[Bioc-devel] February NEWS
jmacdon at med.umich.edu
Tue Mar 6 19:05:25 CET 2007
Modified to use ExpressionSet instead of exprSet
Now readCelunits() can handle unit groups for which there are
no probes, e.g., when stratifying on PM in a unit containing
Added writeCdfHeader(), writeCdfQcUnits() and writeCdfUnits(),
all of which are used by writeCdf(). They make it possible to
write a CDF in chunks using bounded memory.
Updated AmiGO URL
Changed structure of class BeadLevelList to handle uneven
numbers of beads per array, and two-colour data. Updated
plotting and summarising functions.
Added boxplotBeads(), arrayNames(), numBeads(), getArrayData()
to work on this class.
New function readIllumina() to read in raw bead-level data.
Added experimental unsaveSetSlot for internal use. This
functiona llows one to set the slots of an S4 object in place
without any copying. This should allow for considerable speed
up when used appropriately.
Added ExpressionSet introduction vignette. Moved old Biobase
vignette to new 'legacy' directory.
Disallowed drop = TRUE for AnnotatedDataFrame.
Added port attribute to listMarts() and useMart() so users can
choose which port to connect to when using biomaRt in MySQL
mode. Changed default Ensembl host to martdb.ensembl.org using
Added retrieval of more sequence types with the getSequence
function (such as retrieval of exons and upstream
sequences). One can now also use filters for the type argument
of getSequence(). Removed getXref() and getPossibleXrefs() as
these have been deprecated by getBM() and getLDS(). Removed
the martTable object as ouput from all functions is now a
Added the Boyer-Moore algorithm. The defaults for
matchPattern() are now fixed = TRUE and the 'auto' feature ow
picks up the 'boyer-moore' algorithm whenever possible
(generally faster than the shift-or algorithm.
Added the 'naive' algorithm for QC and as a benchmark.
Added the 'gregexpr' algorithm when pattern and subject are
both standard character strings. The 'gregexpr' algorithm is a
modified version of the standard R gregexpr(), to be used as a
'pure R' benchmark.
Changed modified gregexpr() to gregexpr2() and added
gregexpr(). Both undocumented.
Terminology changes. The 'Strong Good Suffix shifts' are now
called the 'Very Strong Good Suffix shifts' to indicate the
difference (>=) from the usual Strong Good Suffix shifts. The
'Good Right Shifts' are now called the 'Matching Window
Added ability to run huperGTest() using chromosome bands as
categories. This adds the ChrMapHyperGParams and
ChrMapHyperGResult classes and code.
Improved handling of MAP annotation ranges. Instead of
dropping annotations given as a range of chromosome bands, we
now take the longest common prefix. There are still some
inconsistencies in the annotation which we don't handle
Removed unused geneCounts and universeCounts from HyperGResult
object. Methods with the same names are available for
accessing these data from the result object. Thanks to N. Le
Meur for the bug report.
Added two new summaries that can be used in
summarizeReplicates(), 'closestToZero' and 'farthestFromZero'.
Bug fix: memory of the size of unpacked image was lost on
every operation using ImageMagick built in filters. Other
filters were not affected, nor were IO, conversions or object
detection. Everyone using the package should update to this
Added propagate(), a Voronoi-based segmentation on image
manifolds with modified metric.
gene.details(), transcript.details() and exon.details() now
take a vector as input and return a data.frame (as
advertised). pc() now uses rowttests(), and does not need
members to be specified if factor has exactly two levels.
Added gene.strip() and probesets.in.eset().
Improved scale on plot.gene().
Changed optical background correction to tolerate no MM
Added edgeMatrix method for graphAM.
Fixed graphNEL ==> graphAM by removing rownames from
adjMat. The optimized version was resulting in a graphAM
instance with rownames and colnames on the adjMat. The graphAM
initialize method removes rownames so the node names are
Fixed bug in ftM2graphNEL() that was due to partial string
matching in accessing list elements by name.
normalizeRobustSpline() now works with only one print-tip
group. New function mergeScahsRG().
Deprecated getColClasses() and namesInFun() and replaced with
read.columns(), a more general function that is similar to
read.delim() but reads specified columns only. Argument '...'
added to all as.matrix methods for compatibility with R-2.5.0.
Bugfix: lm.series() and gls.series() were returning errors
when the design matrix was not of full rank and the columns
Bugfix: write.fit() was using ambiguous column names for the
coef, t-statistic and p-value when the MArrayLM object had
only one column and these components were matrices with one
Default for digits changed in write.fit().
Updated lumiR() to allow directly adding nuID when reading the
data, and updated addNuId2lumi to add the tracking history.
Updated the combine method of LumiBatch class, addNuId2lumi(),
lumiR() for better adaptiveness.
Added support for non-linear PCA and made corresponding
additions to the documentation. Also added simulated example
data for use with nlpca(). Changed Q2 cross-validation to
guarantee that no full column or row is ever deleted. The
screeplot() function was removed and replaced with plotR2().
K-estimate now supports NMRMSEP and Q2 as error measure.
Upgraded plotPcs() so it works with Sweave() and gives
prettier output by basing it on pairs() instead of slplot().
Added a new method kEstimateFast(). This also estimates the
best number of components/similar genes for missing value
estimation. In contrast to kEstimate() no crossvalidation is
performed. This is a more rough estimate than provided by
Improved speed of kEstimate(). Now possible to get the
estimation error for each individual incomplete variable. This
allows one to easily see for which variables missing value
imputation makes sense.
Removed ellipse dependency.
Added vignette on missing value estimation.
New method to comvert pcaRes to exprSet. pca() no longer
returns an exprSet if an exprSet was used as input, use
Added C. elegans and yeast2 to data for QC stats. Updated to
work with ExpressionSet class.
Improvements on the predict method for vsn(). justvsn() is now
Updated lymphoma dataset to ExpressionSet.
Made vsn2() compatible with limma package.
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