CSDL Home IEEE/ACM Transactions on Computational Biology and Bioinformatics 2010 vol.7 Issue No.04 - October-December
Issue No.04 - October-December (2010 vol.7)
W.B. Langdon , University of Essex, Colchester
G.J.G. Upton , University of Essex, Colchester
Renata da Silva Camargo , University of Essex, Colchester
Andrew P. Harrison , University of Essex, Colchester
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TCBB.2008.108
Modern biology has moved from a science of individual measurements to a science where data are collected on an industrial scale. Foremost, among the new tools for biochemistry are chip arrays which, in one operation, measure hundreds of thousands or even millions of DNA sequences or RNA transcripts. While this is impressive, increasingly sophisticated analysis tools have been required to convert gene array data into gene expression levels. Despite the assumption that noise levels are low, since the number of measurements for an individual gene is small, identifying which signals are affected by noise is a priority. High-density oligonucleotide array (HDONAs) from NCBI GEO shows that, even in the best Human GeneChips 1/4 percent of data are affected by spatial noise. Earlier designs are noisier and spatial defects may affect more than 25 percent of probes. BioConductor R code is available as supplementary material which can be found on the Computer Society Digital Library at http://doi.ieeecomputersociety.org/10.1109/TCBB.2008.108 and via http://bioinformatics.essex.ac.uk/users/wlangdon/TCBB-2007-11-0161.tar.gz.
Oligonucleotide array, Affymetrix, microarray, error detection, image processing.
W.B. Langdon, G.J.G. Upton, Renata da Silva Camargo, Andrew P. Harrison, "A Survey of Spatial Defects in Homo Sapiens Affymetrix GeneChips", IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol.7, no. 4, pp. 647-653, October-December 2010, doi:10.1109/TCBB.2008.108