Match-Only Integral Distribution (MOID) Algorithm for high-density oligonucleotide array analysis

BackgroundHigh-density oligonucleotide arrays have become a valuable tool for high-throughput gene expression profiling. Increasing the array information density and improving the analysis algorithms are two important computational research topics.ResultsA new algorithm, Match-Only Integral Distribution (MOID), was developed to analyze high-density oligonucleotide arrays. Using known data from both spiking experiments and no-change experiments performed with Affymetrix GeneChip® arrays, MOID and the Affymetrix algorithm implemented in Microarray Suite 4.0 (MAS4) were compared. While MOID gave similar performance to MAS4 in the spiking experiments, better performance was observed in the no-change experiments.MOID also provides a set of alternative statistical analysis tools to MAS4. There are two main features that distinguish MOID from MAS4. First, MOID uses continuous P values for the likelihood of gene presence, while MAS4 resorts to discrete absolute calls. Secondly, MOID uses heuristic confidence intervals for both gene expression levels and fold change values, while MAS4 categorizes the significance of gene expression level changes into discrete fold change calls.ConclusionsThe results show that by using MOID, Affymetrix GeneChip® arrays may need as little as ten probes per gene without compromising analysis accuracy.

• Publication year

  2002

• Venue

  BMC Bioinformatics

• Publication date

  2002-01-22

• Fields of study

  Biology, Medicine, Computer Science

• Identifiers
  DOI 10.1186/1471-2105-3-3PMID 11835687PMCID 65509
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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