FAStdIncidenceRateResults-class {FamAgg} | R Documentation

## Familial Standardized Incidence Rate

### Description

The `FAStdIncidenceRateResults` object contains the results from a familial standardized incidence rate (FSIR) calculation employing in addition Monte Carlo simulations to assess significance levels for the individuals' FSIRs.

The FSIR weights the disease status of relatives based on their degree of relatedness with the proband (Kerber, 1995). Formally, the FSIR is defined as the standardized incidence ratio (SIR) or standardized morality ratio in epidemiology, i.e. as the ratio between the observed and expected number of cases, only that both are in addition also weighted by the degree of relatedness (i.e. kinship value) between individuals in the pedigree.

### Usage

    ## S4 method for signature 'FAStdIncidenceRateResults'
    fsir(object, trait=NULL, lambda=NULL,
                                               timeInStrata=NULL,
                                               ...)

    ## S4 method for signature 'FAStdIncidenceRateResults'
    lambda(object, ...)

    ## S4 method for signature 'FAStdIncidenceRateResults'
    plotPed(object, id=NULL, family=NULL,
                                                  filename=NULL, device="plot",
                                                  only.phenotyped=FALSE, ...)

    ## S4 method for signature 'FAStdIncidenceRateResults'
    plotRes(object, id=NULL, family=NULL,
                                                  addLegend=TRUE, type="density", ...)

    ## S4 method for signature 'FAStdIncidenceRateResults'
    result(object, method="BH")

    ## S4 method for signature 'FAStdIncidenceRateResults'
    resultForId(object, id=NULL)

    ## S4 method for signature 'FAStdIncidenceRateResults'
    runSimulation(object, nsim=50000,
                                                        lambda=NULL,
                                                        timeInStrata=NULL,
                                                        strata=NULL,
                                                        ...)

    ## S4 method for signature 'FAStdIncidenceRateResults'
    timeInStrata(object)

    ## S4 replacement method for signature 'FAStdIncidenceRateResults'
    trait(object) <- value

### Arguments

(in alphabetic order)

`addLegend` | For `plotRes`: if a legend should be added to the plot.
`device` | For `plotPed`: see `plotPed` for more details.
`family` | For `plotPed`: the family for which the pedigree should be plotted. For `plotRes`: not supported.
`filename` | For `plotPed`: the file name to which the pedigree plot should be exported. See `plotPed` for more details.
`id` | For `plotPed` and `plotRes`: the id of the indiviual for which the pedigree or the simulation result should be plotted. Note: `id` can be a `numeric` or a `character`. Numeric ids will be internally converted to `character`. For `resultForId`: the ID of the individual from which the result should be returned.
`lambda` | Numeric vector with the incidence rates per stratum from the population. The length of this vector has to match the number of columns of argument `timeInStrata`. For `fsir`: not used.
`method` | The multiple hypothesis testing method. All methods supported by `p.adjust` are allowed.
`nsim` | Number of simulations.
`object` | The `FAStdIncidenceRateResults` object.
`only.phenotyped` | For `plotPed`: Wheter only phenotyped individuals, i.e. individuals with a non-NA value in column `affected` (the trait information). If `TRUE`, the function removes all non-phenotyped individuals, keeping only those that are required for the pedigree to be complete.
`strata` | For `runSimulation`: a numeric, character of factor characterizing each individual in the pedigree. The length of this vector and the ordering has to match the pedigree. This vector allows to perform stratified random sampling. See details on the `PedigreeAnalysis` help page or examples for more information.
`timeInStrata` | For `runSimulation`: a numeric matrix specifying the time at risk for each individual in each strata. Columns represent the strata, rows the individuals, each cell the time at risk for the individual in the respective strata. See example below. The `factor2matrix` could be useful in generating such a table. For `fsir`: not used.
`trait` | For `fsir`: not used.
`type` | For `plotRes`: at present only `"density"` is supported.
`value` | For `trait<-`: can be a named numeric, character or factor vector. The names (at least some of them) have to match the ids in the pedigree of the object.
`...` | For `plotPed`: additional arguments to be submitted to the internal `buildPed` call and to `plotPed`. For `runSimulation`: additional arguments `prune` and `lowMem`. See below for details.

