Impact of the spotted microarray preprocessing method on fold-change compression and variance stability

<p>Abstract</p> <p>Background</p> <p>The standard approach for preprocessing spotted microarray data is to subtract the local background intensity from the spot foreground intensity, to perform a log2 transformation and to normalize the data with a global median or a lowess normalization. Although well motivated, standard approaches for background correction and for transformation have been widely criticized because they produce high variance at low intensities. Whereas various alternatives to the standard background correction methods and to log2 transformation were proposed, impacts of both successive preprocessing steps were not compared in an objective way.</p> <p>Results</p> <p>In this study, we assessed the impact of eight preprocessing methods combining four background correction methods and two transformations (the log2 and the glog), by using data from the MAQC study. The current results indicate that most preprocessing methods produce fold-change compression at low intensities. Fold-change compression was minimized using the Standard and the Edwards background correction methods coupled with a log2 transformation. The drawback of both methods is a high variance at low intensities which consequently produced poor estimations of the p-values. On the other hand, effective stabilization of the variance as well as better estimations of the p-values were observed after the glog transformation.</p> <p>Conclusion</p> <p>As both fold-change magnitudes and p-values are important in the context of microarray class comparison studies, we therefore recommend to combine the Edwards correction with a hybrid transformation method that uses the log2 transformation to estimate fold-change magnitudes and the glog transformation to estimate p-values.</p

Quantitative miRNA Expression Analysis Using Fluidigm Microfluidics Dynamic Arrays

MicroRNA (miRNA) is a small non-coding RNA that can regulate gene expression in both plants and animals. Studies showed that miRNAs play a critical role in human cancer by targeting messenger RNAs that are positive or negative regulators of cell proliferation and apoptosis. Here, we evaluated miRNA expression in formalin fixed, paraffin embedded (FFPE) samples and fresh frozen (FF) samples using a high throughput qPCR-based microfluidic dynamic array technology (Fluidigm). We compared the results to hybridization-based microarray platforms using the same samples. We obtained a highly correlated Ct values between multiplex and single-plex RT reactions using standard qPCR assays for miRNA expression. For the same samples, the microfluidic technology (Fluidigm 48.48 dynamic array systems) resulted in a left shift towards lower Ct values compared to those observed by standard TaqMan (ABI 7900HT, mean difference, 3.79). In addition, as little as 10ng total RNA was sufficient to reproducibly detect up to 96 miRNAs at a wide range of expression values using a single 96-multiplexing RT reaction in either FFPE or FF samples. Comparison of miRNAs expression values measured by microfluidic technology with those obtained by other array and Next Generation sequencing platforms showed positive concordance using the same samples but revealed significant differences for a large fraction of miRNA targets. The qPCRarray based microfluidic technology can be used in conjunction with multiplexed RT reactions for miRNA gene expression profiling. This approach is highly reproducible and the results correlate closely with the existing singleplex qPCR platform while achieving much higher throughput at lower sample input and reagent usage. It is a rapid, cost effective, customizable array platform for miRNA expression profiling and validation. However, comparison of miRNA expression using different platforms requires caution and the use of multiple platforms

S-adenosylmethionine (SAM-e) for the treatment of depression in people living with HIV/AIDS

BACKGROUND: This study reports on clinical data from an 8-week open-label study of 20 HIV-seropositive individuals, diagnosed with Major Depressive Disorder (DSM-IV), who were treated with SAM-e (S-Adenosylmethionine). SAM-e may be a treatment alternative for the management of depression in a population reluctant to add another "pill" or another set of related side effects to an already complex highly active antiretroviral therapy (HAART) regimen. METHODS: The Hamilton Rating Scale for Depression (HAM-D) and the Beck Depression Inventory (BDI) were used to assess depressive symptomatology from 1,2,4,6 and 8 weeks after initiation of treatment with SAM-e. RESULTS: Data show a significant acute reduction in depressive symptomatology, as measured by both the HAM-D and the BDI instruments. CONCLUSIONS: SAM-e has a rapid effect evident as soon as week 1 (p < .001), with progressive decreases in depression symptom rating scores throughout the 8 week study

