PSM: A class for peptide-spectrum matches

In rformassspectrometry/PSM: Handling and Managing Peptide Spectrum Matches

A class for peptide-spectrum matches

Description

The PSM class is a simple class to store and manipulate peptide-spectrum matches. The class encapsulates PSM data as a DataFrame (or more specifically a DFrame) with additional lightweight metadata annotation.

There are two types of PSM objects:

• Objects with duplicated spectrum identifiers. This holds for multiple matches to the same spectrum, be it different peptide sequences or the same sequence with or without a post-translational modification. Such objects are typically created with the PSM() constructor starting from mzIdentML files.

• Reduced objects where the spectrum identifiers (or any equivalent column) are unique keys within the PSM table. Matches to the same scan/spectrum are merged into a single PSM data row. Reduced PSM object are created with the reducePSMs() function. See examples below.

Objects can be checked for their reduced state with the reduced() function which returns TRUE for reduced instances, FALSE when the spectrum identifiers are duplicated, or NA when unknown. The flag can also be set explicitly with the ⁠reduced()<-⁠ setter.

Usage

PSM(
  x,
  spectrum = NA,
  peptide = NA,
  protein = NA,
  decoy = NA,
  rank = NA,
  score = NA,
  fdr = NA,
  parser = c("mzR", "mzID"),
  BPPARAM = SerialParam()
)

reduced(object, spectrum = psmVariables(object)["spectrum"])

reduced(object) <- value

psmVariables(object, which = "all")

reducePSMs(object, k = object[[psmVariables(object)["spectrum"]]])

## S4 method for signature 'PSM'
adjacencyMatrix(object)

Arguments

x	character() of mzid file names, an instance of class PSM, or a data.frame.
spectrum	character(1) variable name that defines a spectrum in the PSM data. Default are "spectrumID" (mzR parser) or "spectrumid" (mzID parser). It is also used to calculate the reduced state.
peptide	character(1) variable name that defines a peptide in the PSM data. Detaults are "sequence" (mzR parser) or "pepSeq" (mzID parser).
protein	character(1) variable name that defines a protein in the PSM data. Detaults are "DatabaseAccess" (mzR parser) or "accession" (mzID parser).
decoy	character(1) variable name that defines a decoy hit in the PSM data. Detaults are "isDecoy" (mzR parser) or "isdecoy" (mzID parser).
rank	character(1) variable name that defines the rank of the peptide spectrum match in the PSM data. Default is "rank".
score	character(1) variable name that defines the PSM score. This value isn't set by default as it depends on the search engine and application. Default is NA.
fdr	character(1) variable name that defines that defines the spectrum FDR (or any similar/relevant metric that can be used for filtering). This value isn't set by default as it depends on the search engine and application. Default is NA.
parser	character(1) defining the parser to be used to read the mzIdentML files. One of "mzR" (default) or "mzID".
BPPARAM	an object inheriting from BiocParallelParam to control parallel processing. The default value is SerialParam() to read files in series.
object	An instance of class PSM.
value	new value to be passed to setter.
which	character() with the PSM variable name to retrieve. If "all" (default), all named variables are returned. See PSM() for valid PSM variables.
k	A vector or factor of length equal to nrow(x) that defines the primary key used to reduce x. This typically corresponds to the spectrum identifier. The defauls is to use the spectrum PSM variable.

Value

PSM() returns a PSM object.

reducePSMs() returns a reduced version of the x input.

Creating and using PSM objects

• The PSM() constructor uses parsers provided by the mzR or mzID packages to read the mzIdentML data. The vignette describes some apparent differences in their outputs. The constructor input is a character of one more multiple file names.

• PSM objects can also be created from a data.frame object (or any variable that can be coerced into a DataFrame.

• Finally, PSM() can also take a PSM object as input, which leaves the PSM data as is and is used to set/update the PSM variables.

• The constructor can also initialise variables (called PSM variables) needed for downstream processing, notably filtering (see filterPSMs()) and to generate a peptide-by-protein adjacency matrix (see makeAdjacencyMatrix()). These variables can be extracted with the psmVariables() function. They represent the columns in the PSM table that identify spectra, peptides, proteins, decoy peptides hit ranks and, optionally, a PSM score. The value of these variables will depend on the backend used to create the object, or left blank (i.e. encoded as NA) when building an object by hand from a data.frame. In such situation, they need to be passed explicitly by the user as arguments to PSM().

