Diagnostic performance of the AID Line Probe Assay
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB42600 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:This study is aimed to evaluate the performance of the Micromedic CD24 assay in identifying colorectal adenoma using Western blot and ELISA assays. These assays are designed to detect CD24 protein in peripheral blood leukocytes (PBL). Elevated levels of CD24 may be indicative of colorectal adenoma (inclusive of optically detectable early adenoma to late adenoma, and cancer).
| 2096063 | ecrin-mdr-crc
Project description:The use of data-independent acquisition methods such as SWATH for mass spectrometry based proteomics is usually performed using peptide MS/MS reference ion assay libraries which enable identification and quantitation of peptide peak areas. Reference assay libraries can be generated locally through information dependent acquisition, or obtained from shared data repositories for commonly studied organisms. However, there have been no studies performed to systematically evaluate how locally-generated or repository-based assay libraries affect SWATH performance for proteomic studies. To undertake this analysis we developed a software workflow, SwathXtend, which generates extended peptide assay libraries using a local seed library and delivers statistical analysis of SWATH-based sample comparisons. We designed test samples using peptides from a yeast extract spiked into peptides from human K562 cell lysates at different ratios to simulate common protein abundance change comparisons. SWATH-MS data with 2, 5 and 10% of yeast peptides spiked into the human cell lysate were assessed using several local and repository-based assay libraries of different complexities and proteome compositions. We evaluated detection specificity and accuracy to detect differentially abundant proteins and reporting thresholds for statistical analyses. We demonstrate that extended assay libraries integrated with local seed libraries achieve better performance than local limited assay libraries alone from the aspects of the number of peptides and proteins identified and the specificity to detect differentially abundant proteins; the performance of extended assay libraries heavily depend on the similarity of the seed and add-on libraries; statistical analysis with multiple testing correction can improve the statistical rigor needed when using large, extended assay libraries.
2016-05-12 | PXD002836 | Pride
Project description:Melioidosis, caused by Gram negative bacteria Burkholderia pseudomallei, is a major type of community-acquired septicemia in Southeast Asia and Northern Australia with high mortality and morbidity rate. More accurate and rapid diagnosis is needed for improving the management of septicemic melioidosis. We previously identified 37-gene candidate signature to distinguish septicemic melioidosis from sepsis due to other pathogens. The aims of this current study were to independently validate our previous biomarker and consolidate gene selection from each of our microarray data set for establishing a targeted assay for the differential diagnosis of melioidosis. Blood samples were collected from patients who presented with severe inflammatory response syndromes from 3 provincial hospitals in Northeast of Thailand during September 2009 and November 2011. Only culture-confirmed sepsis were included in the study (n=166). We generated a new microarray dataset comprising of 29 patients with septicemic melioidosis and 54 patients with sepsis due to other pathogens. Validation of the 37-gene signature using this new dataset demonstrated the prediction accuracy of approximately 80% for detecting type of sepsis. In order to develop a nanoliter-scale high throughput PCR technology, we further identified additional gene signature from this new microarray dataset and by revisiting our published data. Altogether 85 genes including 6 housekeeping genes were selected. Using multi-steps iteration approach we could reduce the number of biomarkers to 12 genes while the performance is comparable to that of the full panel. The high performance (accuracy >70%) of this 12-gene signature could be validated in a second independent set of samples. The 12-gene panel identified by our study provides high performance for the differential diagnosis of septicemic melioidosis. This finding will be useful for improving the management of septicemic melioidosis in term of diagnosis, treatment and follow up.
2015-06-04 | GSE69528 | GEO
Project description:Melioidosis, caused by Gram negative bacteria Burkholderia pseudomallei, is a major type of community-acquired septicemia in Southeast Asia and Northern Australia with high mortality and morbidity rate. More accurate and rapid diagnosis is needed for improving the management of septicemic melioidosis. We previously identified 37-gene candidate signature to distinguish septicemic melioidosis from sepsis due to other pathogens. The aims of this current study were to independently validate our previous biomarker and consolidate gene selection from each of our microarray data set for establishing a targeted assay for the differential diagnosis of melioidosis. Blood samples were collected from patients who presented with severe inflammatory response syndromes from 3 provincial hospitals in Northeast of Thailand during September 2009 and November 2011. Only culture-confirmed sepsis were included in the study (n=166). We generated a new microarray dataset comprising of 29 patients with septicemic melioidosis and 54 patients with sepsis due to other pathogens. Validation of the 37-gene signature using this new dataset demonstrated the prediction accuracy of approximately 80% for detecting type of sepsis. In order to develop a nanoliter-scale high throughput PCR technology, we further identified additional gene signature from this new microarray dataset and by revisiting our published data. Altogether 85 genes including 6 housekeeping genes were selected. Using multi-steps iteration approach we could reduce the number of biomarkers to 12 genes while the performance is comparable to that of the full panel. The high performance (accuracy >70%) of this 12-gene signature could be validated in a second independent set of samples. The 12-gene panel identified by our study provides high performance for the differential diagnosis of septicemic melioidosis. This finding will be useful for improving the management of septicemic melioidosis in term of diagnosis, treatment and follow up. Total RNA from whole blood obtained from patients with sepsis caused by B.pseudomallei (n=29) or other pathogens (n=54) and uninfected controls (28 healthy and 27 subjects with type 2 diabetes mellitus) were collected. In order to validate the published signature, microarray data were generated from these samples. This dataset was also used for an independent selection of signature for septicemic melioidosis. The same RNA samples were used for validation by a high throughput real-time PCR technique, Fluidigm.
2015-06-04 | E-GEOD-69528 | biostudies-arrayexpress
Project description:Romanian MDR tuberculosis cohort
| PRJNA616115 | ENA
Project description:<p>The Nex-StoCT and ACMG recommend that validation of an NGS-based diagnostic test include performance test characteristics for assay accuracy, analytical sensitivity and specificity, reproducibility and repeatability. To measure these parameters for the GEDi capture and sequencing test, 4 samples (three randomly selected patient samples and the NA12878 HapMap sample) were prepared and sequenced in triplicate on each of three separate days. We also performed WES and SNP array genotyping analyses of these 4 samples using Agilent V4+UTR whole exome enrichment kit and Illumina Omni 2.5 SNP arrays, respectively.</p>
| phs000798 | dbGaP
Project description:SNP analysis AID-low vs AID-high
2009-07-20 | GSE13612 | GEO
Project description:Affymetrix gene expression AID-GFP-positive vs AID-GFP-negative Experiment Overall Design: Affymetrix gene expression AID-GFP-positive vs AID-GFP-negative
2009-08-22 | E-GEOD-13611 | biostudies-arrayexpress
Project description:Affymetrix gene expression AID-GFP-positive vs AID-GFP-negative
2009-08-15 | GSE13611 | GEO
Project description:Assay Performance Metrics for Low RNA Inputs and Single Cells
2012-02-27 | GSE34363 | GEO