updateRI {TargetSearch} | R Documentation

## Updating Time Index correction

### Description

This function can be used to correct or adjust the detected retention time index (RI) markers or their location to specific retention times. This function adds on `fixRI()` as it also corrects the RI of the CDF files

### Usage

    updateRI(samples, rimLimits, RImatrix = NULL, quiet = TRUE)

### Arguments

`samples` | A tsSample object created by ImportSamples.
`rimLimits` | A tsRim object. See ImportFameSettings.
`RImatrix` | An optional matrix. It represents a retention time matrix of the detected retention time markers that was obtained after running RIcorrect
`quiet` | Logical. Do not print a list of converted files.

### Details

Sometimes the retention time of the RI markers are not detected correctly, either because there was a problem with the standard, or the time limits of the tsRim object were not set correctly, or simply because the markers are not injected with the samples.

In any case, the retention time correction can be fixed by calling this function. This function works almost exactly like `fixRI()`, in fact, it is called internally, and allows correction of RIfiles and CDFfiles at the same time. Check also the documentation of `fixRI()` for extra details.

The parameters are the tsSample and the tsRim object, with optionally a `RImatrix` to force the location of the markers. The parameter `quiet` can be unset to show what samples are corrected.

If only a subset of samples require correction, then they can be chosen by subsetting the object `sample`.

Neededless to say, this function expect that the CDF files exists and are in the TargetSearch format. If this is not the case, then use the function `fixRI()`, as this function deals only with RI files.

### Value

The retention index matrix. If `RImatrix` is not `NULL`, then the output is the same matrix.

### Note

It is required that all the sample names of `samples` are contained in the colnames of `RImatrix`, but the reverse is not necessary. The number of columns of the output matrix will match the number of samples. Extra columns in `RImatrix` will be ignored and not returned.

### Author(s)

Alvaro Cuadros-Inostroza

### See Also

`fixRI()`, `RIcorrect()`, `ImportSamples()`, `ImportFameSettings()`

### Examples

    require(TargetSearchData)
    # import refLibrary, rimLimits and sampleDescription.
    data(TSExample)
    CDFpath(sampleDescription) <-
        file.path(find.package("TargetSearchData"), "gc-ms-data")

    # convert a subset of files to netCDF4
    smp <- ncdf4Convert(sampleDescription[1:6], path=".")

    # make a copy of the RI markers object
    fames <- rimLimits

    # mess up the limits of marker 3 (real value is 369 seconds app.)
    rimLimits(fames)[3,] <- c(375, 400)

    # run RIcorrect (skip CDF-4 conversion)
    RImat <- RIcorrect(smp, fames, Window = 15, IntThreshold = 200)

    # fix the limits of marker 3
    rimLimits(fames)[3,] <- c(360, 380)

    # update RI files and CDF files
    RImat <- updateRI(smp, fames)

    # Pass a RI matrix for manual adjustment
    RImat[, 3] <- c(252, 311, 369)
    RImat <- updateRI(smp, fames, RImat)

    # To select specific samples, simply use sample subsetting
    # Note, RImat2 has only one column in this case.
    ( RImat2 <- updateRI(smp[3], fames, RImat) )

[Package TargetSearch version 1.50.1 Index]