Hi,
I'm glad to announce that aroma.affymetrix v0.9.6 is now available.
Please update with:
source("http://www.braju.com/R/hbLite.R";);
hbInstall("aroma.affymetrix");
The main update is that everything is now in place for CRMA v2, which
is a bounded-memory single-array pre-processing method for estimating
raw copy numbers from any of Affymetrix SNP and CN chip types. There
is also a generic bounded-memory single-array (alt. multi-array)
normalization method that can normalize signals for
nucleotide-position effects. Anything can be done with approx
500-1500MB of RAM. The updates of the latest version is below. As
with all releases, this version pass our redundancy tests ran on
various data sets and chip types.
I will try to put up a vignette for CRMA v2 rather soon. That will
also illustrate how to do nucleotide-position normalization in
general. Bear with me and stay tuned.
Enjoy!
Henrik with other developers.
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UPDATES to aroma.affymetrix:
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Version: 0.9.6 [2008-12-04]
o Now CbsModel and GlabModel display any optional/additional
arguments passed to the internal segmentation method in
the verbose output.
o Added argument 'model' for AllelicCrosstalkCalibration to quickly
specification of default parameter settings according to the CRMA and
CRMA v2 model.
o Added argument 'pairBy' for AllelicCrosstalkCalibration to specify
how the allele probe pairs are identified. Historically we inferred
this from the CDF, but it is safer and more generic to do this from
the probe sequences, which then requires an ACS annotation file.
o Now argument 'target' of FragmentLengthNormalization can also
be "zero", which then specifies a predefined constant target function.
o Added support for importing probe sequences from Affymetrix BPMAP files
via the importFromBpMap() for AromaCellSequenceFile.
o Adding classes and methods in preparation for supporting analysis
of tiling arrays.
o Now fitCnProbes() of UnitModel only fits non-fitted CN units.
o SPEED UP: extractMatrix() of AffymetrixCel{File|Set} is now faster
when argument 'cells' is specified.
o SPEED UP: Now BasePositionNormalization is 2-3 times faster
due to memoization and a more clever prediction algorithm.
o MEMORY OPTIMIZATION: Added abstract normalization class
LinearModelProbeSequenceNormalization that fits linear models
based on probe sequences in bounded memory. This is done by
building up the normal equations incrementally and then call
solve(). It is the generation of normal equations that otherwise
consume most of the memory. The BasePositionNormalization
class now inherits from this memory-efficient class, which
means we can now do probe-position normalization on GenomeWideSNP_6
arrays using less than 1GB of RAM.
o MEMORY OPTIMIZATION: Forgot to clean out weight estimates in
ProbeLevelModel objects when cleaning out the memory cache.
o BUG FIX: For allele-specific estimates, FragmentLengthNormalization
would correctly estimate normalization scale factors, but due to a
typo, it effectively only update the signals for allele A. According
to the source code repository, this has been a bug from the very
beginning when allele-specific estimates was claimed to be supported.
o BUG FIX: RmaPlm(..., flavor="oligo") was broken, because oligo
was updated.
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UPDATES to aroma.core:
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Version: 0.9.6 [2008-12-04]
o SPEED UP: Now predict() of ProbePositionEffects is 6-7 times faster.
o SPEED UP: Now the result of isMissing() for AromaCellSequenceFile
can be cached.
o ALPHA: Added the BinnedScatter class with methods.
o CLEAN UP: readDataFrame() of AromaTabularBinaryFile would forget to
close the connection if verbose output was activated. When R later
would close such connections, a warning would be generated.
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When reporting problems on aroma.affymetrix, make sure 1) to run the latest
version of the package, 2) to report the output of sessionInfo() and
traceback(), and 3) to post a complete code example.
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