Literature DB >> 19436837

Calculation of reliable transcript levels of annotated genes on the basis of multiple probe-sets in Affymetrix microarrays.

Roman Jaksik1, Joanna Polańska, Robert Herok, Joanna Rzeszowska-Wolny.   

Abstract

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.

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Year:  2009        PMID: 19436837

Source DB:  PubMed          Journal:  Acta Biochim Pol        ISSN: 0001-527X            Impact factor:   2.149


  12 in total

1.  Analysis of discordant Affymetrix probesets casts serious doubt on idea of microarray data reutilization.

Authors:  Andrey Marakhonov; Nataliya Sadovskaya; Ivan Antonov; Ancha Baranova; Mikhail Skoblov
Journal:  BMC Genomics       Date:  2014-12-19       Impact factor: 3.969

2.  SplicerAV: a tool for mining microarray expression data for changes in RNA processing.

Authors:  Timothy J Robinson; Michaela A Dinan; Mark Dewhirst; Mariano A Garcia-Blanco; James L Pearson
Journal:  BMC Bioinformatics       Date:  2010-02-25       Impact factor: 3.169

3.  SMARCA4/BRG1 Is a Novel Prognostic Biomarker Predictive of Cisplatin-Based Chemotherapy Outcomes in Resected Non-Small Cell Lung Cancer.

Authors:  Erica Hlavin Bell; Arup R Chakraborty; Xiaokui Mo; Ziyan Liu; Konstantin Shilo; Simon Kirste; Petra Stegmaier; Maureen McNulty; Niki Karachaliou; Rafael Rosell; Gerold Bepler; David P Carbone; Arnab Chakravarti
Journal:  Clin Cancer Res       Date:  2015-12-15       Impact factor: 12.531

4.  Three meta-analyses define a set of commonly overexpressed genes from microarray datasets on astrocytomas.

Authors:  Zhongyu Liu; Mengyu Xie; Zhiqiang Yao; Yulong Niu; Youquan Bu; Chunfang Gao
Journal:  Mol Neurobiol       Date:  2012-11-08       Impact factor: 5.590

5.  SCOREM: statistical consolidation of redundant expression measures.

Authors:  Stephanie Schneider; Temple Smith; Ulla Hansen
Journal:  Nucleic Acids Res       Date:  2011-12-30       Impact factor: 16.971

6.  Impact of heat shock transcription factor 1 on global gene expression profiles in cells which induce either cytoprotective or pro-apoptotic response following hyperthermia.

Authors:  Małgorzata Kus-Liśkiewicz; Joanna Polańska; Joanna Korfanty; Magdalena Olbryt; Natalia Vydra; Agnieszka Toma; Wiesława Widłak
Journal:  BMC Genomics       Date:  2013-07-08       Impact factor: 3.969

7.  Sources of high variance between probe signals in Affymetrix short oligonucleotide microarrays.

Authors:  Roman Jaksik; Michal Marczyk; Joanna Polanska; Joanna Rzeszowska-Wolny
Journal:  Sensors (Basel)       Date:  2013-12-31       Impact factor: 3.576

8.  Sexual Dimorphism and Aging in the Human Hyppocampus: Identification, Validation, and Impact of Differentially Expressed Genes by Factorial Microarray and Network Analysis.

Authors:  Daniel V Guebel; Néstor V Torres
Journal:  Front Aging Neurosci       Date:  2016-10-05       Impact factor: 5.750

9.  Knowledge Driven Variable Selection (KDVS) - a new approach to enrichment analysis of gene signatures obtained from high-throughput data.

Authors:  Grzegorz Zycinski; Annalisa Barla; Margherita Squillario; Tiziana Sanavia; Barbara Di Camillo; Alessandro Verri
Journal:  Source Code Biol Med       Date:  2013-01-09

Review 10.  Microarray experiments and factors which affect their reliability.

Authors:  Roman Jaksik; Marta Iwanaszko; Joanna Rzeszowska-Wolny; Marek Kimmel
Journal:  Biol Direct       Date:  2015-09-03       Impact factor: 4.540

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