• The adjacencyMatrix() accessor can be used to retrieve the binary sparse peptide-by-protein adjacency matrix from the PSM object. It also relies on PSM variables which thus need to be set beforehand. For more flexibility in the generation of the adjacency matrix (for non-binary matrices), use makeAdjacencyMatrix().

Examples

## ---------------------------------
## Example with a single mzid file
## ---------------------------------

f <- msdata::ident(full.names = TRUE, pattern = "TMT")
basename(f)

## mzR parser (default)
psm <- PSM(f)
psm

## PSM variables
psmVariables(psm)

## mzID parser
psm_mzid <- PSM(f, parser = "mzID")
psm_mzid

## different PSM variables
psmVariables(psm_mzid)

## Reducing the PSM data
(i <- which(duplicated(psm$spectrumID))[1:2])
(i <- which(psm$spectrumID %in% psm$spectrumID[i]))
psm2 <- psm[i, ]
reduced(psm2)

## Peptide sequence CIDRARHVEVQIFGDGKGRVVALGERDCSLQRR with
## Carbamidomethyl modifications at positions 1 and 28.
DataFrame(psm2[, c("sequence", "spectrumID", "modName", "modLocation")])
reduced(psm2) <- FALSE
reduced(psm2)

## uses by default the spectrum PSM variable, as defined during
## the construction - see psmVariables()
rpsm2 <- reducePSMs(psm2)
rpsm2
DataFrame(rpsm2[, c("sequence", "spectrumID", "modName", "modLocation")])
reduced(rpsm2)

## ---------------------------------
## Multiple mzid files
## ---------------------------------

library(rpx)
PXD022816 <- PXDataset("PXD022816")
PXD022816

(mzids <- pxget(PXD022816, grep("mzID", pxfiles(PXD022816))[1:2]))
psm <- PSM(mzids)
psm
psmVariables(psm)

## Here, spectrum identifiers are repeated accross files
psm[grep("scan=20000", psm$spectrumID), "spectrumFile"]

## Let's create a new primary identifier composed of the scan
## number and the file name
psm$pkey <- paste(sub("^.+Task\\\\", "", psm$spectrumFile),
                  sub("^.+scan=", "", psm$spectrumID),
                  sep = "::")
head(psm$pkey)

## the PSM is not reduced
reduced(psm, "pkey")
DataFrame(psm[6:7, ])

## same sequence, same spectrumID, same file
psm$sequence[6:7]
psm$pkey[6:7]

## different modification locations
psm$modLocation[6:7]

## here, we need to *explicitly* set pkey to reduce
rpsm <- reducePSMs(psm, psm$pkey)
rpsm
reduced(rpsm, "pkey")

## the two rows are now merged into a single one; the distinct
## modification locations are preserved.
(i <- which(rpsm$pkey == "QEP2LC6_HeLa_50ng_251120_01-calib.mzML::12894"))
DataFrame(rpsm[i, c("sequence", "pkey", "modName", "modLocation")])

## ---------------------------------
## PSM from a data.frame
## ---------------------------------

psmdf <- data.frame(spectrum = paste0("sp", 1:10),
                    sequence = replicate(10,
                                         paste(sample(getAminoAcids()[-1, "AA"], 10),
                                               collapse = "")),
                    protein = sample(paste0("Prot", LETTERS[1:7]), 10,
                                     replace = TRUE),
                    decoy = rep(FALSE, 10),
                    rank = rep(1, 10),
                    score = runif(10))
psmdf

psm <- PSM(psmdf)
psm
psmVariables(psm)

## no PSM variables set
try(adjacencyMatrix(psm))

## set PSM variables
psm <- PSM(psm, spectrum = "spectrum", peptide = "sequence",
           protein = "protein", decoy = "decoy", rank = "rank")
psm
psmVariables(psm)

adjacencyMatrix(psm)

rformassspectrometry/PSM documentation built on March 20, 2024, 9:16 a.m.