addAssay | Quantitative MS QFeatures |
addAssayLink | Links between Assays |
addAssayLinkOneToOne | Links between Assays |
aggcounts | Aggregate an assay's quantitative features |
aggcounts,SummarizedExperiment | Aggregate an assay's quantitative features |
aggcounts-method | Aggregate an assay's quantitative features |
aggregateFeatures | Aggregate an assay's quantitative features |
aggregateFeatures-method | Aggregate an assay's quantitative features |
AllGenerics | Placeholder for generics functions documentation |
AssayLink | Links between Assays |
assayLink | Links between Assays |
AssayLink-class | Links between Assays |
AssayLinks | Links between Assays |
assayLinks | Links between Assays |
AssayLinks-class | Links between Assays |
CharacterVariableFilter | Filter features based on their rowData |
CharacterVariableFilter-class | Filter features based on their rowData |
class:AssayLink | Links between Assays |
class:AssayLinks | Links between Assays |
class:QFeatures | Quantitative MS QFeatures |
countUniqueFeatures | Count Unique Features This function counts the number of unique features per sample. A grouping structure can be provided to count higher level features from assays, for example counting the number of unique proteins from PSM data. |
dims-method | Quantitative MS QFeatures |
display | Interactive MultiAssayExperiment Explorer |
expandDataFrame | Reduces and expands a 'DataFrame' |
feat1 | Feature example data |
feat2 | Feature example data |
feat3 | Example 'QFeatures' object after processing |
filterFeatures | Filter features based on their rowData |
filterFeatures-method | Filter features based on their rowData |
filterNA | Managing missing data |
filterNA-method | Managing missing data |
ft_na | Feature example data |
hlpsms | hyperLOPIT PSM-level expression data |
impute | Quantitative proteomics data imputation |
impute-method | Quantitative proteomics data imputation |
infIsNA | Managing missing data |
infIsNA-method | Managing missing data |
joinAssays | Join assays in a QFeatures object |
logTransform | QFeatures processing |
logTransform-method | QFeatures processing |
longFormat | Quantitative MS QFeatures |
missing-data | Managing missing data |
names<--method | Quantitative MS QFeatures |
nNA | Managing missing data |
nNA-method | Managing missing data |
normalize | QFeatures processing |
normalize-method | QFeatures processing |
normalizeMethods | QFeatures processing |
NumericVariableFilter | Filter features based on their rowData |
NumericVariableFilter-class | Filter features based on their rowData |
plot.QFeatures | Quantitative MS QFeatures |
QFeatures | Quantitative MS QFeatures |
QFeatures-class | Quantitative MS QFeatures |
QFeatures-filtering | Filter features based on their rowData |
QFeatures-processing | QFeatures processing |
rbindRowData | Quantitative MS QFeatures |
readQFeatures | QFeatures from tabular data |
readSummarizedExperiment | QFeatures from tabular data |
reduceDataFrame | Reduces and expands a 'DataFrame' |
rowData-method | Quantitative MS QFeatures |
rowData<--method | Quantitative MS QFeatures |
rowDataNames | Quantitative MS QFeatures |
scaleTransform | QFeatures processing |
scaleTransform-method | QFeatures processing |
selectRowData | Quantitative MS QFeatures |
se_na2 | Feature example data |
show-method | Links between Assays |
show-method | Quantitative MS QFeatures |
subsetByFeature | Subset by feature name |
subsetByFeature-method | Subset by feature name |
sweep | QFeatures processing |
sweep-method | QFeatures processing |
VariableFilter | Filter features based on their rowData |
zeroIsNA | Managing missing data |
zeroIsNA-method | Managing missing data |
[-method | Links between Assays |
[-method | Quantitative MS QFeatures |