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Preferred analysis methods for Affymetrix GeneChips. II. An expanded, balanced, wholly-defined spike-in dataset.

ABSTRACT: Concomitant with the rise in the popularity of DNA microarrays has been a surge of proposed methods for the analysis of microarray data. Fully controlled "spike-in" datasets are an invaluable but rare tool for assessing the performance of various methods.We generated a new wholly defined Affymetrix spike-in dataset consisting of 18 microarrays. Over 5700 RNAs are spiked in at relative concentrations ranging from 1- to 4-fold, and the arrays from each condition are balanced with respect to both total RNA amount and degree of positive versus negative fold change. We use this new "Platinum Spike" dataset to evaluate microarray analysis routes and contrast the results to those achieved using our earlier Golden Spike dataset.We present updated best-route methods for Affymetrix GeneChip analysis and demonstrate that the degree of "imbalance" in gene expression has a significant effect on the performance of these methods.

SUBMITTER: Zhu Q

PROVIDER: S-EPMC2897828 | biostudies-literature | 2010 May

REPOSITORIES: biostudies-literature

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Preferred analysis methods for Affymetrix GeneChips. II. An expanded, balanced, wholly-defined spike-in dataset.

Zhu Qianqian Q Miecznikowski Jeffrey C JC Halfon Marc S MS

BMC bioinformatics 20100527

<h4>Background</h4>Concomitant with the rise in the popularity of DNA microarrays has been a surge of proposed methods for the analysis of microarray data. Fully controlled "spike-in" datasets are an invaluable but rare tool for assessing the performance of various methods.<h4>Results</h4>We generated a new wholly defined Affymetrix spike-in dataset consisting of 18 microarrays. Over 5700 RNAs are spiked in at relative concentrations ranging from 1- to 4-fold, and the arrays from each condition ...[more]

PMID: 20507584

Similar Datasets

Preferred analysis methods for Affymetrix GeneChips. II. An expanded, balanced, wholly-defined spike-in dataset

2010-04-15 | GSE21344 | GEO

Preferred analysis methods for Affymetrix GeneChips. II. An expanded, balanced, wholly-defined spike-in dataset

Project description:We present a new wholly defined Affymetrix spike-in dataset consisting of 18 microarrays. Over 5700 RNAs are spiked in at relative concentrations ranging from 1- to 4-fold, and the arrays from each condition are balanced with respect to both total RNA amount and degree of positive- versus negative-fold change. We use this new â??Platinum Spikeâ?? dataset to evaluate microarray analysis routes and contrast the results to those achieved using our earlier Golden Spike dataset. PCR products from 5725 Drosophila Gene Collection release 1.0 (DGCr1) cDNA clones were collected into 28 distinct pools, and three independent in vitro transcription and labeling reactions were performed for each pool. Labeled cRNAs from each individual pool were then added at specified amounts to samples A and B to achieve the desired fold change differences between samples. 24 cRNAs generated from DGCr2 cDNA clones were added to each sample in known concentrations before hybridization.

2010-04-28 | E-GEOD-21344 | biostudies-arrayexpress

Preferred analysis methods for Affymetrix GeneChips revealed by a wholly defined control dataset.

Project description:BackgroundAs more methods are developed to analyze RNA-profiling data, assessing their performance using control datasets becomes increasingly important.ResultsWe present a 'spike-in' experiment for Affymetrix GeneChips that provides a defined dataset of 3,860 RNA species, which we use to evaluate analysis options for identifying differentially expressed genes. The experimental design incorporates two novel features. First, to obtain accurate estimates of false-positive and false-negative rates, 100-200 RNAs are spiked in at each fold-change level of interest, ranging from 1.2 to 4-fold. Second, instead of using an uncharacterized background RNA sample, a set of 2,551 RNA species is used as the constant (1x) set, allowing us to know whether any given probe set is truly present or absent. Application of a large number of analysis methods to this dataset reveals clear variation in their ability to identify differentially expressed genes. False-negative and false-positive rates are minimized when the following options are chosen: subtracting nonspecific signal from the PM probe intensities; performing an intensity-dependent normalization at the probe set level; and incorporating a signal intensity-dependent standard deviation in the test statistic.ConclusionsA best-route combination of analysis methods is presented that allows detection of approximately 70% of true positives before reaching a 10% false-discovery rate. We highlight areas in need of improvement, including better estimate of false-discovery rates and decreased false-negative rates.

| S-EPMC551536 | biostudies-literature

A wholly defined Agilent microarray spike-in dataset.

Project description:MotivationSpike-in datasets provide a valuable resource for assessing and comparing among competing microarray analysis strategies. Our previous wholly defined spike-in datasets, the Golden and Platinum Spikes, have provided insights for the analysis of Affymetrix GeneChips. However, a similar dataset, in which all cRNA identities and relative levels are known prospectively, has not been available for two-color platforms.ResultsWe have generated a wholly defined spike-in dataset for Agilent microarrays consisting of 12 arrays with more than 2000 differentially expressed, and approximately 3600 background, cRNAs. The composition of this 'Ag Spike' dataset is identical to that of our previous Platinum Spike dataset and therefore allows direct cross-platform comparison. We demonstrate here the utility of the Ag Spike dataset for evaluating different analysis methods designed for two-color arrays. Comparison between the Ag Spike and Platinum Spike studies shows high agreement between results obtained using the Affymetrix and Agilent platforms.AvailabilityThe Ag Spike raw data can be accessed at http://www.ccr.buffalo.edu/halfon/spike/index.html and through NCBI's Gene Expression Omnibus (GEO; accession GSE24866).

