| Title: | PGCA: An Algorithm to Link Protein Groups Created from MS/MS Data |
|---|---|
| Description: | Protein Group Code Algorithm (PGCA) is a computationally inexpensive algorithm to merge protein summaries from multiple experimental quantitative proteomics data. The algorithm connects two or more groups with overlapping accession numbers. In some cases, pairwise groups are mutually exclusive but they may still be connected by another group (or set of groups) with overlapping accession numbers. Thus, groups created by PGCA from multiple experimental runs (i.e., global groups) are called "connected" groups. These identified global protein groups enable the analysis of quantitative data available for protein groups instead of unique protein identifiers. |
| Authors: | Gabriela Cohen-Freue <[email protected]> |
| Maintainer: | Gabriela Cohen-Freue <[email protected]> |
| License: | GPL (>= 2) |
| Version: | 1.29.0 |
| Built: | 2024-09-14 04:38:10 UTC |
| Source: | https://github.com/bioc/pgca |
Apply the dictionary to the data files and write the translated files to disk.
applyDict(..., dict, out.dir = NULL, out.suffix = "", out.prefix = "", col.mapping, out.pg.col = "PGC")applyDict(..., dict, out.dir = NULL, out.suffix = "", out.prefix = "", col.mapping, out.pg.col = "PGC")
... |
input (see details). |
dict |
the PGCA dictionary to use. |
out.dir |
the directory to save the translated files in (see details).
If |
out.suffix, out.prefix
|
suffix and prefix that will be added to the translated files. |
col.mapping |
the column mapping for the input files. Defaults to the same as used to build the dictionary. |
out.pg.col |
the name of the column to store the protein group. |
The dictionary is applied to the data specified argument.
If no input is provided, the dictionary is applied to the
files used to create the dictionary. The inputs can be
directory names, file names, or data.framess.
If the output directory out.dir is specified, the translated files
will be saved in this directory. Otherwise the files will be written to the
same directory as the input files. The function will not overwrite existing
files and will fail if the files already exist. Parameters out.suffix
and out.prefix can be used to ensure unique new file names.
In case the input is a list of data.frames and no output
directory is specified, the data.frames will be translated and
returned as a list. The function will also return the translated
data.frames as list if the out.dir=NULL.
Either a list of data.frames or nothing (see details).
pgcaDict to create the dictionary
# Build PGCA dictionary from all files in a directory dict <- pgcaDict( system.file("extdata", package="pgca"), col.mapping=c(gene.symbol="Gene_Symbol") ) # Translate all files in the directory and return as a list of data.frames trans <- applyDict(system.file("extdata", package="pgca"), dict=dict, out.dir=NULL) # Translate only some files in the directory and return as a list of # data.frames trans <- applyDict( system.file("extdata", "BET1947_v339.txt", package="pgca"), system.file("extdata", "BET2047_v339.txt", package="pgca"), dict=dict ) str(trans) # Translate all files in the directory and save to another directory out.dir <- tempdir() applyDict(system.file("extdata", package="pgca"), dict=dict, out.dir=out.dir)# Build PGCA dictionary from all files in a directory dict <- pgcaDict( system.file("extdata", package="pgca"), col.mapping=c(gene.symbol="Gene_Symbol") ) # Translate all files in the directory and return as a list of data.frames trans <- applyDict(system.file("extdata", package="pgca"), dict=dict, out.dir=NULL) # Translate only some files in the directory and return as a list of # data.frames trans <- applyDict( system.file("extdata", "BET1947_v339.txt", package="pgca"), system.file("extdata", "BET2047_v339.txt", package="pgca"), dict=dict ) str(trans) # Translate all files in the directory and save to another directory out.dir <- tempdir() applyDict(system.file("extdata", package="pgca"), dict=dict, out.dir=out.dir)
These are four iTRAQ runs used to process samples from heart transplant patients. The datasets belong to the Biomarkers in Transplantation (BiT) initiative and PROOF Centre of Excellence. In all four runs, the raw MS/MS data was processed using ProteinPilot(tm) software v3.0 with the integrated Paragon(tm) Search and ProGroup(tm) algorithms and searching against the International Protein Index (IPI HUMAN v3.39) database.
Each data.frame has columns
the local protein group identifier
the accession number of the protein
the gene symbol
the protein name
Takhar M, Sasaki M, Hollander Z, Kepplinger D, Smith D, McManus B, McMaster W, Ng R and Cohen Freue G (Under revision). "PGCA: An Algorithm to Link Protein Groups Created from MS/MS Data."