Cross-platform comparability of microarray technology: Intra-platform consistency and appropriate data analysis procedures are essential

BACKGROUND: The acceptance of microarray technology in regulatory decision-making is being challenged by the existence of various platforms and data analysis methods. A recent report (E. Marshall, Science, 306, 630–631, 2004), by extensively citing the study of Tan et al. (Nucleic Acids Res., 31, 5676–5684, 2003), portrays a disturbingly negative picture of the cross-platform comparability, and, hence, the reliability of microarray technology. RESULTS: We reanalyzed Tan's dataset and found that the intra-platform consistency was low, indicating a problem in experimental procedures from which the dataset was generated. Furthermore, by using three gene selection methods (i.e., p-value ranking, fold-change ranking, and Significance Analysis of Microarrays (SAM)) on the same dataset we found that p-value ranking (the method emphasized by Tan et al.) results in much lower cross-platform concordance compared to fold-change ranking or SAM. Therefore, the low cross-platform concordance reported in Tan's study appears to be mainly due to a combination of low intra-platform consistency and a poor choice of data analysis procedures, instead of inherent technical differences among different platforms, as suggested by Tan et al. and Marshall. CONCLUSION: Our results illustrate the importance of establishing calibrated RNA samples and reference datasets to objectively assess the performance of different microarray platforms and the proficiency of individual laboratories as well as the merits of various data analysis procedures. Thus, we are progressively coordinating the MAQC project, a community-wide effort for microarray quality control

Do teashirt family genes specify trunk identity? Insights from the single tiptop/teashirt homolog of Tribolium castaneum

The Drosophila teashirt gene acts in concert with the homeotic selector (Hox) genes to specify trunk (thorax and abdomen) identity. There has been speculation that this trunk-specifying function might be very ancient, dating back to the common ancestor of insects and vertebrates. However, other evidence suggests that the role of teashirt in trunk identity is not well conserved even within the Insecta. To address this issue, we have analyzed the function of Tc-tiotsh, the lone teashirt family member in the red flour beetle, Tribolium castaneum. Although Tc-tiotsh is important for aspects of both embryonic and imaginal development including some trunk features, we find no evidence that it acts as a trunk identity gene. We discuss this finding in the context of recent insights into the evolution and function of the Drosophila teashirt family genes

Evaluating methods for ranking differentially expressed genes applied to microArray quality control data

<p>Abstract</p> <p>Background</p> <p>Statistical methods for ranking differentially expressed genes (DEGs) from gene expression data should be evaluated with regard to high sensitivity, specificity, and reproducibility. In our previous studies, we evaluated eight gene ranking methods applied to only Affymetrix GeneChip data. A more general evaluation that also includes other microarray platforms, such as the Agilent or Illumina systems, is desirable for determining which methods are suitable for each platform and which method has better inter-platform reproducibility.</p> <p>Results</p> <p>We compared the eight gene ranking methods using the MicroArray Quality Control (MAQC) datasets produced by five manufacturers: Affymetrix, Applied Biosystems, Agilent, GE Healthcare, and Illumina. The area under the curve (AUC) was used as a measure for both sensitivity and specificity. Although the highest AUC values can vary with the definition of "true" DEGs, the best methods were, in most cases, either the weighted average difference (WAD), rank products (RP), or intensity-based moderated <it>t </it>statistic (ibmT). The percentages of overlapping genes (POGs) across different test sites were mainly evaluated as a measure for both intra- and inter-platform reproducibility. The POG values for WAD were the highest overall, irrespective of the choice of microarray platform. The high intra- and inter-platform reproducibility of WAD was also observed at a higher biological function level.</p> <p>Conclusion</p> <p>These results for the five microarray platforms were consistent with our previous ones based on 36 real experimental datasets measured using the Affymetrix platform. Thus, recommendations made using the MAQC benchmark data might be universally applicable.</p

The ‘heritagisation’ of the British seaside resort: The rise of the ‘old penny’ arcade.

