PQN and DQN: algorithms for expression microarrays

An ideal expression algorithm should be able to tell truly different expression levels with small false positive errors and be robust to assay changes. We propose two algorithms. PQN is the non-central trimmed mean of perfect match intensities with quantile normalization. DQN is the non-central trimmed mean of differences between perfect match and mismatch intensities with quantile normalization. The quantiles for normalization can be either empirical or theoretical. When array types and/or assay change in a study, the normalization to common quantiles at the probe set level is essential. We compared DQN, PQN, RMA, GCRMA, DCHIP, PLIER and MAS5 for the Affymetrix Latin square data and our data of two sets of experiments using the same bone marrow but different types of microarrays and different assay. We found the computation for AUC of ROC at affycomp.biostat.jhsph.edu can be improved.     

A concentration-dependent analysis method for high density protein microarrays

Protein microarray technology is rapidly growing and has the potential to accelerate the discovery of targets of serum antibody responses in cancer, autoimmunity and infectious disease. Analytical tools for interpreting this high-throughput array data, however, are not well-established. We developed a concentration-dependent analysis (CDA) method which normalizes protein microarray data based on the concentration of spotted probes. We show that this analysis samples a data space that is complementary to other commonly employed analyses, and demonstrate experimental validation of 92% of hits identified by the intersection of CDA with other tools. These data support the use of CDA either as a preprocessing step for a more complete proteomic microarray data analysis or as a stand-alone analysis method.     

The utility of MAS5 expression summary and detection call algorithms

Background  

Used alone, the MAS5.0 algorithm for generating expression summaries has been criticized for high False Positive rates resulting from exaggerated variance at low intensities.     

Profiling microRNA expression with microarrays

The discovery of several types of small RNAs (sRNAs) has led to a steady increase in available RNA databases. Many of these sRNAs remain to be validated and functionally characterized. Recent advances in microRNA (miRNA)-expression profiling of different tissues, stages of development and physiological or pathological states are beginning to be explored using several technological approaches. In this review, these recent advances in miRNA microarray technology and their applications, particularly in basic research and clinical diagnosis, will be summarized and discussed. The methods for miRNA enrichment and probe design and labeling will also be discussed with an emphasis on evaluation of predicted miRNA sequences, analysis of miRNA expression and exploration of the potential roles of miRNA sequences in the regulation of stem cell differentiation and tissue- and time-specific profiling patterns of their target genes.     

Gene expression profiles of vitrified in vivo derived 8-cell stage mouse embryos detected by high density oligonucleotide microarrays

Very little is known about the effect of vitrification on gene functions after warming. The goals of our study were to compare the gene expression patterns, and identify those most affected. For this, 8-cell stage embryos were collected from ICR mice and vitrified with solid surface vitrification technique, while maintaining equal numbers of embryos as control. Total RNAs were extracted and two rounds of amplification were employed. Finally three micrograms of contrasting RNA samples were hybridized on the Agilent Mouse 22 K oligonucleotide slides and the results were analyzed with subsequent verification by independent real-time PCR analyses. The two rounds of amplification with 5 ng tRNA input have yielded 15-16 microg of cRNA. The analyses of repeated hybridizations showed 20,183 genes/ESTs as common signatures, and unsupervised analysis identified 628 differentially expressed (P < 0.01) genes. However, with at least 1.5-fold change considerations, 183 genes were differentially expressed (P < 0.01) out of which 107 were upregulated. The independent analysis with real-time PCR and unamplified samples fully confirmed the results of microarray, indicating the linearity of amplification. Furthermore, this novel gene expression study for vitrified embryos identified many new candidate genes with overrepresentation in some important biological processes. Thus, it is possible to conclude that the expression pattern reflected a broad spectrum of consequences of vitrification on embryos, with most effects on metabolism, regulatory role and stress response genes and allowed the identification of new candidate marker genes for cryosurvival.     

Genome analysis with gene expression microarrays

Advances in biochemistry, chemistry and engineering have enabled the development of a new gene expression assay. This ‘chip-based’ approach utilizes microscopic arrays of cDNAs printed on glass as high-density hybridization targets. Fluorescent probe mixtures derived from total cellular messenger RNA (mRNA) hybridize to cognate elements on the array, allowing accurate measurement of the expression of the corresponding genes. Array densities of >1,000 cDNAs per cm² enable quantitative expression monitoring of a large number of genes in a single hybridization. A two-color fluorescence detection scheme allows rapid and simultaneous differential expression analysis of independent biological samples. Mass-produced microarrays provide a new tool for genome expression analysis that may revolutionize genetic dissection, drug discovery and human disease diagnostics.     

Ultrahigh density microarrays of solid samples

We present a sectioning and bonding technology to make ultrahigh density microarrays of solid samples, cutting edge matrix assembly (CEMA). Maximized array density is achieved by a scaffold-free, self-supporting construction with rectangular array features that are incrementally scalable. This platform technology facilitates arrays of >10,000 tissue features on a standard glass slide, inclusion of unique sample identifiers for improved manual or automated tracking, and oriented arraying of stratified or polarized samples.     

Fabrication of high quality microarrays

Fabrication of DNA microarray demands that between ten (diagnostic microarrays) and many hundred thousands of probes (research or screening microarrays) are efficiently immobilised to a glass or plastic surface using a suitable chemistry. DNA microarray performance is measured by parameters like array geometry, spot density, spot characteristics (morphology, probe density and hybridised density), background, specificity and sensitivity. At least 13 factors affect these parameters and factors affecting fabrication of microarrays are used in this review to compare different fabrication methods (spotted microarrays and in situ synthesis of microarrays) and immobilisation chemistries.     