| S-EPMC3109518 | biostudies-literature

A wholly-defined Agilent microarray spike-in dataset

2010-10-23 | GSE24866 | GEO

A wholly-defined Agilent microarray spike-in dataset

Project description:We have generated a wholly defined spike-in dataset for Agilent microarrays consisting of 12 arrays with more than 2000 differentially expressed, and approximately 3600 background, cRNAs. The composition of this âAg Spikeâdataset is identical to that of our previous Platinum Spike dataset (GSE21344) and therefore allows direct cross-platform comparison. Comparison between the Ag Spike and Platinum Spike studies shows high agreement between results obtained using the Affymetrix and Agilent platforms. We used the same 28 PCR pools that had been used before to generate the Platinum-Spike dataset (GSE21344). These pools contain PCR products from 5725 Drosophila Gene Collection release 1.0 (DGCr1) cDNA clones. We mixed PCR products from all pools together with specified relative abundance to generate two samples representing the A and B conditions. Both samples were in vitro transcribed and then labeled with Cy3 and Cy5 fluorescent dye. Labeled A samples were hybridized with B samples labeled with reverse dye to three Agilent Drosophila Gene Expression microarrays. The process from in vitro transcription to hybridization was repeated twice. At the end we generated 12 arrays that were randomly placed in three independent slides to remove potential systematic error due to array position.

2010-10-23 | E-GEOD-24866 | biostudies-arrayexpress

Comparison of target labeling methods for use with Affymetrix GeneChips.

Project description:BackgroundSeveral different commercial one-cycle labeling kits are available for preparation of the target for use with the Affymetrix GeneChip platform. However, there have been no evaluations of these different kits to determine if comparable results were generated. We report on the cRNA target synthesis, labeling efficiency and hybridization results using the One-Cycle Target Labeling Assay (Affymetrix), the BioArray RNA Amplification and Labeling System (Enzo Life Sciences), and the Superscript RNA Amplification System (Invitrogen Life Technologies).ResultsThe only notable difference between kits was in the yield of cRNA target synthesized during in vitro transcription, where the BioArray assay had to be repeated several times in order to have sufficient target. However, each kit resulted in comparable signal and detection calls when hybridized to the Affymetrix GeneChip.ConclusionThese 3 one-cycle labeling kits produce comparable hybridization results. This provides users with several kit options and flexibility when using the Affymetrix system.

| S-EPMC1885795 | biostudies-literature

Using luminescent nanoparticles as staining probes for Affymetrix GeneChips.

Project description:Microarray technology provides efficient access to genetic information using miniaturized, high-density arrays of DNA probes. We investigated the application of luminescent nanoparticles as probes for Affymetrix GeneChips detection without the need for signal amplification. Our goal is to investigate the feasibility of using luminescent nanoparticles as probes in a commercial microarray system without changing its configurations. With the present imaging modality and existing optical excitation and detection systems of the Affymetrix GeneChips, our early results indicate that nanoparticles not only can be used for GeneChip labeling but also are superior to the traditional fluorescent protein streptavidin-phycoerythrin (SAPE). The advantage of the particles lies in a simplified staining procedure, higher photobleaching threshold, and enhanced luminescence signal. The nanoparticles can be used for detection of low-abundance targets without any amplification step. A concentration detection limit of 50 fM has been achieved. This work demonstrates the feasibility of using luminescent nanoparticles as probes for commercial microarray systems, making them less costly, more reproducible, and potentially quantitative.

| S-EPMC2527177 | biostudies-literature

Microarray labeling extension values: laboratory signatures for Affymetrix GeneChips.

Project description:Interlaboratory comparison of microarray data, even when using the same platform, imposes several challenges to scientists. RNA quality, RNA labeling efficiency, hybridization procedures and data-mining tools can all contribute variations in each laboratory. In Affymetrix GeneChips, about 11-20 different 25-mer oligonucleotides are used to measure the level of each transcript. Here, we report that 'labeling extension values (LEVs)', which are correlation coefficients between probe intensities and probe positions, are highly correlated with the gene expression levels (GEVs) on eukaryotic Affymetrix microarray data. By analyzing LEVs and GEVs in the publicly available 2414 cel files of 20 Affymetrix microarray types covering 13 species, we found that correlations between LEVs and GEVs only exist in eukaryotic RNAs, but not in prokaryotic ones. Surprisingly, Affymetrix results of the same specimens that were analyzed in different laboratories could be clearly differentiated only by LEVs, leading to the identification of 'laboratory signatures'. In the examined dataset, GSE10797, filtering out high-LEV genes did not compromise the discovery of biological processes that are constructed by differentially expressed genes. In conclusion, LEVs provide a new filtering parameter for microarray analysis of gene expression and it may improve the inter- and intralaboratory comparability of Affymetrix GeneChips data.

| S-EPMC2677891 | biostudies-literature

Motif effects in Affymetrix GeneChips seriously affect probe intensities.

Project description:An Affymetrix GeneChip consists of an array of hundreds of thousands of probes (each a sequence of 25 bases) with the probe values being used to infer the extent to which genes are expressed in the biological material under investigation. In this article, we demonstrate that these probe values are also strongly influenced by their precise base sequence. We use data from >28 000 CEL files relating to 10 different Affymetrix GeneChip platforms and involving nearly 1000 experiments. Our results confirm known effects (those due to the T7-primer and the formation of G-quadruplexes) but reveal other effects. We show that there can be huge variations from one experiment to another, and that there may also be sizeable disparities between batches within an experiment and between CEL files within a batch.

| S-EPMC3479185 | biostudies-literature

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