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Hochreiter, S., Clevert, D.-A., & Obermayer, K. (2006). A new summarization method for Affymetrix probe level data. Bioinformatics (Oxford, England), 22(8), 943–949.

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Hochreiter S, Clevert DA, Obermayer K. A new summarization method for Affymetrix probe level data. Bioinformatics. 2006 Apr 15;22(8):943–9.

@ARTICLE{Hochreiter2006-ji,
  title     = "A new summarization method for Affymetrix probe level data",
  author    = "Hochreiter, Sepp and Clevert, Djork-Arn{\'e} and Obermayer,
               Klaus",
  abstract  = "MOTIVATION: We propose a new model-based technique for
               summarizing high-density oligonucleotide array data at probe
               level for Affymetrix GeneChips. The new summarization method is
               based on a factor analysis model for which a Bayesian maximum a
               posteriori method optimizes the model parameters under the
               assumption of Gaussian measurement noise. Thereafter, the RNA
               concentration is estimated from the model. In contrast to
               previous methods our new method called 'Factor Analysis for
               Robust Microarray Summarization (FARMS)' supplies both P-values
               indicating interesting information and signal intensity values.
               RESULTS: We compare FARMS on Affymetrix's spike-in and Gene
               Logic's dilution data to established algorithms like Affymetrix
               Microarray Suite (MAS) 5.0, Model Based Expression Index (MBEI),
               Robust Multi-array Average (RMA). Further, we compared FARMS
               with 43 other methods via the 'Affycomp II' competition. The
               experimental results show that FARMS with default parameters
               outperforms previous methods if both sensitivity and specificity
               are simultaneously considered by the area under the receiver
               operating curve (AUC). We measured two quantities through the
               AUC: correctly detected expression changes versus wrongly
               detected (fold change) and correctly detected significantly
               different expressed genes in two sets of arrays versus wrongly
               detected (P-value). Furthermore FARMS is computationally less
               expensive then RMA, MAS and MBEI. AVAILABILITY: The FARMS R
               package is available from
               http://www.bioinf.jku.at/software/farms/farms.html.
               SUPPLEMENTARY INFORMATION:
               http://www.bioinf.jku.at/publications/papers/farms/supplementary.ps",
  journal   = "Bioinformatics",
  publisher = "Oxford University Press (OUP)",
  volume    =  22,
  number    =  8,
  pages     = "943--949",
  month     =  apr,
  year      =  2006,
  url       = "https://academic.oup.com/bioinformatics/article/22/8/943/227151?login=true",
  language  = "en",
  issn      = "1367-4803, 1367-4811",
  pmid      = "16473874",
  doi       = "10.1093/bioinformatics/btl033"
}

TY  - JOUR
AU  - Hochreiter, Sepp
AU  - Clevert, Djork-Arné
AU  - Obermayer, Klaus
AD  - Department of Electrical Engineering and Computer Science, Technische
      Universität Berlin, 10587 Berlin, Germany. hochreit@bioinf.jku.at
TI  - A new summarization method for Affymetrix probe level data
T2  - Bioinformatics
VL  - 22
IS  - 8
SP  - 943-949
PY  - 2006
DA  - 2006/4/15
Y2  - 2021/3/4
PB  - Oxford University Press (OUP)
AB  - MOTIVATION: We propose a new model-based technique for summarizing
      high-density oligonucleotide array data at probe level for Affymetrix
      GeneChips. The new summarization method is based on a factor analysis
      model for which a Bayesian maximum a posteriori method optimizes the model
      parameters under the assumption of Gaussian measurement noise. Thereafter,
      the RNA concentration is estimated from the model. In contrast to previous
      methods our new method called 'Factor Analysis for Robust Microarray
      Summarization (FARMS)' supplies both P-values indicating interesting
      information and signal intensity values. RESULTS: We compare FARMS on
      Affymetrix's spike-in and Gene Logic's dilution data to established
      algorithms like Affymetrix Microarray Suite (MAS) 5.0, Model Based
      Expression Index (MBEI), Robust Multi-array Average (RMA). Further, we
      compared FARMS with 43 other methods via the 'Affycomp II' competition.
      The experimental results show that FARMS with default parameters
      outperforms previous methods if both sensitivity and specificity are
      simultaneously considered by the area under the receiver operating curve
      (AUC). We measured two quantities through the AUC: correctly detected
      expression changes versus wrongly detected (fold change) and correctly
      detected significantly different expressed genes in two sets of arrays
      versus wrongly detected (P-value). Furthermore FARMS is computationally
      less expensive then RMA, MAS and MBEI. AVAILABILITY: The FARMS R package
      is available from http://www.bioinf.jku.at/software/farms/farms.html.
      SUPPLEMENTARY INFORMATION:
      http://www.bioinf.jku.at/publications/papers/farms/supplementary.ps
SN  - 1367-4803
DO  - 10.1093/bioinformatics/btl033
UR  - https://academic.oup.com/bioinformatics/article/22/8/943/227151?login=true
UR  - http://bioinformatics.oxfordjournals.org/cgi/content/abstract/22/8/943
UR  - https://academic.oup.com/bioinformatics/article-lookup/doi/10.1093/bioinformatics/btl033
UR  - http://dx.doi.org/10.1093/bioinformatics/btl033
UR  - https://www.ncbi.nlm.nih.gov/pubmed/16473874
ER  -