Optimization and Clinical Validation of a Pathogen Detection Microarray
Ontology highlight
ABSTRACT:
OTHER RELATED OMICS DATASETS IN: GSE7779
PROVIDER: PRJNA99799 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:This series includes microarrays from 36 patient samples and 2 cell-culture controls, used to optimize and validate the pathogen detection microarray (Wong, et. al. 2007) Keywords: viral pathogen detection
2007-05-29 | GSE7779 | GEO
Project description:DNA microarrays used as 'genomic sensors' have great potential in clinical diagnostics. Biases inherent in random PCR-amplification, cross-hybridization effects, and inadequate microarray analysis, however, limit detection sensitivity and specificity. Here, we have studied the relationships between viral amplification efficiency, hybridization signal, and target-probe annealing specificity using a customized microarray platform. Novel features of this platform include the development of a robust algorithm that accurately predicts PCR bias during DNA amplification and can be used to improve PCR primer design, as well as a powerful statistical concept for inferring pathogen identity from probe recognition signatures. Compared to real-time PCR, the microarray platform identified pathogens with 94% accuracy (76% sensitivity and 100% specificity) in a panel of 36 patient specimens. Our findings show that microarrays can be used for the robust and accurate diagnosis of pathogens, and further substantiate the use of microarray technology in clinical diagnostics.
| S-EPMC1929155 | biostudies-literature
Project description:DNA microarray for STD pathogen detection
| PRJNA285757 | ENA
Project description:In order to evaluate the performance of CNV detection in next-generation sequencing platform in varied sample types, we employed chromosomal microarray analysis (CMA) for validation of the samples with NGS-based detection results (NCBI Sequence Read Archive with accession number SRA296708). Besides array Comparative Genomics Hybridization (aCGH, Agilent) , we used a commerical SNP-array (Illumina) including early abortus, induced termination, prenatal samples and postnatal samples. CMA results were compared with NGS-based detection results. 100% consistency was obtained between NGS-based approach and CMA in pathogenic or likely pathogenic CNVs detection.
2015-10-01 | GSE73190 | GEO
Project description:This SuperSeries is composed of the following subset Series: GSE24626: Validation data for Lawrence Livermore Microbial Detection Array version 2 GSE24699: Validation data for Lawrence Livermore Microbial Detection Array version 1 Refer to individual Series
2010-10-15 | E-GEOD-24700 | biostudies-arrayexpress
Project description:Background: With the growing availability of entire genome sequences, an increasing number of scientists can exploit oligonucleotide microarrays for genome-scale expression studies. While probe-design is a major research area, relatively little work has been reported on the optimization of microarray protocols. Results: As shown in this study, suboptimal conditions can have considerable impact on biologically relevant observations. For example, deviation from the optimal temperature by one degree Celsius lead to a loss of 44% of differentially expressed genes identified. While genes from thousands of Gene Ontology categories were affected, transcription factors and other low-copy-number regulators were disproportionately lost. Calibrated protocols are thus required in order to take full advantage of the large dynamic range of microarrays. For an objective optimization of protocols we introduce an approach that maximizes the amount of information obtained per experiment. A comparison of two typical samples is sufficient for this calibration. We ensure, however, that optimization results are independent of the samples and the specific measures used for calibration. Both simulations and spike-in experiments confirm an unbiased determination of generally optimal experimental conditions. Conclusions: Well calibrated hybridization conditions are thus easily achieved and necessary for the efficient detection of differential expression. They are essential for the sensitive profiling of low-copy-number molecules. This is particularly critical for studies of transcription factor expression, or the inference and study of regulatory networks. Supporting material, including source code and data, is available at http://bioinf.boku.ac.at/pub/optMA2010/. Optimization of hybridization temperature via an assessment of differential expression between two samples (male vs female Drosophila melanogaster) in 6 technical replicates (3 regular + 3 dye-swaps) for hybridizations at different temperatures (in two batches of 50, 52, 54, and 56; and 47, 49, 50, and 51 degree Celsius, with the repeated hybridization at 50 degree Celsius serving to demonstrate batch-to-batch stability).
2011-11-11 | E-GEOD-25625 | biostudies-arrayexpress
Project description:This work describes the development of the first microarray detection system that simultaneously identifies common pathogens associated with STDs from clinical samples, and paves the way for establishing a time-saving, accurate and high-throughput diagnostic tool.
2015-12-31 | GSE69508 | GEO
Project description:The Blood Borne Pathogen Resequencing Microarray Expanded (BBP-RMAv.2) is a platform that allows multiplex detection and identification of 80 different blood-borne pathogens in one single test, comprising 60 virus, 5 bacteria and 15 parasites. The objective is to evaluate the lowest concentration detected in blood or plasma, species discrimination and applicability of the microarray platform for testing blood donors. Human blood or plasma spiked with selected pathogens (10,000, 1,000 or 100 cells or copies/ml), including 6 viral, 2 bacterial and 5 protozoan pathogens were each tested on this platform. The nucleic acids were extracted, amplified using multiplexed sets of pooled specific primers, fragmented, labeled, and hybridized to a microarray. Finally, the detected sequences were identified using an automated genomic database alignment algorithm. The performance of the BBP-RMAv.2 demonstrated detection for most spiked protozoan pathogens at 1,000 cells/ml, 10,000 cells/ml for bacterial pathogens and as low as 100 copies/ml for viral pathogens. Coded specimens, including spiked and negative controls, were identified correctly for one blood specimen and for two plasma specimens. One negative plasma resulted in a false positive detection of a virus demonstrating the effectiveness of the platform.
2024-06-08 | E-MTAB-13972 | biostudies-arrayexpress
Project description:In order to evaluate the performance of CNV detection in next-generation sequencing platform in varied sample types, we employed chromosomal microarray analysis (CMA) for validation of the samples with NGS-based detection results (NCBI Sequence Read Archive with accession number SRA296708). Besides snp-array, we used a customized array Comparative Genomics Hybridization (aCGH, Agilent) approach for a cohort of clinical samples including early abortus, induced termination, prenatal samples and postnatal samples. CMA results were compared with NGS-based detection results. 100% consistency was obtained between NGS-based approach and CMA in pathogenic or likely pathogenic CNVs detection.
2015-10-01 | GSE72891 | GEO
Project description:Background: With the growing availability of entire genome sequences, an increasing number of scientists can exploit oligonucleotide microarrays for genome-scale expression studies. While probe-design is a major research area, relatively little work has been reported on the optimization of microarray protocols. Results: As shown in this study, suboptimal conditions can have considerable impact on biologically relevant observations. For example, deviation from the optimal temperature by one degree Celsius lead to a loss of 44% of differentially expressed genes identified. While genes from thousands of Gene Ontology categories were affected, transcription factors and other low-copy-number regulators were disproportionately lost. Calibrated protocols are thus required in order to take full advantage of the large dynamic range of microarrays. For an objective optimization of protocols we introduce an approach that maximizes the amount of information obtained per experiment. A comparison of two typical samples is sufficient for this calibration. We ensure, however, that optimization results are independent of the samples and the specific measures used for calibration. Both simulations and spike-in experiments confirm an unbiased determination of generally optimal experimental conditions. Conclusions: Well calibrated hybridization conditions are thus easily achieved and necessary for the efficient detection of differential expression. They are essential for the sensitive profiling of low-copy-number molecules. This is particularly critical for studies of transcription factor expression, or the inference and study of regulatory networks. Supporting material, including source code and data, is available at http://bioinf.boku.ac.at/pub/optMA2010/.
2011-11-11 | GSE25625 | GEO