Chromatographic peaks data

As explained in the Chromatograms class documentation, the Chromatograms object is a container for chromatographic data that includes chromatographic peaks data (retention time and related intensity values, also referred to as peaks data variables in the context of Chromatograms) and metadata of individual chromatograms (so called chromatograms variables).

The peaks data variables information can be accessed using the peaksData() function. It is also possible to access specific peaks variables using $.

The peaks data can be accessed, replaced but also filtered/subsetted. Refer to the sections below for more details.

# S4 method for class 'Chromatograms'
imputePeaksData(
  object,
  method = c("linear", "spline", "gaussian", "loess"),
  span = 0.3,
  sd = 1,
  window = 2,
  ...
)

# S4 method for class 'Chromatograms'
filterPeaksData(
  object,
  variables = character(),
  ranges = numeric(),
  match = c("any", "all"),
  keep = TRUE
)

# S4 method for class 'Chromatograms'
intensity(object, ...)

# S4 method for class 'Chromatograms'
intensity(object) <- value

# S4 method for class 'Chromatograms'
peaksData(
  object,
  columns = peaksVariables(object),
  f = processingChunkFactor(object),
  BPPARAM = bpparam(),
  drop = FALSE,
  ...
)

# S4 method for class 'Chromatograms'
peaksData(object) <- value

# S4 method for class 'Chromatograms'
peaksVariables(object, ...)

# S4 method for class 'Chromatograms'
rtime(object, ...)

# S4 method for class 'Chromatograms'
rtime(object) <- value

# S4 method for class 'Chromatograms'
lengths(x)

Arguments

object: A Chromatograms object.
method: For imputePeaksData(): character(1): Imputation method ("linear", "spline", "gaussian", "loess")
span: For imputePeaksData: numeric(1), for the loess method: Smoothing parameter (only used if method == "loess")
sd: For imputePeaksData: numeric(1), for the gaussian method: Standard deviation for Gaussian kernel (only used if method == "gaussian")
window: For imputePeaksData: integer, for the gaussian method: Half-width of Gaussian kernel window (e.g., 2 gives window size 5)
...: Additional arguments passed to the method.
variables: For filterPeaksData(): character vector with the names of the peaks data variables to filter for. The list of available peaks data variables can be obtained with peaksVariables().
ranges: For filterPeaksData() : a numeric vector of paired values (upper and lower boundary) that define the ranges to filter the object. These paired values need to be in the same order as the variables parameter (see below).
match: For filterPeaksData() : character(1) defining whether the condition has to match for all provided ranges (match = "all"; the default), or for any of them (match = "any").
keep: For filterPeaksData(): logical(1) defining whether to keep (keep = TRUE) or remove (keep = FALSE) the chromatographic peaks data that match the condition.
value: For rtime() and intensity(): numeric vector with the values to replace the current values. The length of the vector must match the number of peaks data pairs in the Chromatograms object.
columns: For peaksData(): optional character with column names (peaks variables) that should be included in the returned list of data.frame. By default, all columns are returned. Available variables can be found by calling peaksVariables() on the object.
f: factor defining the grouping to split the Chromatograms object.
BPPARAM: Parallel setup configuration. See BiocParallel::bpparam() for more information.
drop: logical(1) For peaksData(), default to FALSE. If TRUE, and one column is called by the user, the method returns a list of vector of the single column requested.
x: For lengths(): A Chromatograms object.

Value

Refer to the individual function description for information on the return value.

Filter Peaks Variables

Functions that filter a Chromatograms's peaks data (i.e., peaksData). These functions remove peaks data that do not meet the specified conditions. If a chromatogram in a Chromatograms object is filtered, only the corresponding peaks variable pairs (i.e., rows) in the peaksData are removed, while the chromatogram itself remains in the object.

