Literature DB >> 12874043

New normalization methods for cDNA microarray data.

D L Wilson1, M J Buckley, C A Helliwell, I W Wilson.   

Abstract

MOTIVATION: The focus of this paper is on two new normalization methods for cDNA microarrays. After the image analysis has been performed on a microarray and before differentially expressed genes can be detected, some form of normalization must be applied to the microarrays. Normalization removes biases towards one or other of the fluorescent dyes used to label each mRNA sample allowing for proper evaluation of differential gene expression.
RESULTS: The two normalization methods that we present here build on previously described non-linear normalization techniques. We extend these techniques by firstly introducing a normalization method that deals with smooth spatial trends in intensity across microarrays, an important issue that must be dealt with. Secondly we deal with normalization of a new type of cDNA microarray experiment that is coming into prevalence, the small scale specialty or 'boutique' array, where large proportions of the genes on the microarrays are expected to be highly differentially expressed. AVAILABILITY: The normalization methods described in this paper are available via http://www.pi.csiro.au/gena/ in a software suite called tRMA: tools for R Microarray Analysis upon request of the authors. Images and data used in this paper are also available via the same link.

Mesh:

Year:  2003        PMID: 12874043     DOI: 10.1093/bioinformatics/btg146

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  32 in total

1.  A customized gene expression microarray reveals that the brittle stem phenotype fs2 of barley is attributable to a retroelement in the HvCesA4 cellulose synthase gene.

Authors:  Rachel A Burton; Gang Ma; Ute Baumann; Andrew J Harvey; Neil J Shirley; Jillian Taylor; Filomena Pettolino; Antony Bacic; Mary Beatty; Carl R Simmons; Kanwarpal S Dhugga; J Antoni Rafalski; Scott V Tingey; Geoffrey B Fincher
Journal:  Plant Physiol       Date:  2010-06-07       Impact factor: 8.340

2.  High-resolution spatial normalization for microarrays containing embedded technical replicates.

Authors:  Daniel S Yuan; Rafael A Irizarry
Journal:  Bioinformatics       Date:  2006-10-23       Impact factor: 6.937

3.  Laser capture microdissection and cDNA microarrays used to generate gene expression profiles of the rapidly expanding fibre initial cells on the surface of cotton ovules.

Authors:  Yingru Wu; Danny J Llewellyn; Rosemary White; Katya Ruggiero; Yves Al-Ghazi; Elizabeth S Dennis
Journal:  Planta       Date:  2007-07-18       Impact factor: 4.116

4.  Gene expression in a starch synthase IIa mutant of barley: changes in the level of gene transcription and grain composition.

Authors:  B Clarke; R Liang; M K Morell; A R Bird; C L D Jenkins; Z Li
Journal:  Funct Integr Genomics       Date:  2008-02-13       Impact factor: 3.410

5.  Gene expression profiling differentiates germ cell tumors from other cancers and defines subtype-specific signatures.

Authors:  Dejan Juric; Sanja Sale; Robert A Hromas; Ron Yu; Yan Wang; George E Duran; Robert Tibshirani; Lawrence H Einhorn; Branimir I Sikic
Journal:  Proc Natl Acad Sci U S A       Date:  2005-11-23       Impact factor: 11.205

6.  A microarray analysis of wheat grain hardness.

Authors:  Bryan Clarke; Sadequr Rahman
Journal:  Theor Appl Genet       Date:  2005-04-02       Impact factor: 5.699

7.  Microarray meta-analysis database (M(2)DB): a uniformly pre-processed, quality controlled, and manually curated human clinical microarray database.

Authors:  Wei-Chung Cheng; Min-Lung Tsai; Cheng-Wei Chang; Ching-Lung Huang; Chaang-Ray Chen; Wun-Yi Shu; Yun-Shien Lee; Tzu-Hao Wang; Ji-Hong Hong; Chia-Yang Li; Ian C Hsu
Journal:  BMC Bioinformatics       Date:  2010-08-10       Impact factor: 3.169

8.  Identification of differentially expressed transcripts from maturing stem of sugarcane by in silico analysis of stem expressed sequence tags and gene expression profiling.

Authors:  Rosanne E Casu; Christine M Dimmock; Scott C Chapman; Christopher P L Grof; C Lynne McIntyre; Graham D Bonnett; John M Manners
Journal:  Plant Mol Biol       Date:  2004-03       Impact factor: 4.076

9.  A cross-species transcriptomics approach to identify genes involved in leaf development.

Authors:  Nathaniel Robert Street; Andreas Sjödin; Max Bylesjö; Petter Gustafsson; Johan Trygg; Stefan Jansson
Journal:  BMC Genomics       Date:  2008-12-05       Impact factor: 3.969

10.  Normalization and gene p-value estimation: issues in microarray data processing.

Authors:  Katrin Fundel; Robert Küffner; Thomas Aigner; Ralf Zimmer
Journal:  Bioinform Biol Insights       Date:  2008-05-28
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.