[aroma.affymetrix] aroma.affymetrix 3.0.0 release (10 years today!) - now with parallel processing

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[aroma.affymetrix] aroma.affymetrix 3.0.0 release (10 years today!) - now with parallel processing

Henrik Bengtsson-2
The Aroma Project turns 10 years today.  Technically it's probably a
few weeks older, but it was on Jan 11, 2006 that a few R scripts was
put together to create the aroma.affymetrix.  To celebrate,
aroma.affymetrix 3.0.0 has been released and it brings some exiting
updates including parallel processing (finally!) and automatic
generation of checksum files.  For full update details, see the end of
this message.  To update, just do:

    source("http://callr.org/install#aroma.affymetrix")


Now to what everyone is wondering - how can we do parallel processing?
 It is super easy because everything is taken care of internally, so
no need to change anything.  All you have to do is specify what type
of processing you wish to use.  To utilize multiple cores on the local
machine, just add (preferably to your ~/.Rprofile startup file):

    future::plan("multicore")

That's all.  Pretty neat, eh?  For other types of parallel processing,
see http://aroma-project.org/howtos/parallel_processing/.

Enjoy,

Henrik



Details on updated since aroma.affymetrix 2.14.0 (2015-10-24).

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Updates to aroma.affymetrix
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Version: 3.0.0 [2016-01-09]
o SPEED: Adding support for parallel/distributed processing via futures
  to some of the methods for which it is possible to process each
  sample independently, e.g. background and crosstalk correction methods.
o REPRODUCIBILITY: Several of the methods now generate *.md5 checksum
  files for the data files they output.
o REPRODUCIBILITY: GcRmaBackgroundCorrection(), LimmaBackgroundCorrection(),
  and RmaBackgroundCorrection() gained argument 'seed'.
o Package requires R (>= 3.1.2) and BioC (>= 3.0) both released
  in October 2014.
o Now also convertToUnique() acknowledge asterisk tags.
o ROBUSTNESS: MatNormalization did not create CEL files atomically.
o ROBUSTNESS: Using do.call(fcn) internally instead of do.call("fcn").
o ROBUSTNESS: Using getPathname() instead of accessing private field.
o CLEANUP: Warnings on "is.na() applied to non-(list or vector) of
  type 'NULL'" are no longer generated.
o CLEANUP: Formally defunct'ed bgAdjustRma(), bgAdjustGcrma(),
  bgAdjustOptical() for AffymetrixCelFile/AffymetrixCelSet since they
  have effectively been defunct'ed in the public API for years.  These
  are now all incorporated in corresponding BackgroundCorrection classes.
o BUG FIX: LimmaBackgroundCorrection(..., addJitter=TRUE) gave an error.
o BUG FIX: convertToUnique() for AffymetrixCelSet would give an error
  if there was an error while checking if results already exist.


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Updates to aroma.core
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Version: 3.0.0 [2016-01-05]
o SPEED: Segmentation methods (e.g. CbsModel) now uses futures, which
  means that samples can now be segmented in parallel/distributed.
o Package requires R (>= 3.1.2) and BioC (>= 3.0) both released in
  October 2014.
o ROBUSTNESS: Using do.call(fcn) internally instead of do.call("fcn").
o ROBUSTNESS: Using getPathname() instead of accessing private field.
o CLEANUP: Defunct apply() for SampleAnnotationFile; use applyTo().
o CLEANUP: Drop defunct methods.
o BUG FIX: getOutputDataSet(..., onMissing="dropall") for AromaTransform
  would throw error on no applicable method getFullNames() for NULL.


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Updates to R.filesets
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Version: 2.10.0 [2016-01-04]
o Now file sizes are reported using IEC binary prefixes, i.e.
  bytes, KiB, MiB, GiB, TiB, ..., YiB.
o Preparing to make the default pathname for GenericDataFile() to
  become NA_character_.  It is currently NULL, but the goal is to
  enforce length(pathname) to be one.
o Added hasChecksumFile() for GenericDataFile.
o hasBeenModified() for GenericDataFile gained argument 'update'.
o Package requires R (>= 3.1.2) released October 2014, because
  of its dependency on the listenv package.
o CLEANUP: extractMatrix(ds, files, ...) for GenericTabularFileSet
  is deprecated. Use extractMatrix(ds[files], ...) instead.
o CLEANUP: Removed na.omit() for GenericDataFileSet; the default
  one in the stats package works equally well.
o ROBUSTNESS: Increased test coverage from 51% to 62%.
o BUG FIX: Arguments$getTags() failed to drop missing values.
o BUG FIX: equals(df, other) for GenericDataFile would give an error
  if 'other' was not a GenericDataFile.
o BUG FIX: dropTags() would drop name if a tag had the same name.
o BUG FIX: getOneFile() on a GenericDataFileSet with a single
  missing file would give an error, now it gives a file with
  an NA pathname.


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PSCBS
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Version: 0.60.0 [2015-11-17]
o PARALLEL: Add support for parallel processing via futures by
  utilizing the future package.  Parallel segmentation over multiple
  chromosomes (or known segments) done by segmentByCBS() and
  segmentByPairedPSCBS() is enabled by future::plan("multicore").
o REPRODUCIBILITY: Whenever argument 'seed' is given, the
  L'Ecuyer-CMRG stream is now used to generate random numbers.
  For backward compatibility with other types of random number
  generators, don't specify argument 'seed' but instead use
  set.seed() to set the seed before calling the method.
o Bump package dependencies.

--
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