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PubMed2002

An adaptive meta-clustering approach: combining the information from different clustering results.

With the development of microarray techniques, there is an increasing need of information processing methods to analyze the high throughput data. Clustering is one of the most promising candidates because of its simplicity, flexibility and robustness. However, there is no "perfect" clustering approach outperforming its counterparts, and it is hard to evaluate and combine the results from different techniques, especially in a field without much prior knowledge, such as bioinformatics. This paper proposes a meta-clustering approach to extract the information from results of different clustering techniques, so that a better interpretation of the data distribution can be obtained. A special distance measure is defined to represent the statistical "signal" of each cluster produced by various clustering techniques. The algorithm is applied on both artificial and real data Simulations show that the proposed approach is able to extract the information efficiently and accurately from the input clustering structure.

Algorithms↗
PubMed2006

Gene expression patterns in gastric cancer.

OBJECTIVE: To identify gene expression patterns in distinct stages of intestinal-type gastric cancer(GC). METHODS: Gene expression patterns of distinct stages of intestinal-type GC samples from 3 patients were compared with cDNA microarray, which contained 576 genes. There were 506 target genes, which included 51 genes identified from our previous experiment with suppression subtractive hybridization(SSH) and other 455 genes chosen for their important roles in cancers. Hierarchical clustering was performed to clarify genes in association with distinct stages of GC. RESULTS: One hundred and eighty-one differentially expressed genes with average Cy5:Cy3 ratios higher than 2.0 or lower than 0.5 in at least one stage of GC were identified by cDNA microarray. Among them, 48 genes were up-regulated and 133 down-regulated. Hierarchical clustering analysis separated the differentially expressed genes in different stages of GC into 5 main characteristic groups. Some important differentially expressed genes in different stages of GC were identified, such as SEC23IP, LIPF, ES(BQ291520), SLC5A1, PG(encoding similar to pepsin A precursor), CXCR4, DICER1, SH3GL2, and IGF2R. CONCLUSION: The differentially expressed gene patterns and some important genes were identified, which might be useful in further study on carcinogenesis, progression and metastasis of intestinal-type GC.

DNA, Neoplasm↗
PubMed2006

SemBiosphere: a semantic web approach to recommending microarray clustering services.

Clustering is a popular method for analyzing microarray data. Given the large number of clustering algorithms being available, it is difficult to identify the most suitable ones for a particular task. It is also difficult to locate, download, install and run the algorithms. This paper describes a matchmaking system, SemBiosphere, which solves both problems. It recommends clustering algorithms based on some minimal user requirement inputs and the data properties. An ontology was developed in OWL, an expressive ontological language, for describing what the algorithms are and how they perform, in addition to how they can be invoked. This allows machines to "understand" the algorithms and make the recommendations. The algorithm can be implemented by different groups and in different languages, and run on different platforms at geographically distributed sites. Through the use of XML-based web services, they can all be invoked in the same standard way. The current clustering services were transformed from the non-semantic web services of the Biosphere system, which includes a variety of algorithms that have been applied to microarray gene expression data analysis. New algorithms can be incorporated into the system without too much effort. The SemBiosphere system and the complete clustering ontology can be accessed at http://yeasthub2.gersteinlab. org/sembiosphere/.

Algorithms↗
PubMed2006

ABCA12 is the major harlequin ichthyosis gene.

Harlequin ichthyosis (HI) is the most severe form of autosomal-recessive, congenital ichthyosis. Affected infants have markedly impaired barrier function and are more susceptible to infection. Abnormalities in the localization of epidermal lipids as well as abnormal lamellar granule formation are features of HI skin. Previously, we and others have shown that mutations in the ABCA12 gene encoding an adenosine triphosphate-binding cassette (ABC) transporter underlie the skin disease HI. In this study, we have sequenced the ABCA12 gene in an additional 14 patients and show that all contain mutations, with the majority being either nonsense substitution or frameshift mutations. Eleven HI patients had bi-allelic ABCA12 mutations, whereas in the remaining three HI patients in this study, ABCA12 mutations were detected on only one allele by sequencing. In addition, the one patient from the previous study where no sequence mutations were detected was screened for heterozygous deletions. A combination of oligonucleotide arrays, multiplex PCR analysis and single-nucleotide polymorphism genotyping revealed a heterozygous intragenic deletion in exon 8. These mutation data establish ABCA12 as the major HI gene.

ATP-Binding Cassette Transporters↗
PubMed2005

Differentiation of important and closely related cereal plant species (Poaceae) in food by hybridization to an oligonucleotide array.