Build a dictionary for protein groups from MS/MS data. Details of the algorithm can be found in Takhar et al. (Under revision). "PGCA: An Algorithm to Link Protein Groups Created from MS/MS Data.".
pgcaDict(..., col.mapping, master.gene.identifier)pgcaDict(..., col.mapping, master.gene.identifier)
... |
arbitrary number of directory names, file names, or
|
col.mapping |
column mapping (see Details). |
master.gene.identifier |
if given, genes with this value in the
column |
If the group.identifier column is logical (i.e., TRUE or
FALSE) or master.gene.identifier is given,
the TRUE accessions are assumed to be a "master gene" and the
data set is assumed to be in the correct order. This means all
FALSE values following the master gene are assumed to belong to
the same group.
The col.mapping maps the column names in the data files to a specific
function. It nees to be a named character vector, whereas the name of each
item is the "function" of the given column name. The algorithm knows about
the following columns:
"group.identifier"Column containing the group identifier.
"accession.nr"Column containing the accession nr.
"protein.name"Column containing the protein name.
"gene.symbol"Column containing the gene symbol (if any, can be missing)
The default column mapping is c(group.identifier="N", accession.nr =
"Accession", protein.name="Protein_Name"). The supplied column mapping can
ignore those columns that are already correct in the default map.
For instance, if the accession nr. is stored in column AccessionNr
instead of Accession, but the remaining columns are the same as in the
default mapping, specifying col.mapping=c(accession.nr="AccessionNr")
is sufficient.
An object of type pgcaDict.
Takhar M, Sasaki M, Hollander Z, McManus B, McMaster W, Ng R and Cohen Freue G (Under revision). "PGCA: An Algorithm to Link Protein Groups Created from MS/MS Data." PLOS ONE.
applyDict to apply the dictionary to the data files
and saveDict to save the dictionary itself.
# Build the dictionary from all files in a directory # and specifying the column "Gene_Symbol" holds the `gene.symbol`. dict.dir <- pgcaDict( system.file("extdata", package="pgca"), col.mapping=c(gene.symbol="Gene_Symbol") ) # Build the dictionary from a list of files dict.files <- pgcaDict( system.file("extdata", "BET1947_v339.txt", package="pgca"), system.file("extdata", "BET2007_v339.txt", package="pgca"), system.file("extdata", "BET2047_v339.txt", package="pgca"), col.mapping=c(gene.symbol="Gene_Symbol") ) # Build the dictionary from already read-in data.frames dict.data <- pgcaDict(BET1947_v339, BET2047_v339, col.mapping=c(gene.symbol="Gene_Symbol"))# Build the dictionary from all files in a directory # and specifying the column "Gene_Symbol" holds the `gene.symbol`. dict.dir <- pgcaDict( system.file("extdata", package="pgca"), col.mapping=c(gene.symbol="Gene_Symbol") ) # Build the dictionary from a list of files dict.files <- pgcaDict( system.file("extdata", "BET1947_v339.txt", package="pgca"), system.file("extdata", "BET2007_v339.txt", package="pgca"), system.file("extdata", "BET2047_v339.txt", package="pgca"), col.mapping=c(gene.symbol="Gene_Symbol") ) # Build the dictionary from already read-in data.frames dict.data <- pgcaDict(BET1947_v339, BET2047_v339, col.mapping=c(gene.symbol="Gene_Symbol"))
Write the dictionary to a text file using the
write.table function. By default, a tab-separated file
is written, but this can be changed
by changing the arguments to write.table.
saveDict(dict, file = stop("`file` must be specified"), ...)saveDict(dict, file = stop("`file` must be specified"), ...)
dict |
a PGCA dictionary. |
file |
either a character string naming a file or a
|
... |
further arguments passed to |
This function returns NULL invisibly.
pgcaDict to create the dictionary, and
applyDict to apply the dictionary for translating
data files.
# Build accession dictionary from all files in a directory dict <- pgcaDict( system.file("extdata", package="pgca"), col.mapping=c(gene.symbol="Gene_Symbol") ) # Save dictionary to a temporary file dictOutFile <- tempfile() saveDict(dict, file=dictOutFile) # Change the separator string to a tab dictOutFile <- tempfile() saveDict(dict, file=dictOutFile, sep="\t")# Build accession dictionary from all files in a directory dict <- pgcaDict( system.file("extdata", package="pgca"), col.mapping=c(gene.symbol="Gene_Symbol") ) # Save dictionary to a temporary file dictOutFile <- tempfile() saveDict(dict, file=dictOutFile) # Change the separator string to a tab dictOutFile <- tempfile() saveDict(dict, file=dictOutFile, sep="\t")