Amusement arcades have long been a key component of the British seaside resort. For almost a century, they enjoyed popularity and success and became established as a quintessential feature of the British seaside holiday. However, the advent of home-based video games along with recent gambling legislation has led to a decline of the seaside amusement arcade sector. Arcades gained a reputation as unsavoury places and their appearance and fortunes often mirrored those of the resorts in which they were located. However, over the past decade, a new variant of the seaside amusement arcade has appeared, featuring mechanical machines working on pre-decimal currency. Such ‘old penny arcades’ frequently describe themselves as museums or heritage centres and they offer an experience based on a nostalgic affection for the ‘traditional’ seaside holiday. They have appeared in the context of an increasing interest in the heritage of the British seaside resort and constitute one element of the ‘heritagisation’ of such resorts. This paper argues that such arcades can be important elements of strategies to reposition and rebrand resorts for the heritage tourism market

An efficient algorithm for the stochastic simulation of the hybridization of DNA to microarrays

<p>Abstract</p> <p>Background</p> <p>Although oligonucleotide microarray technology is ubiquitous in genomic research, reproducibility and standardization of expression measurements still concern many researchers. Cross-hybridization between microarray probes and non-target ssDNA has been implicated as a primary factor in sensitivity and selectivity loss. Since hybridization is a chemical process, it may be modeled at a population-level using a combination of material balance equations and thermodynamics. However, the hybridization reaction network may be exceptionally large for commercial arrays, which often possess at least one reporter per transcript. Quantification of the kinetics and equilibrium of exceptionally large chemical systems of this type is numerically infeasible with customary approaches.</p> <p>Results</p> <p>In this paper, we present a robust and computationally efficient algorithm for the simulation of hybridization processes underlying microarray assays. Our method may be utilized to identify the extent to which nucleic acid targets (e.g. cDNA) will cross-hybridize with probes, and by extension, characterize probe robustnessusing the information specified by MAGE-TAB. Using this algorithm, we characterize cross-hybridization in a modified commercial microarray assay.</p> <p>Conclusions</p> <p>By integrating stochastic simulation with thermodynamic prediction tools for DNA hybridization, one may robustly and rapidly characterize of the selectivity of a proposed microarray design at the probe and "system" levels. Our code is available at <url>http://www.laurenzi.net</url>.</p

Cross platform microarray analysis for robust identification of differentially expressed genes

<p>Abstract</p> <p>Background</p> <p>Microarrays have been widely used for the analysis of gene expression and several commercial platforms are available. The combined use of multiple platforms can overcome the inherent biases of each approach, and may represent an alternative that is complementary to RT-PCR for identification of the more robust changes in gene expression profiles.</p> <p>In this paper, we combined statistical and functional analysis for the cross platform validation of two oligonucleotide-based technologies, Affymetrix (AFFX) and Applied Biosystems (ABI), and for the identification of differentially expressed genes.</p> <p>Results</p> <p>In this study, we analysed differentially expressed genes after treatment of an ovarian carcinoma cell line with a cell cycle inhibitor. Treated versus control RNA was analysed for expression of 16425 genes represented on both platforms.</p> <p>We assessed reproducibility between replicates for each platform using CAT plots, and we found it high for both, with better scores for AFFX. We then applied integrative correlation analysis to assess reproducibility of gene expression patterns across studies, bypassing the need for normalizing expression measurements across platforms. We identified 930 genes as differentially expressed on AFFX and 908 on ABI, with ~80% common to both platforms. Despite the different absolute values, the range of intensities of the differentially expressed genes detected by each platform was similar. ABI showed a slightly higher dynamic range in FC values, which might be associated with its detection system. 62/66 genes identified as differentially expressed by Microarray were confirmed by RT-PCR.</p> <p>Conclusion</p> <p>In this study we present a cross-platform validation of two oligonucleotide-based technologies, AFFX and ABI. We found good reproducibility between replicates, and showed that both platforms can be used to select differentially expressed genes with substantial agreement. Pathway analysis of the affected functions identified themes well in agreement with those expected for a cell cycle inhibitor, suggesting that this procedure is appropriate to facilitate the identification of biologically relevant signatures associated with compound treatment. The high rate of confirmation found for both common and platform-specific genes suggests that the combination of platforms may overcome biases related to probe design and technical features, thereby accelerating the identification of trustworthy differentially expressed genes.</p