We report the development of an oligonucleotide microarray for the simultaneous detection of six important cereal food plant species from the Poaceae based on the chloroplast trnL intron sequence. We used universal primers to amplify the trnL intron from wheat, rye, barley, oat, rice, and maize, followed by a cyclic labeling of oligonucleotides probes and subsequent hybridization to an oligonucleotide microarray. In single taxon analyses, positive signals were produced with a high signal-to-noise ratio. The assay also enabled the analysis of mixed samples. The results obtained for real food samples were in agreement with the ingredient labels, but positive results for grains not declared on the ingredients list were observed in three out of 10 samples, which indicates that the final products and/or the declared ingredients were probably botanically impure or contaminated. The combination of the sensitivity of a universal polymerase chain reaction with the specificity of the labeling reaction allows this protocol to be applied in routine analyses of food samples, as demonstrated by successful analysis of processed composite food products.

DNA, Plant↗
PubMed2004

Multipathogen oligonucleotide microarray for environmental and biodefense applications.

Food-borne pathogens are a major health problem. The large and diverse number of microbial pathogens and their virulence factors has fueled interest in technologies capable of detecting multiple pathogens and multiple virulence factors simultaneously. Some of these pathogens and their toxins have potential use as bioweapons. DNA microarray technology allows the simultaneous analysis of thousands of sequences of DNA in a relatively short time, making it appropriate for biodefense and for public health uses. This paper describes methods for using DNA microarrays to detect and analyze microbial pathogens. The FDA-1 microarray was developed for the simultaneous detection of several food-borne pathogens and their virulence factors including Listeria spp., Campylobacter spp., Staphylococcus aureus enterotoxin genes and Clostridium perfringens toxin genes. Three elements were incorporated to increase confidence in the microarray detection system: redundancy of genes, redundancy of oligonucleotide probes (oligoprobes) for a specific gene, and quality control oligoprobes to monitor array spotting and target DNA hybridization. These elements enhance the reliability of detection and reduce the chance of erroneous results due to the genetic variability of microbes or technical problems with the microarray. The results presented demonstrate the potential of oligonucleotide microarrays for detection of environmental and biodefense relevant microbial pathogens.

Bacteria↗
PubMed2004

The effect of normalization on microarray data analysis.

This paper contains a description of several common normalization methods used in microarray analysis, and compares the effect of these methods on microarray data. The importance of background subtraction is also addressed. The research focuses on three parts. The first uses three statistical methods: t-test, Wilcoxon signed rank test, and sign test to measure the difference between background subtracted data and nonbackground subtracted data. The second part of the study uses the same three statistical methods to compare whether data normalized with different normalization methods yield similar results. The third part of the study focuses on whether these differently normalized data will influence the result of gene selection (dimension reduction). The comparisons are done for several data sets to help identify similarity patterns. The conclusion of this study is that background subtraction can make a difference, especially for some data sets with poorer quality data. The choice of normalization method, for the most part, makes little difference in the sense that the methods produce similarly normalized data. But, based on the third part of analysis, we found that when gene selection is performed on these differently normalized data, somewhat different gene sets are obtained. Thus, the choice of normalization method will likely have some effect on the final analysis.

Oligonucleotide Array Sequence Analysis↗
PubMed2000

Analysis of mutations in oral poliovirus vaccine by hybridization with generic oligonucleotide microchips.

This paper describes use of a new technology of hybridization with a micro-array of immobilized oligonucleotides for detection and quantification of neurovirulent mutants in Oral Poliovirus Vaccine (OPV). We used a micro-array consisting of three-dimensional gel-elements containing all possible hexamers (total of 4096 probes). Hybridization of fluorescently labelled viral cDNA samples with such microchips resulted in a pattern of spots that was registered and quantified by a computer-linked CCD camera, so that the sequence of the original cDNA could be deduced. The method could reliably identify single point mutations, since each of them affected fluorescence intensity of 12 micro-array elements. Micro-array hybridization of DNA mixtures with varying contents of point mutants demonstrated that the method can detect as little as 10% of revertants in a population of vaccine virus. This new technology should be useful for quality control of live viral vaccines, as well as for other applications requiring identification and quantification of point mutations.

DNA Mutational Analysis↗
PubMed2002

Genesis: cluster analysis of microarray data.

A versatile, platform independent and easy to use Java suite for large-scale gene expression analysis was developed. Genesis integrates various tools for microarray data analysis such as filters, normalization and visualization tools, distance measures as well as common clustering algorithms including hierarchical clustering, self-organizing maps, k-means, principal component analysis, and support vector machines. The results of the clustering are transparent across all implemented methods and enable the analysis of the outcome of different algorithms and parameters. Additionally, mapping of gene expression data onto chromosomal sequences was implemented to enhance promoter analysis and investigation of transcriptional control mechanisms.

