those positions for which a LOD score column exceeded its threshold are given. If `threshold` is a single number, it is applied to all of the LOD score columns. If `alpha` is specified, it must be a single significance level, applied for all LOD score columns, and again `perms` must be specified, and these are used to calculate the LOD score threshold for the significance level `alpha`.

For `format="allpeaks"`, the output will contain, for each chromosome, the maximum LOD score for each LOD score column, at the position at which it achieved its maximum. Thus, the output will contain no more than one row per chromosome, but will contain the position and maximum LOD score for each of the LOD score columns. The arguments `threshold` and `alpha` may be specified as for the `"allpheno"` format. The results for a chromosome are returned if at least one of the LOD score columns exceeded its threshold.

For `format="tabByCol"`, there will be a separate table for each LOD score column, with a single peak per chromosome. Included are columns indicating chromosome, peak position, lower and upper limits of the confidence interval calculated via `lodint` or `bayesint`, and lod score.

The output for `format="tabByChr"`, is similar to that of `format="tabByCol"`, but with results organized by chromosome rather than by LOD score column.

If `pvalues=TRUE`, and `perms` is specified, genome-scan-adjusted p-values are calculated for each LOD score column, and there are additional columns in the output containing these p-values.

In the case that X-chromosome specific permutations were performed (with `perm.Xsp=TRUE` in `scanone`), autosome- and X-chromosome specific thresholds and p-values are calculated by the method in Broman et al. (2006).

### Value

An object of class `summary.scanone`, to be printed by `print.summary.scanone`.

### Author(s)

Karl W Broman, broman@wisc.edu

### References

Broman, K. W., Sen, Ś, Owens, S. E., Manichaikul, A., Southard-Smith, E. M. and Churchill G. A. (2006) The X chromosome in quantitative trait locus mapping. Genetics, 174, 2151–2158.

### See Also

`scanone`, `plot.scanone`, `max.scanone`, `subset.scanone`, `c.scanone`, `summary.scanoneperm` `c.scanoneperm`

### Examples

    data(fake.bc)

    fake.bc <- calc.genoprob(fake.bc, step=5)

    # genome scan by Haley-Knott regression
    out <- scanone(fake.bc, method="hk")

    # permutation tests
    ## Not run: operm <- scanone(fake.bc, method="hk", n.perm=1000)

    # peaks for all chromosomes
    summary(out)

    # results with LOD >= 3
    summary(out, threshold=3)

    # the same, but also showing the p-values
    summary(out, threshold=3, perms=operm, pvalues=TRUE)

    # results with LOD meeting the 0.05 threshold from the permutation results
    summary(out, perms=operm, alpha=0.05)

    # the same, also showing the p-values
    summary(out, perms=operm, alpha=0.05, pvalues=TRUE)

    ##### summary with multiple phenotype results
    out2 <- scanone(fake.bc, pheno.col=1:2, method="hk")

    # permutations
    ## Not run: operm2 <- scanone(fake.bc, pheno.col=1:2, method="hk", n.perm=1000)

    # results with LOD >= 2 for the 1st phenotype and >= 1 for the 2nd phenotype
    #     using format="allpheno"
    summary(out2, thr=c(2, 1), format="allpheno")

    # The same with format="allpeaks"
    summary(out2, thr=c(2, 1), format="allpeaks")

    # The same with p-values
    summary(out2, thr=c(2, 1), format="allpeaks", perms=operm2, pvalues=TRUE)

    # results with LOD meeting the 0.05 significance level by the permutations
    #     using format="allpheno"
    summary(out2, format="allpheno", perms=operm2, alpha=0.05)

    # The same with p-values
    summary(out2, format="allpheno", perms=operm2, alpha=0.05, pvalues=TRUE)

    # The same with format="allpeaks"
    summary(out2, format="allpeaks", perms=operm2, alpha=0.05, pvalues=TRUE)

    # format="tabByCol"
    summary(out2, format="tabByCol", perms=operm2, alpha=0.05, pvalues=TRUE)

    # format="tabByChr", but using bayes intervals
    summary(out2, format="tabByChr", perms=operm2, alpha=0.05, pvalues=TRUE,
            ci.function="bayesint")

    # format="tabByChr", but using 99% bayes intervals
    summary(out2, format="tabByChr", perms=operm2, alpha=0.05, pvalues=TRUE,
            ci.function="bayesint", prob=0.99)

[Package qtl version 1.46-2 Index]