Creates an object of class QFeatures
from text file.
Source: R/import_2_qfeatures.R
import-export-QFeatures.Rd
Creates an object of class QFeatures
from a
single tabulated-like file for quantitative and meta-data and a dataframe
for the samples description.
Usage
createQFeatures(
data = NULL,
file = "myDataset",
sample,
indQData,
keyId = "AutoID",
indexForMetacell = NULL,
logData = FALSE,
force.na = TRUE,
typeDataset,
parentProtId = NULL,
analysis = "foo",
description = NULL,
processes = NULL,
typePipeline = NULL,
software = NULL,
name = "original"
)
Arguments
- data
The name of a tab-separated file that contains the data.
- file
A
character(1)
. The name of a file xxx- sample
A dataframe describing the samples (in lines).
- indQData
A vector of string where each element is the name of a column in designTable that have to be integrated in the
rowData()
table of theQFeatures
object.- keyId
A
character(1)
ornumeric(1)
which is the indice of the column containing the ID of entities (peptides or proteins)- indexForMetacell
They must be in the same order as the samples in the experimental design
- logData
xxx
- force.na
A
boolean
that indicates if the '0' and 'NaN' values of quantitative values must be replaced by 'NA' (Default is FALSE)- typeDataset
A string that indicates whether the dataset is about
- parentProtId
A
character(1)
For peptide entities, a string which is the name of a column in rowData. It contains the id of parent proteins and is used to generate adjacency matrix and process to aggregation.- analysis
A
character(1)
which is the name of the MS study.- description
A text which describes the study.
- processes
A vector of A
character()
which contains the name of processes which has already been run on the data. Default is 'original'.- typePipeline
A
character(1)
The type of pipeline used with this dataset. The list of predefined pipelines in DaparToolshed can be obtained with the functionpipelines()
. Default value is NULL- software
A
character(1)
- name
A
character(1)
which is the name of the assay in the QFeatures object. Default is 'original'
Examples
data.file <- system.file("extdata", "Exp1_R25_pept.txt", package = "DaparToolshedData")
data <- read.table(data.file, header = TRUE, sep = "\t", as.is = TRUE, stringsAsFactors = FALSE)
qdata.indices <- 56:61
qdata.names <- colnames(data)[qdata.indices]
sample.file <- system.file("extdata", "samples_Exp1_R25.txt", package = "DaparToolshedData")
sample <- read.table(sample.file, header = TRUE, sep = " ", as.is = TRUE, stringsAsFactors = FALSE)
metacell.indices <- 43:48
metacell.names <- colnames(data)[metacell.indices]
ft <- createQFeatures(file = data.file,
data = data,
sample = sample,
indQData = 56:61,
keyId = "Sequence",
analysis = "test",
logData = TRUE,
indexForMetacell = as.numeric(43:48),
typeDataset = "peptide",
parentProtId = "Protein_group_IDs",
force.na = TRUE,
software = "maxquant"
)
#> Checking arguments.
#> Loading data as a 'SummarizedExperiment' object.
#> Formatting sample annotations (colData).
#> Formatting data as a 'QFeatures' object.
#> Setting assay rownames.
ft <- createQFeatures(file = data.file,
data = data,
sample = sample,
indQData = 56:61,
keyId = "Sequence",
analysis = "test",
logData = TRUE,
typeDataset = "peptide",
parentProtId = "Protein_group_IDs",
force.na = TRUE,
software = "maxquant"
)
#> Checking arguments.
#> Loading data as a 'SummarizedExperiment' object.
#> Formatting sample annotations (colData).
#> Formatting data as a 'QFeatures' object.
#> Setting assay rownames.
ft <- createQFeatures(file = data.file,
data = data,
sample = sample,
indQData = qdata.names,
keyId = "Sequence",
analysis = "test",
indexForMetacell = metacell.names,
typeDataset = "peptide",
parentProtId = "Protein_group_IDs",
force.na = TRUE,
software = "maxquant")
#> Checking arguments.
#> Loading data as a 'SummarizedExperiment' object.
#> Formatting sample annotations (colData).
#> Formatting data as a 'QFeatures' object.
#> Setting assay rownames.