Designs for two-colour microarray experiments

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35 Citations (Scopus)

Abstract

Designs for two-colour microarray experiments can be viewed as block designs with two treatments per block. Explicit formulae for the A- and D-criteria are given for the case that the number of blocks is equal to the number of treatments. These show that the A- and D-optimality criteria conflict badly if there are 10 or more treatments. A similar analysis shows that designs with one or two extra blocks perform very much better, but again there is a conflict between the two optimality criteria for moderately large numbers of treatments. It is shown that this problem can be avoided by slightly increasing the number of blocks. The two colours that are used in each block effectively turn the block design into a row-column design. There is no need to use a design in which each treatment has each colour equally often; rather, an efficient row-column design should be used. For odd replication, it is recommended that the row-column design should be based on a bipartite graph, and it is proved that the optimal such design corresponds to an optimal block design for half the number of treatments. Efficient row-column designs are given for replications 3--6. It is shown how to adapt them for experiments in which some treatments have replication only 2.
Original languageEnglish
Pages (from-to)365-394
Number of pages30
JournalJournal of the Royal Statistical Society: Series C (Applied Statistics)
Volume56
Issue number4
Publication statusPublished - 2007

Keywords

  • block design
  • design of experiments
  • graph theory
  • microarray experiment
  • optimal design
  • robustness
  • row-column design

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