Algorithms↗
PubMed2003

INCLUSive: A web portal and service registry for microarray and regulatory sequence analysis.

INCLUSive is a suite of algorithms and tools for the analysis of gene expression data and the discovery of cis-regulatory sequence elements. The tools allow normalization, filtering and clustering of microarray data, functional scoring of gene clusters, sequence retrieval, and detection of known and unknown regulatory elements using probabilistic sequence models and Gibbs sampling. All tools are available via different web pages and as web services. The web pages are connected and integrated to reflect a methodology and facilitate complex analysis using different tools. The web services can be invoked using standard SOAP messaging. Example clients are available for download to invoke the services from a remote computer or to be integrated with other applications. All services are catalogued and described in a web service registry. The INCLUSive web portal is available for academic purposes at http://www.esat.kuleuven.ac.be/inclusive.

Algorithms↗
PubMed2006

Multiple detection of food-borne pathogenic bacteria using a novel 16S rDNA-based oligonucleotide signature chip.

There have been many attempts to develop sensitive and accurate techniques for the detection and diagnosis of pathogenic bacteria using nucleic acid-based technology. To achieve efficient multiple detection of seven selected food-borne pathogens, we assessed the respective 16S rDNA pathogen specific sequences using an oligonucleotide-based signature array. Strategic optimal design of specific capture probes was achieved by using the characteristic first variable region. To assess the specificity of this pathogen detection system, we employed a two-step experimental strategy. Under conditions established through experiments with chemically synthesized model targets comprising both conserved and variable regions of 16S rDNA, we confirmed the validity of this system using real 16S rDNA targets. Detection with real targets was successfully performed using our system, and better specificity was obtained compared to experiments with model targets. Moreover, the subtypes of Vibrio pathogens were successfully classified. We developed a two-dimensional visualization plot tool for positive control and specific spots, which allowed facile and minute differentiation between spot intensities. Repeated array formats were employed to ensure experimental uniformity, and included the statistical p-value criterion for pathogen discrimination. The present results thus indicate that our novel oligonucleotide-based signature chip detection system can be employed for the effective detection of multiple pathogens.

Bacteria↗
PubMed2025

Detection of copy number variations by chromosomal microarray analysis in disorders of sex development of unexplained molecular etiology and association with clinical findings.

PURPOSE: Despite advances in genetic diagnostics, the molecular cause of a significant proportion of DSDs remains unknown. The aim of this study was to identify copy number variations (CNVs) using chromosomal microarray analysis (CMA) technology in DSD patients with previously undetected molecular genetic etiology and to investigate their phenotypic associations with these variations. METHODS: This study included DSD cases without chromosomal abnormalities and without any variants detected by sequence analysis methods, including whole-exome sequencing analysis. We evaluated variant pathogenicity according to the American College of Medical Genetics and Genomics guidelines and recorded the phenotypic findings of the cases. All pathogenic variants were subjected to segregation analysis. RESULTS: Of the 20 patients included in the study, 16 (80%) were classified as 46,XY DSD and 4 (20%) as 46,XX DSD. Initial clinical diagnoses in this 46,XX DSD group included gonadal dysgenesis in two patients (50%) and androgen excess in the remaining two (50%). Among the 46,XY DSD patients, five patients (31.25%) were presumed to be androgen insensitive, nine (56.25%) were diagnosed with defects in androgen biosynthesis, and two (12.5%) had gonadal dysgenesis. CMA detected 38 CNVs in 16 patients (80%), comprising 12 deletions (31.6%) and 26 duplications (68.4%). Three pathogenic CNVs were detected in 3 patients (15%), whereas 27 variants of uncertain significance were identified in 13 patients (65%). CONCLUSION: In selected cases, the diagnostic approach should incorporate CMA to elucidate the molecular etiology of DSD. Furthermore, CMA may prove to be an invaluable tool in the search for new genes responsible for DSD.

Humans↗
PubMed2001

Population variation of human mitochondrial DNA hypervariable regions I and II in 105 Croatian individuals demonstrated by immobilized sequence-specific oligonucleotide probe analysis.

AIM: To detect sequence variation in 105 Croatian individuals by the use of duplex polymerase chain reaction amplification of full-length hypervariable region I and II (HVI/HVII) products and subsequent hybridization to a linear array of 27 immobilized sequence-specific oligonucleotide (SSO) probes, which targets six regions within HVI and HVII, and two additional sites, 189 and 16093. METHODS: Chelex-extracted bloodstains were used for amplification of HV regions. In all cases, a single robust amplification was sufficient for immobilized SSO probe typing and subsequent direct sequence analysis for both HVI and HVII. This method, suitable for a range of forensic samples (including shaft portions of single hairs), was also applied to the analysis of 18 skeletal elements recovered from a mass grave. Using a panel of immobilized SSO probes, we have developed a rapid screening approach to mitochondrial DNA (mtDNA) haplotyping before direct sequence analysis. RESULTS: We established a reference sequence database of mtDNA haplotypes for 105 randomly selected Croatian individuals. Fifty different mitotypes were observed (33 unique). The most frequent mitotypes occurred 18 times or approximately 17.1% [111111 189 (A) 16093 (T)] and 11 times or approximately 10.5% [131111 189 (A) 16093 (T)]; all other mitotypes occurred 5% or less. The corresponding genetic diversity value for this database was approximately 0.952. The usefulness of establishing an mtDNA reference database with immobilized SSO probe testing has been demonstrated by determining the strength of a match comparison obtained for one skeletal element and a corresponding maternal reference from 18 specimens recovered from a mass grave. CONCLUSION: The sequence variation detected by the panel of immobilized SSO probes is sufficiently diverse to be used for identification of human skeletal remains from mass graves. The immobilized SSO typing strip targets polymorphic regions within HVI and HVII and is a useful identification tool for mass grave and mass disaster analysis, as well as for criminal casework testing.

Base Sequence↗
PubMed2005

Rapid detection of deletional alpha-thalassemia by an oligonucleotide microarray.

A simple, fast, and highly reproducible protocol for detection of the three most common deletional alpha-thalassemias (- -SEA, - alpha3.7, -alpha4.2) using an oligonucleotide microarray was developed. PCR products were directly hybridized to the microarrays with different deletion-specific probes. Genotypes were determined by quantitative analysis of the fluorescent signals detected by fluorescence scanning. Blind assays on 400 samples validated the efficiency and specificity of the protocol. This method may be suitable for routine clinical use and population screening for deletional alpha-thalassemia.

DNA Mutational Analysis↗
PubMed2006

Identifying differentially expressed genes in meta-analysis via Bayesian model-based clustering.

A Bayesian model-based clustering approach is proposed for identifying differentially expressed genes in meta-analysis. A Bayesian hierarchical model is used as a scientific tool for combining information from different studies, and a mixture prior is used to separate differentially expressed genes from non-differentially expressed genes. Posterior estimation of the parameters and missing observations are done by using a simple Markov chain Monte Carlo method. From the estimated mixture model, useful measure of significance of a test such as the Bayesian false discovery rate (FDR), the local FDR (Efron et al., 2001), and the integration-driven discovery rate (IDR; Choi et al., 2003) can be easily computed. The model-based approach is also compared with commonly used permutation methods, and it is shown that the model-based approach is superior to the permutation methods when there are excessive under-expressed genes compared to over-expressed genes or vice versa. The proposed method is applied to four publicly available prostate cancer gene expression data sets and simulated data sets.

Algorithms↗
PubMed2006

Oligonucleotide-arrayed TFT photosensor applicable for DNA chip technology.

A thin film transistor (TFT) photosensor fabricated by semiconductor integrated circuit (IC) technology was applied to DNA chip technology. The surface of the TFT photosensor was coated with TiO2 using a vapor deposition technique for the fabrication of optical filters. The immobilization of thiolated oligonucleotide probes onto a TiO2-coated TFT photosensor using gamma-aminopropyltriethoxysilane (APTES) and N-(gamma-maleimidobutyloxy) sulfosuccinimide ester (GMBS) was optimized. The coverage value of immobilized oligonucleotides reached a plateau at 33.7 pmol/cm2, which was similar to a previous analysis using radioisotope-labeled oligonucleotides. The lowest detection limits were 0.05 pmol/cm2 for quantum dot and 2.1 pmol/cm2 for Alexa Fluor 350. Furthermore, single nucleotide polymorphism (SNP) detection was examined using the oligonucleotide-arrayed TFT photosensor. A SNP present in the aldehyde dehydrogenase 2 (ALDH2) gene was used as a target. The SNPs in ALDH2*1 and ALDH2*2 target DNA were detected successfully using the TFT photosensor. DNA hybridization in the presence of both ALDH2*1 and ALDH2*2 target DNA was observed using both ALDH2*1 and ALDH2*2 detection oligonucleotides-arrayed TFT photosensor. Use of the TFT photosensor will allow the development of a disposable photodetecting device for DNA chip systems.

Biosensing Techniques↗