### Details

Monte Carlo simulation and empirical p-value estimation: see details of `FAIncidenceRateResults` as the concept and calculation is essentially identical.

Calling the `runSimulation` method on a `FAStdIncidenceRateResults` object is the same as calling the `fsirTest` on a `FAData` object. In the first case the simulation is performed using the trait information data stored internally in the object, while in the latter case the trait information have to be submitted to the function call.

By providing argument `strata`, the stratified random sampling is performed. See example below and the details section in `PedigreeAnalysis` for more details.

The FSIR can also be directly calculated, without simulation, using the `fsir` method of a `FAData` object.

A call to the setter methods `trait<-` resets any simulation results present in the `sim` slot, thus, the object can be re-used to perform a simulation analysis using the new trait data.

By default the Monte Carlo p-value estimation in the `runSimulation` method is quite memory demanding. For very large pedigrees the optional argument `lowMem=TRUE` might be passed to the method which results in faster and less memory demanding calculations. This will however disable the `plotRes` method on the resulting `FAStdIncidenceRateResults` as the distribution of FSIR from the simulation runs is no longer reported.

Note: the FIR for singletons and individuals that do not share kinship with at least one other phenotyped individual that has also a valid value in argument `timeAtRisk` (and eventually `strata`) will be `NA`.

### Value

Refer to the method and function description above for detailed information on the returned result object.

### Objects from the Class

`FAStdIncidenceRateResults` objects are created by the `fsirTest` method on a `FAData` object.

### Extends

Class `FAData` directly.

### Slots

nsim

  Number of simulations.

sim

  The result of the simulation. This slot should not be accessed directly, use the `result` method to extract result information.

timeInStrata

  Numeric matrix specifying the time at risk in each strata (represented by the columns) of each individual (rows). Use the accessor method `timeInStrata` to extract this data.

lambda

  Numeric vector with the incidence rates per stratum from the population.

### Methods and Functions

object$name

  Access various results and data stored in the object. `name` can be `fsir`, `pvalue`, `lambda` or `timeInStrata` to access the FSIR, the (raw) p-value from the simulation analysis, the lambda or the time in strata.

fsir

  Returns the FSIR values calculated by a call to the `runSimulation` method or `fsir` method on a `FAData` object. In contrast to that latter method, which directly calculates the values, this method returns the values from a calculation stored inside the `FAStdIncidenceRateResults` object.

  The method returns a named numeric vector with the familial incidence rates, the names being the ID of the individuals. Singletons as well as individuals that, after removing not phenotyped individuals or individuals without time at risk, do not share kinship with any other individual in the pedigree have a value of `NA`.

plotPed

  Plots a pedigree for one of the affected individuals in the simulation results. The id of the selected affected individual (specified with argument `id`) is highlighted in red. The FSIR value for each individual is drawn below the individual's id. See `plotPed` for more details.

plotRes

  Plots the distribution of expected FSIR calculated for the selected individuals from Monte Carlo simulations along with the actually observed FSIR.

result

  Returns the result from the simulation as a `data.frame` with columns:

  `"trait_name"`: the name of the trait.

  `"total_phenotyped"`: total number of phenotyped individuals in the trait.

  `"total_affected"`: total number of affected individuals in the trait.

  `"total_tested"`: the number of individuals in the pedigree considered for the simulation. This corresponds to all individuals with valid, non-NA, values in trait, timeAtRisk and eventually strata.

  `"id"`: the id of the individual.

  `"family"`: the family id.

  `"fsir"`: the familial standardized incidence rate. Note that this will be

  `NA` for all non-phenotyped individuals and singletons in the pedigree as well as for individuals that do not share kinship with at least one other phenotyped individual with valid time at risk (or valid value in parameter `strata`).

