Linked Life Data

19276243

Source:http://linkedlifedata.com/resource/pubmed/id/19276243

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
2009-6-18
pubmed:abstractText
Novel techniques for analyzing microarray data are constantly being developed. Though many of the methods contribute to biological discoveries, inability to properly evaluate the novel techniques limits their ability to advance science. Because the underlying distribution of microarray data is unknown, novel methods are typically tested against the assumed normal distribution. However, microarray data are not, in fact, normally distributed, and assuming so can have misleading consequences. Using an Affymetrix technical replicate spike-in data set, we show that oligonucleotide expression values are not normally distributed for any of the standard methods for calculating expression values. The resulting data tend to have a large proportion of skew and heavy tailed genes. Additionally, we show that standard methods can give unexpected and misleading results when the data are not well approximated by the normal distribution. Robust methods are therefore recommended when analyzing microarray data. Additionally, new techniques should be evaluated with skewed and/or heavy-tailed data distributions.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jul
pubmed:issn
1468-4357
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
10
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
446-50
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
A note on oligonucleotide expression values not being normally distributed.
pubmed:affiliation
Department of Mathematics, Pomona College, 610 North College Avenue, Claremont, CA 91711, USA. jo.hardin@pomona.edu
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't