Last data update: 2014.03.03
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Cran Task View
BiocViews
SMO (statistical methods ontology)
Results 1 - 10 of 57 found.[1]
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Images
Performs set union, intersection and (asymmetric!) difference on two vector-like objects.
● Data Source:
BioConductor
sort
(Package: BiocGenerics ) :
Sorting a vector-like object
● Data Source:
BioConductor
start
(Package: BiocGenerics ) :
Start, end, width generic getters and setters
● Data Source:
BioConductor
strand
(Package: BiocGenerics ) :
Accessing strand information
● Data Source:
BioConductor
subset
(Package: BiocGenerics ) :
Subsetting vector-like, matrix-like and data-frame-like objects
● Data Source:
BioConductor
table
(Package: BiocGenerics ) :
Cross tabulation and table creation
table uses the cross-classifying factors to build a contingency table of the counts at each combination of factor levels.
● Data Source:
BioConductor
tapply
(Package: BiocGenerics ) :
Apply a function over a ragged array
tapply applies a function to each cell of a ragged array, that is to each (non-empty) group of values given by a unique combination of the levels of certain factors.
● Data Source:
BioConductor
testPackage helps developers implement unit tests using the RUnit testing conventions.
● Data Source:
BioConductor
unique
(Package: BiocGenerics ) :
Extract unique elements
unique returns an object of the same class as x (typically a vector-like, data-frame-like, or array-like object) but with duplicate elements/rows removed.
● Data Source:
BioConductor
unlist
(Package: BiocGenerics ) :
Flatten list-like objects
x, unlist produces a vector-like object obtained by concatenating (conceptually thru c) all the top-level elements in x (each of them being expected to be a vector-like object, typically).
● Data Source:
BioConductor
providing 
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