Corpus ID: 2106735

aroma.affymetrix: A generic framework in R for analyzing small to very large Affymetrix data sets in bounded memory

  title={aroma.affymetrix: A generic framework in R for analyzing small to very large Affymetrix data sets in bounded memory},
  author={H. Bengtsson and K. Simpson and James H. Bullard and K. Hansen},
Summary: We have developed a cross-platform open-source framework for analyzing Affymetrix data sets consisting of 1 to 1,000s of arrays. By working directly with CDF and CEL files (standard Affymetrix file formats) most chip types are automatically supported, e.g. expression, SNP, and exon arrays. The package provides methods for low-level analysis such as background correction of different kinds, allelic cross-talk calibration, quantile and affine normalization, PCR fragment-length and GC… Expand
161 Citations

Figures and Tables from this paper

Reproducible probe-level analysis of the Affymetrix Exon 1.0 ST array with R/Bioconductor
  • 11
  • PDF
Exon array data analysis using Affymetrix power tools and R statistical software
  • H. Lockstone
  • Biology, Computer Science
  • Briefings Bioinform.
  • 2011
  • 83
  • PDF
A scalable method for cross-platform merging of SNP array datasets
  • PDF
iGEMS: an integrated model for identification of alternative exon usage events
  • 15
  • PDF
MPAgenomics: an R package for multi-patient analysis of genomic markers
  • 4
  • PDF


Summaries of Affymetrix GeneChip probe level data.
  • 4,986
  • Highly Influential
  • PDF
Model-based analysis of oligonucleotide arrays: expression index computation and outlier detection.
  • C. Li, W. Wong
  • Biology, Medicine
  • Proceedings of the National Academy of Sciences of the United States of America
  • 2001
  • 3,324
  • PDF
A comparison of normalization methods for high density oligonucleotide array data based on variance and bias
  • 7,709
  • PDF
A faster circular binary segmentation algorithm for the analysis of array CGH data
  • 875
  • PDF
Bioconductor: open software development for computational biology and bioinformatics
  • 11,319
  • Highly Influential
  • PDF