Conception de séries chronologiques
Contenu
Titre (dcterms:title)
fr
Conception de séries chronologiques
en
Time series design
Identifiant (dcterms:identifier)
obo:OBI_0500020
label (rdfs:label)
en
Time series design
fr
Conception de séries chronologiques
editor preferred label (obo:IAO_0000111)
en
Time series design
example of usage (obo:IAO_0000112)
en
PMID: 14744830-Microarrays are powerful tools for surveying the expression levels of many thousands of genes simultaneously. They belong to the new genomics technologies which have important applications in the biological, agricultural and pharmaceutical sciences. There are myriad sources of uncertainty in microarray experiments, and rigorous experimental design is essential for fully realizing the potential of these valuable resources. Two questions frequently asked by biologists on the brink of conducting cDNA or two-colour, spotted microarray experiments are 'Which mRNA samples should be competitively hybridized together on the same slide?' and 'How many times should each slide be replicated?' Early experience has shown that whilst the field of classical experimental design has much to offer this emerging multi-disciplinary area, new approaches which accommodate features specific to the microarray context are needed. In this paper, we propose optimal designs for factorial and time course experiments, which are special designs arising quite frequently in microarray experimentation. Our criterion for optimality is statistical efficiency based on a new notion of admissible designs; our approach enables efficient designs to be selected subject to the information available on the effects of most interest to biologists, the number of arrays available for the experiment, and other resource or practical constraints, including limitations on the amount of mRNA probe. We show that our designs are superior to both the popular reference designs, which are highly inefficient, and to designs incorporating all possible direct pairwise comparisons. Moreover, our proposed designs represent a substantial practical improvement over classical experimental designs which work in terms of standard interactions and main effects. The latter do not provide a basis for meaningful inference on the effects of most interest to biologists, nor make the most efficient use of valuable and limited resources.
has curation status (obo:IAO_0000114)
definition (obo:IAO_0000115)
en
Groups of assays that are related as part of a time series.
fr
Groupes d'essais liés à une série chronologique.
editor note (obo:IAO_0000116)
PRS-AGB adding formal restriction on independent variable specification about time (march 2013) and making time series design class a defined class.
term editor (obo:IAO_0000117)
en
Philippe Rocca-Serra on behalf of MO
fr
Jean-Marc Meunier
definition source (obo:IAO_0000119)
en
MO_887
imported from (obo:IAO_0000412)
type (rdf:type)
subClassOf (rdfs:subClassOf)
has broader (skos:broader)
hierarchy level (md:hierarchyLevel)
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