z-logo
open-access-imgOpen Access
Calculation of reliable transcript levels of annotated genes on the basis of multiple probe-sets in Affymetrix microarrays.
Author(s) -
Roman Jaksik,
Joanna Polańska,
Robert Herok,
Joanna RzeszowskaWolny
Publication year - 2009
Publication title -
acta biochimica polonica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.452
H-Index - 78
eISSN - 1734-154X
pISSN - 0001-527X
DOI - 10.18388/abp.2009_2459
Subject(s) - bioconductor , dna microarray , computational biology , gene , annotation , microarray , biology , outlier , genome , microarray analysis techniques , set (abstract data type) , gene annotation , computer science , genetics , gene expression , data mining , artificial intelligence , programming language
Microarray methods have become a basic tool in studies of global gene expression and changes in transcript levels. Affymetrix microarrays from the HGU133 series contain multiple probe-sets complementary to the same gene (4742 genes are represented by more than one probe-set in a microarray HGU133A). Individual probe-sets annotated to the same gene often show different hybridization signals and even opposite trends, which may result from some of them matching transcripts of more than one gene and from the existence of different splice-variant transcripts. Existing methods that redefine probe-sets and develop custom probe-set definitions use mathematical tools such as Matlab or the R statistical environment with the Bioconductor package (Gentleman et al., 2004, Genome Biol. 5: 280) and thus are directed to researchers with a good knowledge of bioinformatics. We propose here a new approach based on the principle that a probe-set which hybridizes to more than one transcript can be recognized because it produces a signal significantly different from others assigned to the particular gene, allowing it to be detected as an outlier in the group and eliminated from subsequent analyses. A simple freeware application has been developed (available at www.bioinformatics.aei.polsl.pl) that detects and removes outlying probe-sets and calculates average signal values for individual genes using the latest annotation database provided by Affymetrix. We illustrate this procedure using microarray data from our experiments aiming to study changes of transcription profile induced by ionizing radiation in human cells.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom