Construction of optimal quality control for oligo arrays

MOTIVATION: Oligo arrays are important experimental tools for the high throughput measurement of gene expression levels. During production of oligo arrays, it is important to identify any faulty manufacturing step. RESULTS: We describe a practical algorithm for the construction of optimal quality control designs that identify any faulty manufacturing step. The algorithm uses hillclimbing, a search technique from combinatorial optimization. We also present the results of using this algorithm on all practical quality control design sizes. AVAILABILITY: On request from the authors.     

Improving DNA array data quality by minimising ‘neighbourhood’ effects

Gene expression studies using cDNA arrays require robust and sensitive detection methods. Being extremely sensitive, radioactive detection suffers from the influence of signals positioned in each other’s vicinity, the ‘neighbourhood’ effect. This limits the gene density of arrays and the quality of the results obtained. We have investigated the quantitative influence of different parameters on the ‘neighbourhood’ effect. By using a model experimental system, we could show that the effect is linear and depends only on the intensity of the hybridisation signal. We identified a common factor that can describe the influence of the neighbour spots based on their intensities. This factor is <1%, but it has to be taken into account if a high dynamic range of gene expression is to be detected. We could also derive the factor, although with less precision, from comparison of duplicate spots on arrays of 4565 different clones and replication of the hybridisation experiments. The calculated coefficient applied to our actual experimental results not only revealed previously undetected tissue or cell-specific expression differences, but also increased the dynamic range of detection. It thus provides a relatively simple way of improving DNA array data quality with few experimental modifications.     

Improving DNA array data quality by minimising 'neighbourhood' effects

Gene expression studies using cDNA arrays require robust and sensitive detection methods. Being extremely sensitive, radioactive detection suffers from the influence of signals positioned in each other's vicinity, the 'neighbourhood' effect. This limits the gene density of arrays and the quality of the results obtained. We have investigated the quantitative influence of different parameters on the 'neighbourhood' effect. By using a model experimental system, we could show that the effect is linear and depends only on the intensity of the hybridisation signal. We identified a common factor that can describe the influence of the neighbour spots based on their intensities. This factor is <1%, but it has to be taken into account if a high dynamic range of gene expression is to be detected. We could also derive the factor, although with less precision, from comparison of duplicate spots on arrays of 4565 different clones and replication of the hybridisation experiments. The calculated coefficient applied to our actual experimental results not only revealed previously undetected tissue or cell-specific expression differences, but also increased the dynamic range of detection. It thus provides a relatively simple way of improving DNA array data quality with few experimental modifications.     

At-TAX: a whole genome tiling array resource for developmental expression analysis and transcript identification in <Emphasis Type="Italic">Arabidopsis thaliana</Emphasis>

Gene expression maps for model organisms, including Arabidopsis thaliana, have typically been created using gene-centric expression arrays. Here, we describe a comprehensive expression atlas, Arabidopsis thaliana Tiling Array Express (At-TAX), which is based on whole-genome tiling arrays. We demonstrate that tiling arrays are accurate tools for gene expression analysis and identified more than 1,000 unannotated transcribed regions. Visualizations of gene expression estimates, transcribed regions, and tiling probe measurements are accessible online at the At-TAX homepage.     

MedMiner: an Internet text-mining tool for biomedical information, with application to gene expression profiling

The trend toward high-throughput techniques in molecular biology and the explosion of online scientific data threaten to overwhelm the ability of researchers to take full advantage of available information. This problem is particularly severe in the rapidly expanding area of gene expression experiments, for example, those carried out with cDNA microarrays or oligonucleotide chips. We present an Internet-based hypertext program, MedMiner, which filters and organizes large amounts of textual and structured information returned from public search engines like GeneCards and PubMed. We demonstrate the value of the approach for the analysis of gene expression data, but MedMiner can also be extended to other areas involving molecular genetic or pharmacological information. More generally still, MedMiner can be used to organize the information returned from any arbitrary PubMed search.     

Evaluation of normalization procedures for oligonucleotide array data based on spiked cRNA controls

Background  

Affymetrix oligonucleotide arrays simultaneously measure the abundances of thousands of mRNAs in biological samples. Comparability of array results is necessary for the creation of large-scale gene expression databases. The standard strategy for normalizing oligonucleotide array readouts has practical drawbacks. We describe alternative normalization procedures for oligonucleotide arrays based on a common pool of known biotin-labeled cRNAs spiked into each hybridization.     

HugeIndex: a database with visualization tools for high-density oligonucleotide array data from normal human tissues

High-density oligonucleotide arrays are a powerful tool for uncovering changes in global gene expression in various disease states. To this end, it is essential to first characterize the variations of gene expression in normal physiological processes. We established the Human Gene Expression (HuGE) Index database (www.HugeIndex.org) to serve as a public repository for gene expression data on normal human tissues using high-density oligonucleotide arrays. This resource currently contains the results of 59 gene expression experiments on 19 human tissues. We provide interactive tools for researchers to query and visualize our data over the Internet. To facilitate data analysis, we cross-reference each gene on the array with its annotation in the LocusLink database at NCBI.     

High throughput gene expression measurement with real time PCR in a microfluidic dynamic array

We describe a high throughput gene expression platform based on microfluidic dynamic arrays. This system allows 2,304 simultaneous real time PCR gene expression measurements in a single chip, while requiring less pipetting than is required to set up a 96 well plate. We show that one can measure the expression of 45 different genes in 18 tissues with replicates in a single chip. The data have excellent concordance with conventional real time PCR and the microfluidic dynamic arrays show better reproducibility than commercial DNA microarrays.     

Visualization of genomic aberrations using Affymetrix SNP arrays

MOTIVATION: DNA copy number aberrations are frequently found in different types of cancer. Recent developments of microarray-based approaches have broadened the knowledge on number and structure of such aberrations. High-density single nucleotide polymorphism (SNP) microarrays provide an extremely high resolution with up to 500,000 SNPs per genome. Owing to the enormous amount of data the detection of common aberrations in large datasets is a great challenge. We describe a novel open source software tool--IdeogramBrowser--which was specifically designed for use with the Affymetrix SNP arrays. It provides an interactive karyotypic visualization of multiple aberration profiles and direct links to GeneCards. Visualization of consensus regions together with gene representation allows the explorative assessment of the data. AVAILABILITY: IdeogramBrowser and its source code are freely available under a creative commons license and can be obtained from http://www.informatik.uni-ulm.de/ni/staff/HKestler/ideo/. IdeogramBrowser is a platform independent Java application.     

Local-pooled-error test for identifying differentially expressed genes with a small number of replicated microarrays

MOTIVATION: In microarray studies gene discovery based on fold-change values is often misleading because error variability for each gene is heterogeneous under different biological conditions and intensity ranges. Several statistical testing methods for differential gene expression have been suggested, but some of these approaches are underpowered and result in high false positive rates because within-gene variance estimates are based on a small number of replicated arrays. RESULTS: We propose to use local-pooled-error (LPE) estimates and robust statistical tests for evaluating significance of each gene's differential expression. Our LPE estimation is based on pooling errors within genes and between replicate arrays for genes in which expression values are similar. We have applied our LPE method to compare gene expression in na?ve and activated CD8+ T-cells. Our results show that the LPE method effectively identifies significant differential-expression patterns with a small number of replicated arrays. AVAILABILITY: The methodology is implemented with S-PLUS and R functions available at http://hesweb1.med.virginia.edu/bioinformatics     

Recovery and evolutionary analysis of complete integron gene cassette arrays from Vibrio

Background  

Integrons are genetic elements capable of the acquisition, rearrangement and expression of genes contained in gene cassettes. Gene cassettes generally consist of a promoterless gene associated with a recombination site known as a 59-base element (59-be). Multiple insertion events can lead to the assembly of large integron-associated cassette arrays. The most striking examples are found in Vibrio, where such cassette arrays are widespread and can range from 30 kb to 150 kb. Besides those found in completely sequenced genomes, no such array has yet been recovered in its entirety. We describe an approach to systematically isolate, sequence and annotate large integron gene cassette arrays from bacterial strains.     

Exon arrays provide accurate assessments of gene expression

We have developed a strategy for estimating gene expression on Affymetrix Exon arrays. The method includes a probe-specific background correction and a probe selection strategy in which a subset of probes with highly correlated intensities across multiple samples are chosen to summarize gene expression. Our results demonstrate that the proposed background model offers improvements over the default Affymetrix background correction and that Exon arrays may provide more accurate measurements of gene expression than traditional 3' arrays.