The available functions to filter chromatographic peaks data include:

filterPeaksData(): Filters numerical peaks data variables based on the specified numerical ranges parameter. This method returns the same input Chromatograms object, but the filtering step is added to the processing queue. The filtered data will be reflected when the user accesses peaksData. This function does not reduce the number of chromatograms in the object, but it removes the specified peaks data (e.g., "rtime" and "intensity" pairs) from the peaksData.

In the case of a read-only backend, (such as the ChromBackendMzR), the replacement of the peaks data is not possible. The peaks data can be filtered, but the filtered data will not be saved in the backend. This means the original mzml files will not be affected by computations performed on the Chromatograms.

Impute Peaks Variables

imputePeaksData will impute missing values in a Chromatograms's peaks data (i.e., peaksData). This functions replace missing peaks data values with specified imputation methods using various methods such as linear interpolation, spline interpolation, Gaussian kernel smoothing, or LOESS smoothing. This method modifies the peaks data in place and returns the same Chromatograms object with imputed values.

Author

Philippine Louail

Examples


# Create a Chromatograms object
cdata <- data.frame(
    msLevel = c(1L, 1L, 1L),
    mz = c(112.2, 123.3, 134.4),
    dataOrigin = c("mem1", "mem2", "mem3")
)

pdata <- list(
    data.frame(
        rtime = c(12.4, 12.8, 13.2, 14.6),
        intensity = c(123.3, 153.6, 2354.3, 243.4)
    ),
    data.frame(
        rtime = c(45.1, 46.2),
        intensity = c(100, 80.1)
    ),
    data.frame(
        rtime = c(12.4, 12.8, 13.2, 14.6),
        intensity = c(123.3, 153.6, 2354.3, 243.4)
    )
)

be <- backendInitialize(new("ChromBackendMemory"),
    chromData = cdata,
    peaksData = pdata
)

chr <- Chromatograms(be)

# Access peaks data
peaksData(chr)
#> [[1]]
#>   rtime intensity
#> 1  12.4     123.3
#> 2  12.8     153.6
#> 3  13.2    2354.3
#> 4  14.6     243.4
#> 
#> [[2]]
#>   rtime intensity
#> 1  45.1     100.0
#> 2  46.2      80.1
#> 
#> [[3]]
#>   rtime intensity
#> 1  12.4     123.3
#> 2  12.8     153.6
#> 3  13.2    2354.3
#> 4  14.6     243.4
#> 

# Access specific peaks data variables
peaksData(chr, columns = "rtime")
#> [[1]]
#>   rtime
#> 1  12.4
#> 2  12.8
#> 3  13.2
#> 4  14.6
#> 
#> [[2]]
#>   rtime
#> 1  45.1
#> 2  46.2
#> 
#> [[3]]
#>   rtime
#> 1  12.4
#> 2  12.8
#> 3  13.2
#> 4  14.6
#> 
rtime(chr)
#> [[1]]
#> [1] 12.4 12.8 13.2 14.6
#> 
#> [[2]]
#> [1] 45.1 46.2
#> 
#> [[3]]
#> [1] 12.4 12.8 13.2 14.6
#> 

# Replace peaks data
rtime(chr)[[1]] <- c(1, 2, 3, 4)

# Filter peaks data
filterPeaksData(chr, variables = "rtime", ranges = c(12.5, 13.5))
#> Chromatographic data (Chromatograms) with 3 chromatograms in a ChromBackendMemory backend:
#>   chromIndex msLevel    mz
#> 1         NA       1 112.2
#> 2         NA       1 123.3
#> 3         NA       1 134.4
#> ... 3 more  chromatogram variables/columns
#> ... 2 peaksData variables
#> Lazy evaluation queue: 1 processing step(s)
#> Processing:
#>  Filter: remove peaks based on the variables: rtimethe ranges: 12.5, 13.5and the match condition: any [Wed Oct 22 08:40:23 2025]
#>  Filter: remove peaks based on the variables: rtimethe ranges: 12.5, 13.5and the match condition: all [Wed Oct 22 08:40:23 2025]