Literature DB >> 18778252

Assessment of repeated microarray experiments using mixed tissue RNA reference samples.

M Ann Mongan1, Ann Mongan, Marnie Higgins, P Scott Pine, Scott Pine, Cynthia Afshari, Hisham Hamadeh.   

Abstract

Genome-scale gene expression technologies are increasingly being applied for biological research as a whole and toxicological screening in particular. In order to monitor data quality and process drift, we adopted the use of two rat-tissue mixtures (brain, liver, kidney, and testis) previously introduced as RNA reference samples. These samples were processed every time a microarray experiment was hybridized, thereby verifying the comparability of the resulting expression data for cross-study comparison. This study presents the analysis of 21 technical replicates of these two mixed-tissue samples using Affymetrix RAE230_2 GeneChip over a period of 12 months. The results show that detection sensitivity, measured by the number of present and absent sequences, is robust, and data correlation, indicated by scatter plots, varies little over time. Receiver operating characteristic (ROC) curves show the sensitivity and specificity of the current measurements are consistent with arrays previously classified as well performing. Overall, this paper shows that the inclusion of standard samples during microarray labeling and hybridization experiments is useful to benchmark the performance of microarray experiments over time and allows discovery of any process drift that, if it occurs, may confound the comparison of these datasets.

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Year:  2008        PMID: 18778252     DOI: 10.2144/000112914

Source DB:  PubMed          Journal:  Biotechniques        ISSN: 0736-6205            Impact factor:   1.993


  4 in total

1.  ANEXdb: an integrated animal ANnotation and microarray EXpression database.

Authors:  Oliver Couture; Keith Callenberg; Neeraj Koul; Sushain Pandit; Remy Younes; Zhi-Liang Hu; Jack Dekkers; James Reecy; Vasant Honavar; Christopher Tuggle
Journal:  Mamm Genome       Date:  2009-11-20       Impact factor: 2.957

2.  Tradeoffs between Dense and Replicate Sampling Strategies for High-Throughput Time Series Experiments.

Authors:  Emre Sefer; Michael Kleyman; Ziv Bar-Joseph
Journal:  Cell Syst       Date:  2016-07-21       Impact factor: 10.304

3.  A novel statistical algorithm for gene expression analysis helps differentiate pregnane X receptor-dependent and independent mechanisms of toxicity.

Authors:  M Ann Mongan; Robert T Dunn; Steven Vonderfecht; Nancy Everds; Guang Chen; Cheng Su; Marnie Higgins-Garn; Yuan Chen; Cynthia A Afshari; Toni L Williamson; Linda Carlock; Christopher Dipalma; Suzanne Moss; Jeanine Bussiere; Charles Qualls; Yudong D He; Hisham K Hamadeh
Journal:  PLoS One       Date:  2010-12-21       Impact factor: 3.240

4.  Relative impact of key sources of systematic noise in Affymetrix and Illumina gene-expression microarray experiments.

Authors:  Robert R Kitchen; Vicky S Sabine; Arthur A Simen; J Michael Dixon; John M S Bartlett; Andrew H Sims
Journal:  BMC Genomics       Date:  2011-12-01       Impact factor: 3.969

  4 in total

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