as.DataFrame: New generic defined to allow for easy
DataFramecoercion. Avoid defining the
coerce, as this will result in unexpected behavior for
DataFramecoercion. The standard
DataFramegenerator currently doesn't handle lists very well, unlike
as_tibble, so we defined an alternative approach via
as.DataFramehere in the package, to allow for easy list column generation.
mutateAll: Further improvements for list column handling and
coerceS4ToListin favor of
coerceToList. The old function spelling is soft deprecated and will be deprecated/made defunct in a future release.
mutateAll: Fix for improved handling of nested list columns. Requires that
as_tibbleis called internally before handing off to
metadata2<-: Assign and extract metadata from either S3 or S4 objects in a consistent manner. Requires the
whichargument, similar to the approach employed in base
attr. Working example shows clearly how this differs internally between S3 (
attr) and S4 objects extending
SummarizedExperiment) defunct in favor of
Updated NAMESPACE to work with migration of some low-level functions into new acidbase package.
matchRowNameColumn: Converted function to S4 method that works on
DataFrameclass objects. Added
choicesargument, which lets the user change the column matching values, if desired.
as.SummarizedExperiment: Redefined generic to include
...in case we need to add arguments in a future update.
coerceS4ToList: Converted to S4 method approach. Now works specifically on objects that extend
Annotatedclass, such as
flatFilesdefunct, in favor of
mutateAll: Bug fix that improves column creation with
select*verbs to use simple base R code internally, and now methods are only defined for
DataFrameclass. This way we don't run into any masking issues with dplyr, and we don't need to list it as a suggested package.
select_all. These verbs don't really make sense in the context of Bioconductor-related internal code.
Improved S4 method support for dplyr verbs working on
anti_join. These methods use
mergeinternally but ensure that rows are not unexpectedly reordered.
select_if. These variants keep track of row names. Internally, these functions coerce to
tbl_dfand then call the dplyr function. Return is coerced back to
DataFrame, with row names preserved.
relevel:Made S3 methods for
releveldefunct of favor of recommend S4 method usage of
droplevelsinstead. S4 method support for
droplevelsis already provided in S4Vectors (i.e.
DataFrame). Here we are improving
droplevelsfunctionality by adding additional method support for
GRanges) as well as
SummarizedExperiment, which enables automatic leveling of factors in
Rlecolumns, which will error otherwise when attempting to coerce from
left_jointo keep row names, which correspond to the
relevel: Added S3 method support for
GRangesobjects containing factor columns.
encodefrom brio here.
as.DataFrameS3 method in favor of simply using S4
as.SummarizedExperimentS3 methods to support
rdnametag instead of
tbl_dfwhen coercing to
tbl_df, which works like the default
matchRowNameColumnfunction, which can detect row name columns inside data frame classes that don't support row names assignment, currently
GRangesclass from GenomicRanges package.
DataFrameS4 method support for
GRangesclass objects are initially supported.
tbl_dfcoercion that doesn't make names syntactically valid during internal
encode()S4 methods from basejump.
atomize()compatibility with Bioconductor 3.7 release. Now DataFrame objects containing Rle columns will get decoded consistently without applying stringsAsFactors in an unexpected fashion. This works correctly in Bioconductor 3.8 simply using
as.data.frame()internally, but has unwanted coercion of
factorcolumns for Rle-encoded data when using the Bioconductor 3.7 release.
as.DataFrame()S3 coercion methods, for consistency.
Initial release. Migrated useful S4 coercion methods from basejump for easier unit testing in a separate package.
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