as.DataFrame: New generic defined to allow for easy list to DataFrame
coercion. Avoid defining the list method for as/coerce, as this will
result in unexpected behavior for data.frame to DataFrame coercion.
The standard DataFrame generator currently doesn't handle lists very well,
unlike as_tibble, so we defined an alternative approach via as.DataFrame
here in the package, to allow for easy list column generation.mutateAll: Further improvements for list column handling and DataFrame
return consistency.coerceS4ToList in 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_tibble is called internally before handing off to DataFrame.metadata2 and metadata2<-: Assign and extract metadata from either S3 or
S4 objects in a consistent manner. Requires the which argument, similar to
the approach employed in base attr. Working example shows clearly how this
differs internally between S3 (attr) and S4 objects extending Annotated
class (metadata).relevel methods (DataFrame, Ranges,
SummarizedExperiment) defunct in favor of droplevels usage.Updated NAMESPACE to work with migration of some low-level functions into new acidbase package.
matchRowNameColumn: Converted function to S4 method that works on
data.frame and DataFrame class objects. Added choices argument, 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 Annotated class, such as SummarizedExperiment.flatFiles defunct, in favor of coerceS4ToList usage.mutateAll: Bug fix that improves column creation with DataFrame.innerJoin, leftJoin,
rightJoin, fullJoin, semiJoin, antiJoin; mutateAll, mutateAt,
mutateIf; selectIf.mutate* and select* verbs to use simple base R code internally,
and now methods are only defined for DataFrame class. 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 and 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 DataFrame class.
inner_join, left_join (already defined), right_join, full_join,
semi_join, and anti_join. These methods use merge internally but
ensure that rows are not unexpectedly reordered.mutate and select: mutate_all, mutate_at,
mutate_if, transmute_at, transmute_if; select_all, select_at,
select_if. These variants keep track of row names. Internally, these
functions coerce to tbl_df and then call the dplyr function. Return is
coerced back to DataFrame, with row names preserved.relevel: Made S3 methods for relevel defunct of favor of recommend S4
method usage of droplevels instead. S4 method support for droplevels is
already provided in S4Vectors (i.e. List, DataFrame). Here we are
improving droplevels functionality by adding additional method support
for Ranges (to support IRanges, GRanges) as well as
SummarizedExperiment, which enables automatic leveling of factors in
colData or rowData.Rle columns, which will error otherwise when
attempting to coerce from DataFrame to data.frame.left_join generic. Improved DataFrame method for
left_join to keep row names, which correspond to the x object.relevel: Added S3 method support for DataFrame and GRanges objects
containing factor columns.atomize, decode, and encode from brio here.as.DataFrame S3 method in favor of simply using S4 as coercion.as.SummarizedExperiment S3 methods to support
SummarizedExperiment and RangedSummarizedExperiment specifically.rdname tag instead of method
(or legacy s3method).data.table and tbl_df when
coercing to DataFrame.IRanges to data.frame, data.table, and
tbl_df, which works like the default GRanges coercion methods.matchRowNameColumn function, which can detect row name columns
inside data frame classes that don't support row names assignment, currently
data.table and tbl_df.GRanges class from GenomicRanges package.DataFrame S4 method support for left_join.as_tibble
and as.data.table.data.table class. DataFrame and GRanges
class objects are initially supported.DataFrame to tbl_df coercion that doesn't make names syntactically
valid during internal as.data.frame() call.atomize(), factorize(),
encode(), decode().decode() and 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 character to factor columns for Rle-encoded data when using
the Bioconductor 3.7 release.atomize() and factorize() from basejump.tibble::as_tibble() gets reexported.as.DataFrame() S3 coercion methods, for consistency.as() coercion methods.Initial release. Migrated useful S4 coercion methods from basejump for easier unit testing in a separate package.
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