Meta-analysis of gene expression microarrays with missing replicates

Background  

Many different microarray experiments are publicly available today. It is natural to ask whether different experiments for the same phenotypic conditions can be combined using meta-analysis, in order to increase the overall sample size. However, some genes are not measured in all experiments, hence they cannot be included or their statistical significance cannot be appropriately estimated in traditional meta-analysis. Nonetheless, these genes, which we refer to as incomplete genes, may also be informative and useful.     

Photonic immobilization of BSA for nanobiomedical applications: creation of high density microarrays and superparamagnetic bioconjugates

Light assisted molecular immobilization has been used for the first time to engineer covalent bioconjugates of superparamagnetic nanoparticles and proteins. The technology involves disulfide bridge disruption upon UV excitation of nearby aromatic residues. The close spatial proximity of aromatic residues and disulfide bridges is a conserved structural feature in proteins. The created thiol groups bind thiol reactive surfaces leading to oriented covalent protein immobilization. We have immobilized a model carrier protein, bovine serum albumin, onto Fe(3)O(4)@Au core-shell nanoparticles as well as arrayed it onto optically flat thiol reactive surfaces. This new immobilization technology allows for ultra high dense packing of different bio-molecules on a surface, allowing the creation of multi-potent functionalized active new biosensor materials, biomarkers identification and the development of nanoparticles based novel drug delivery system.     

Indirect measurements of differential gene expression with cDNA microarrays

The use of universal RNA reference sets is an increasingly common approach to molecular classification studies with cDNA microarrays. Here we evaluated the reliability of indirect measurements of fluorescence ratios with a common RNA reference as a means of identifying differentially expressed genes. Comparisons of direct and indirect measures of differential gene expression showed a strong overall correlation in fluorescence ratio measurements but also a high degree of false positives in our indirect measurements. These results indicated that the application of more stringent ratio filters may be required when assessing differential gene expression utilizing a common RNA reference in classification studies.     

Comparative analysis of algorithms for signal quantitation from oligonucleotide microarrays

MOTIVATION: Recent years' exponential increase in DNA microarrays experiments has motivated the development of many signal quantitation (SQ) algorithms. These algorithms perform various transformations on the actual measurements aimed to enable researchers to compare readings of different genes quantitatively within one experiment and across separate experiments. However, it is relatively unclear whether there is a 'best' algorithm to quantitate microarray data. The ability to compare and assess such algorithms is crucial for any downstream analysis. In this work, we suggest a methodology for comparing different signal quantitation algorithms for gene expression data. Our aim is to enable researchers to compare the effect of different SQ algorithms on the specific dataset they are dealing with. We combine two kinds of tests to assess the effect of an SQ algorithm in terms of signal to noise ratio. To assess noise, we exploit redundancy within the experimental dataset to test the variability of a given SQ algorithm output. For the effect of the SQ on the signal we evaluate the overabundance of differentially expressed genes using various statistical significance tests. RESULTS: We demonstrate our analysis approach with three SQ algorithms for oligonucleotide microarrays. We compare the results of using the dChip software and the RMAExpress software to the ones obtained by using the standard Affymetrix MAS5 on a dataset containing pairs of repeated hybridizations. Our analysis suggests that dChip is more robust and stable than the MAS5 tools for about 60% of the genes while RMAExpress is able to achieve an even greater improvement in terms of signal to noise, for more than 95% of the genes.     

AccuTyping: new algorithms for automated analysis of data from high-throughput genotyping with oligonucleotide microarrays

Microarray-based analysis of single nucleotide polymorphisms (SNPs) has many applications in large-scale genetic studies. To minimize the influence of experimental variation, microarray data usually need to be processed in different aspects including background subtraction, normalization and low-signal filtering before genotype determination. Although many algorithms are sophisticated for these purposes, biases are still present. In the present paper, new algorithms for SNP microarray data analysis and the software, AccuTyping, developed based on these algorithms are described. The algorithms take advantage of a large number of SNPs included in each assay, and the fact that the top and bottom 20% of SNPs can be safely treated as homozygous after sorting based on their ratios between the signal intensities. These SNPs are then used as controls for color channel normalization and background subtraction. Genotype calls are made based on the logarithms of signal intensity ratios using two cutoff values, which were determined after training the program with a dataset of approximately 160,000 genotypes and validated by non-microarray methods. AccuTyping was used to determine >300,000 genotypes of DNA and sperm samples. The accuracy was shown to be >99%. AccuTyping can be downloaded from http://www2.umdnj.edu/lilabweb/publications/AccuTyping.html.     

A fluorescent amino acid probe to monitor efficiency of peptide conjugation to glass surfaces for high density microarrays

Using a fluorescent NBD amino acid, new protease substrates were developed that are attractive because of the excellent chemical stability and long wavelength of excitation (480 nm) of the NBD fluorophore. The fluorescent peptides are synthesized by Fmoc solid-phase peptide synthesis. An example peptide was efficiently immobilized onto a microarray surface using click chemistry, and its proteolysis was monitored by fluorescence imaging. Excellent site specificity was achieved for the protease. Fluorescent peptides are also used to monitor the conjugation efficiency onto a surface using a standard microarray scanner.