May 2, 2013: aroma.affymetrix v2.9.0 released.
Apr 23, 2013: PSCBS v0.35.0 released.
Jan 11, 2013: The aroma.affymetrix package turns 7 years.
Jan 7, 2013: aroma.cn v1.3.0 and calmate v0.10.0 released.
Jan 14, 2012: OSX 10.6 & 10.7 users: If R crashes, install the affxparser OSX binary bug fix.

An open-source R framework for your microarray analysis

ChromosomeExplorer ArrayExplorer FIRMA and alternative splicing Allelic crosstalk

Aroma.affymetrix is an R package for analyzing large Affymetrix data sets.  It allows you to analyze 100-1,000s of arrays of various chip types, e.g. expression arrays, SNP chips, exon arrays and so on.  Here are some of the features:

  • Number of arrays: unlimited.
  • System requirements: As low as 1GB RAM, any operating system.
  • Chip types: all Affymetrix chip types with a CDF, e.g. gene expression, exon, SNP & CN, tiling arrays.
  • Immediate support for custom CDFs, e.g. BrainArray, GeneAnnot and Wageningen University-NuGO.
  • File formats: Works directly with CEL and CDF files (all versions; text/ASCII, binary/XDA, binary/Calvin).
  • Export to/Import from: Bioconductor, CNAG, CNAT & dChip.
  • Pre-processing: Background correction, allelic cross-talk calibration, quantile normalization, nucleotide-position normalization etc.
  • Probe-level modeling: RMA (log-additive), MBEI (multiplicative), affine (multiplicative with or without offset), ACNE (non-negative matrix factorization).
  • Post-processing: PCR fragment-length and/or GC-content normalization.
  • Paired & non-paired copy-number analysis: All generations, including 10K, 100K, 500K, 5.0, 6.0, and CytoScanHD. Estimation of full-resolution (raw) copy numbers using CRMA (10K-500K) and CRMAv2 (10K-CytoScanHD). Combine data from multiple chip types. Segmentation methods such as CBS, GLAD and HaarSeg.
  • Genotyping: CRLMM (100K & 500K).
  • Alternative splicing: FIRMA.
  • Dynamic HTML reports: ArrayExplorer & ChromosomeExplorer.
  • Persistent memory: Final and intermediate results and estimates are stored on the file system.
  • Robustness: Analysis picks up where last interrupted.  Only complete files are produced (even during power failures).
  • Reproducibility: Near perfect replication of RMA, GCRMA and SNPRMA (normalization & summarization) as implemented in the affyPLM, affy, gcrma and oligo packages, as well as CRLMM (genotyping) of oligo.
  • Portable scripts: All data sets and data files are referred to by their names - not by pathnames.
  • Design goals: usability, quality & extendibility.