Microarray analysis techniques: Difference between revisions

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Revision as of 19:40, 7 May 2021

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[[File:Mas5.jpg|thumb|500px|none|Flowchart showing how the MAS5 algorithm by Agilent works.]]

Factor Analysis for Robust Microarray Summarization (FARMS)<ref>{{cite journal | vauthors = Hochreiter S, Clevert DA, Obermayer K | year = 2006 | title = A new summarization method for affymetrix probe level data | url = http://bioinformatics.oxfordjournals.org/cgi/content/short/22/8/943 | journal = Bioinformatics | volume = 22 | issue = 8| pages = 943–949 | doi=10.1093/bioinformatics/btl033 | pmid=16473874| doi-access = free }}</ref> is a model-based technique for summarizing array data at perfect match probe level. It 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. According to the Affycomp benchmark<ref>{{Cite web | url=http://affycomp.jhsph.edu/ | title=Affycomp III: A Benchmark for Affymetrix GeneChip Expression Measures}}</ref> FARMS outperformed all other summarizations methods with respect to sensitivity and specificity.

===Identification of significant differential expression===