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List of metacell tags

Source: R/DaparToolshed_Params_Addons.R, R/metacell.R, R/DaparToolshed_QFeatures_Addons.R
QFeatures-accessors.Rd

This function gives the list of metacell tags available.

  • onlyPresent: In this case, the function gives the tags found in a dataset. In addition, and w.r.t to the hierarchy of tags, if all leaves of a node are present, then the tag corresponding to this node is added.

These names are common to all assays contained in the object. This is why they are stored in the global metadata. This function is used whenever it i s necessary to (re)detect MEC and POV (new dataset or when post processing protein qMetacell after aggregation)

Usage

paramshistory(object, ...)

# S4 method for class 'QFeatures'
paramshistory(object, i, slotName = "paramshistory")

# S4 method for class 'SummarizedExperiment'
paramshistory(object, slotName = "paramshistory")

paramshistory(object, i, slotName = "paramshistory") <- value

GetMetacellTags(object, ...)

# S4 method for class 'QFeatures'
GetMetacellTags(object, i, ...)

# S4 method for class 'SummarizedExperiment'
GetMetacellTags(object, ...)

# S4 method for class 'data.frame'
GetMetacellTags(object, ...)

qMetacell(object, ...)

# S4 method for class 'QFeatures'
qMetacell(object, i)

# S4 method for class 'SummarizedExperiment'
qMetacell(object)

qMetacell(object, i, slotName = "qMetacell") <- value

GetUniqueTags(object, ...)

# S4 method for class 'QFeatures'
GetUniqueTags(object, i)

# S4 method for class 'SummarizedExperiment'
GetUniqueTags(object)

.GetMetadataSlot(object, slotName = NULL)

.GetRowdataSlot(object, slotName = NULL)

ConnectedComp(object, ...)

# S4 method for class 'QFeatures'
ConnectedComp(object, i, slotName = "ConnectedComp")

# S4 method for class 'SummarizedExperiment'
ConnectedComp(object, slotName = "ConnectedComp")

ConnectedComp(object, i, slotName = "ConnectedComp") <- value

typeDataset(object, ...)

# S4 method for class 'QFeatures'
typeDataset(object, i, slotName = "typeDataset")

# S4 method for class 'SummarizedExperiment'
typeDataset(object, slotName = "typeDataset")

typeDataset(object, i, slotName = "typeDataset") <- value

idcol(object, ...)

# S4 method for class 'QFeatures'
idcol(object, i, slotName = "idcol")

# S4 method for class 'SummarizedExperiment'
idcol(object, slotName = "idcol")

idcol(object, i, slotName = "idcol") <- value

parentProtId(object, ...)

# S4 method for class 'QFeatures'
parentProtId(object, i, slotName = "parentProtId")

# S4 method for class 'SummarizedExperiment'
parentProtId(object, slotName = "parentProtId")

parentProtId(object, i, slotName = "parentProtId") <- value

filename(object, ...)

# S4 method for class 'QFeatures'
filename(object, slotName = "filename")

filename(object, slotName = "filename") <- value

analysis(object, ...)

# S4 method for class 'QFeatures'
analysis(object, i, slotName = "analysis")

# S4 method for class 'SummarizedExperiment'
analysis(object, slotName = "analysis")

analysis(object, i, slotName = "analysis") <- value

version(object, ...)

# S4 method for class 'QFeatures'
version(object, slotName = "version")

version(object, slotName = "version") <- value

design.qf(object, ...)

# S4 method for class 'QFeatures'
design.qf(object, slotName = "design")

design.qf(object, slotName = "design") <- value

mainAssay(object)

HypothesisTest(object, ...)

# S4 method for class 'QFeatures'
HypothesisTest(object, i, slotName = "HypothesisTest")

# S4 method for class 'SummarizedExperiment'
HypothesisTest(object, slotName = "HypothesisTest")

HypothesisTest(object, i) <- value

DifferentialAnalysis(object, ...)

# S4 method for class 'QFeatures'
DifferentialAnalysis(object, i, slotName = "DifferentialAnalysis")

# S4 method for class 'SummarizedExperiment'
DifferentialAnalysis(object, slotName = "DifferentialAnalysis")

DifferentialAnalysis(object, i) <- value

names_metacell(object, ...)

# S4 method for class 'QFeatures'
names_metacell(object, i, slotName = "names_metacell")

# S4 method for class 'SummarizedExperiment'
names_metacell(object, slotName = "names_metacell")

names_metacell(object, i, slotName = "names_metacell") <- value

Arguments

object

xxx

...

xxx

i

The index or name of the assays to extract the quantitative metadata from. All must have a rowdata variable named as slotName

slotName

xxx

value

xxx

Value

A vector of tags..

NA

NA

NA

NA

NA

NA

NA

Details

Additional slots for rowdata of a SummarizedExperiment object:

  • qMetacell: xxx

Additional slots for Metadata for a QFeatures object:

  • xxx: xxxx

Additional slots for Metadata for a SummarizedExperiment object:

  • qMetacell: xxxx

  • parentProtId: xxx

  • idcol: xxxx

  • typeDataset: xxx

Quantitative metadata

Default slotName is "qMetacell". The value is an adjacency matrix with row and column names. The matrix will be coerced to compressed, column-oriented sparse matrix (class dgCMatrix) as defined in the Matrix package, as generaled by the sparseMatrix() constructor.

Author

Samuel Wieczorek

Examples

data(Exp1_R25_pept, package="DaparToolshedData")
obj <- Exp1_R25_pept
GetMetacellTags(obj, 1, level="peptide")
#> [1] "Quantified"          "Quant. by direct id" "Quant. by recovery" 
#> [4] "Missing"             "Missing POV"         "Missing MEC"        
#> [7] "Imputed"             "Imputed POV"         "Imputed MEC"        
GetMetacellTags(obj, 1, level="peptide", onlyPresent=TRUE)
#> [1] "Quant. by direct id" "Quant. by recovery"  "Missing POV"        
#> [4] "Missing MEC"         "Quantified"          "Missing"            

data(ft, package='DaparToolshed')
design.qf(ft)