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Identify Global Objects in R Expressions
Identifies global ("unknown" or "free") objects in R expressions by code inspection using various strategies, e.g. conservative or liberal. The objective of this package is to make it as simple as possible to identify global objects for the purpose of exporting them in distributed compute environments.
'Markdown' Rendering for R
Provides R bindings to the 'Sundown' 'Markdown' rendering library ( https://github.com/vmg/sundown). 'Markdown' is a plain-text formatting syntax that can be converted to 'XHTML' or other formats. See http://en.wikipedia.org/wiki/Markdown for more information about 'Markdown'.
Methods for Reading dChip Files
Functions for reading DCP and CDF.bin files generated by the dChip software.
A Probe-Level Data File Format Used by 'aroma.affymetrix' [deprecated]
DEPRECATED. Do not start building new projects based on this package. (The (in-house) APD file format was initially developed to store Affymetrix probe-level data, e.g. normalized CEL intensities. Chip types can be added to APD file and similar to methods in the affxparser package, this package provides methods to read APDs organized by units (probesets). In addition, the probe elements can be arranged optimally such that the elements are guaranteed to be read in order when, for instance, data is read unit by unit. This speeds up the read substantially. This package is supporting the Aroma framework and should not be used elsewhere.)
Improved Allele-Specific Copy Number of SNP Microarrays for Downstream Segmentation
A multi-array post-processing method of allele-specific copy-number estimates (ASCNs).
Friendly R Startup Configuration
Adds support for R startup configuration via '.Renviron.d' and '.Rprofile.d' directories in addition to '.Renviron' and '.Rprofile' files. This makes it possible to keep private / secret environment variables separate from other environment variables. It also makes it easier to share specific startup settings by simply copying a file to a directory.
Affymetrix SNP Probe-Summarization using Non-Negative Matrix Factorization
A summarization method to estimate allele-specific copy number signals for Affymetrix SNP microarrays using non-negative matrix factorization (NMF).
A Future API for Parallel and Distributed Processing using BatchJobs
Implementation of the Future API on top of the 'BatchJobs' package. This allows you to process futures, as defined by the 'future' package, in parallel out of the box, not only on your local machine or ad-hoc cluster of machines, but also via high-performance compute ('HPC') job schedulers such as 'LSF', 'OpenLava', 'Slurm', 'SGE', and 'TORQUE' / 'PBS', e.g. 'y <- future.apply::future_lapply(files, FUN = process)'. NOTE: The 'BatchJobs' package is deprecated in favor of the 'batchtools' package. Because of this, it is recommended to use the 'future.batchtools' package instead of this package.
A Future API for Parallel Processing using 'callr'
Implementation of the Future API on top of the 'callr' package. This allows you to process futures, as defined by the 'future' package, in parallel out of the box, on your local (Linux, macOS, Windows, ...) machine. Contrary to backends relying on the 'parallel' package (e.g. 'future::multisession'), the 'callr' backend provided here can run more than 125 parallel R processes.
Methods for Accessing Huge Amounts of Data [deprecated]
DEPRECATED. Do not start building new projects based on this package. Cross-platform alternatives are the following packages: bigmemory (CRAN), ff (CRAN), BufferedMatrix (Bioconductor). The main usage of it was inside the aroma.affymetrix package. (The package currently provides a class representing a matrix where the actual data is stored in a binary format on the local file system. This way the size limit of the data is set by the file system and not the memory.)