Linked Life Data

12034851

Source:http://linkedlifedata.com/resource/pubmed/id/12034851

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
11
pubmed:dateCreated
2002-5-29
pubmed:abstractText
Data from gene expression arrays are influenced by many experimental parameters that lead to variations not simply accessible by standard quantification methods. To compare measurements from gene expression array experiments, quantitative data are commonly normalised using reference genes or global normalisation methods based on mean or median values. These methods are based on the assumption that (i) selected reference genes are expressed at a standard level in all experiments or (ii) that mean or median signal of expression will give a quantitative reference for each individual experiment. We introduce here a new ranking diagram, with which we can show how the different normalisation methods compare, and how they are influenced by variations in measurements (noise) that occur in every experiment. Furthermore, we show that an upper trimmed mean provides a simple and robust method for normalisation of larger sets of experiments by comparative analysis.
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jun
pubmed:issn
1362-4962
pubmed:author
pubmed:issnType
Electronic
pubmed:day
1
pubmed:volume
30
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
e50
pubmed:dateRevised
2009-11-18
pubmed:meshHeading
pubmed:year
2002
pubmed:articleTitle
Ranking: a closer look on globalisation methods for normalisation of gene expression arrays.
pubmed:affiliation
AG Molekularbiologie, Klinik für Innere Medizin, Klinikum der Friedrich Schiller Universität Jena, Erlanger Allee 101, D-07747 Jena, Germany.
pubmed:publicationType
Journal Article, Comparative Study, Research Support, Non-U.S. Gov't