Linked Life Data

16258508

Source:http://linkedlifedata.com/resource/pubmed/id/16258508

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
12
pubmed:dateCreated
2005-11-21
pubmed:abstractText
We have previously published a suite of software tools that facilitates the reformulation of tissue microarray (TMA) data so that it may be analyzed using techniques originally devised for analysis of cDNA microarray data. However, current microarray data often feature multiple scores for a given tissue sample and antibody combination. Furthermore, an efficient and systematic method for combining scores that takes into account the differing staining properties of tissue epitopes has not been described. We thus present the TMA-Combiner, a new Microsoft Excel-based macro that permits analysis of data for which tissues may have two or more scores per antibody, and permits combination of data from multiple different tissue microarrays. It accomplishes this by rendering one score per tissue per antibody from two or more scores, using one of multiple user-selectable combination rules developed to account for the differing staining properties of tissue epitopes. This greatly facilitates analysis of tissue microarrays, particularly for users with large repositories of data, and may facilitate discovery of biological trends and help refine diagnostic accuracy of tissue markers in clinical samples.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
0893-3952
pubmed:author
pubmed:issnType
Print
pubmed:volume
18
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1641-8
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2005
pubmed:articleTitle
TMA-Combiner, a simple software tool to permit analysis of replicate cores on tissue microarrays.
pubmed:affiliation
Biological and Biomedical Sciences Program, Division of Medical Sciences, Harvard Medical School, Cambridge, MA 02138, USA. clliu@fas.harvard.edu
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, Non-P.H.S., Research Support, Non-U.S. Gov't