  `"pvalue"`: the p-value for the significance of the familial standardized incidence rate assessed by Monte Carlo simulations.

  `"padj"`: the p-value adjusted for multiple hypothesis testing (with the method specified with argument `method`).

  The returned `data.frame` is sorted by column `"pvalue"`, its row names correspond to column `"id"`.

resultForId

  Extracts results information for a given individual. The method returns a `list` with elements `"id"`, `"fsir"`, `"pvalue"`, `"timeInStrata"` and `"lambda"` with the ID of the individual, the FSIR and corresponding p-value estimated by the simulation, the row from the `timeInStrata` matrix of the individual and the `lambda` (incidence rates from the population).

runSimulation

  Performs the simulation analysis based on the pedigree and trait information stored in the object as well as the time at risk provided with argument `timeAtRisk`. Returns a `FAStdIncidenceRateResults` object with the results from the simulation.

trait<-

  Set the trait information. This method will reset all simulation results saved in the `sim` slot.

### Note

Subsetting (using the `[` operator) is not supported.

### Author(s)

Johannes Rainer

### References

Kerber, R.A. (1995) Method for calculating risk associated with family history of a disease. Genet Epidemiol, pp 291–301.

### See Also

`FAData`, `kinship`, `trait`, `probabilityTest`, `kinshipGroupTest`, `kinshipSumTest`, `genealogicalIndexTest`, `familialIncidenceRateTest`, `fsirTest`, `plotPed`, `estimateTimeAtRisk`

### Examples

    ##########################
    ##
    ##  Perform the simulation analysis
    ##
    ## Load the test data.
    data(minnbreast)

    ## Subset to some families and generate a pedigree data.frame.
    mbsub <- minnbreast[minnbreast$famid == 4 | minnbreast$famid == 5 |
                        minnbreast$famid == 6 | minnbreast$famid == 7 |
                        minnbreast$famid == 411, ]
    PedDf <- mbsub[, c("famid", "id", "fatherid", "motherid", "sex")]
    colnames(PedDf) <- c("family", "id", "father", "mother", "sex")

    ## Generate the FAData.
    fad <- FAData(pedigree=PedDf)

    ## Specify the trait.
    tcancer <- mbsub$cancer
    names(tcancer) <- mbsub$id

    ## Next we have to specify lambda and the timeInStrata matrix.
    ## For lambda we use information from Cancer Research UK:
    ## New breast cancer cases in females per year and 100000: 155.3
    ## New breast cancer cases in males per year and 100000:     1.1
    ## New prostate cancer cases in females per year and 100000: 0
    ## New prostate cancer cases in males per year and 100000: 134.3
    lbda <- c(M=(1.1+134.4)/100000, F=155.3/100000)

    ## Next we need the time at risk of each individual in each strata.
    ## For strata we use male and females, for the time at risk we use
    ## column "endage":
    stratMat <- factor2matrix(fad$sex)
    ## Next we have to multiply that with the endage, since each person
    ## spent that time "at risk" to get cancer.
    stratMat <- stratMat * mbsub$endage

    ## Running the simulation
    fsirs <- fsirTest(fad, trait=tcancer, traitName="cancer", lambda=lbda,
                      timeInStrata=stratMat, nsim=500)

    ## Showing some of the results
    head(result(fsirs))

    ## Extract the FSIR
    head(fsirs$fsir)

    ## We can also directly access the p-values from the simulation,
    ## these are however the raw, unadjusted p-values.
    head(fsirs$pvalue)

    ## Get the time in strata for each individual
    head(fsirs$timeInStrata)

    ## Plot the pedigree for a family with significant FSIRs.
    ## The numbers below the IDs of the individuals represent the actual
    ## FSIR values.
    plotPed(fsirs, family=result(fsirs)$family[1])

    ## Plot also the result from the simulation run.
    plotRes(fsirs, id=result(fsirs)$id[1])

    ## Extract the data and result for an individual
    resultForId(fsirs, id="16424")

[Package FamAgg version 1.10.4 Index]