Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA296350 | ENA |
REPOSITORIES: ENA
Similar Datasets
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:In order to validate of CNV detection from low-coverage whole-genome sequencing in the blood samples from recurrent miscarriage couples, we employed a customized array Comparative Genomics Hybridization (aCGH, Agilent) approach as chromosomal microarray analysis (CMA) in present study for a cohort of 78 DNA samples from blood. CMA results were compared with low-coverage whole-genome sequencing detection results. 100% consistency was obtained in pathogenic or likely pathogenic CNVs detection.
2017-11-01 | GSE83941 | GEO
Project description:RNA extracted at 240min. Samples are rRNA depleted. Expression measurement of Homo sapiens genes.
2019-07-31 | GSE114179 | GEO
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:Chromosomal microarray analysis for validation of the NGS-based CNV detection results in clinical samples
| PRJNA296351 | ENA
Project description:10 Intellectual Disability samples for clinically relevant CNV detection
| PRJNA197143 | ENA
Project description:aCGH CNV detection by CNsolidate for 6,827 DDD probands
| EGAD00001005728 | EGA
Project description: Not available
| S-EPMC2531291 | biostudies-literature
Project description:Background: High-resolution microarray technology is routinely used in basic research and clinical practice to efficiently detect copy number variants (CNVs) across the entire human genome. A new generation of arrays combining high probe densities with optimized designs will comprise essential tools for genome analysis in the coming years. We systematically compared the genome-wide CNV detection power of all 17 available array designs from the Affymetrix, Agilent, and Illumina platforms by hybridizing the well-characterized genome of 1000 Genomes Project subject NA12878 to all arrays, and performing data analysis using both manufacturer-recommended and platform-independent software. We benchmarked the resulting CNV call sets from each array using a gold standard set of CNVs for this genome derived from 1000 Genomes Project whole genome sequencing data. Results: The arrays tested comprise both SNP and aCGH platforms with varying designs and contain between ~0.5 to ~4.6 million probes. Across the arrays CNV detection varied widely in number of CNV calls (4 - 489), CNV size range (~40 bp to ~8 Mbp), and percentage of non-validated CNVs (0 - 86 %). We discovered strikingly strong effects of specific array design principles on performance. For example, some SNP array designs with the largest numbers of probes and extensive exonic coverage produced a considerable number of CNV calls that could not be validated, compared to designs with probe numbers that are sometimes an order of magnitude smaller. This effect was only partially ameliorated using different analysis software and optimizing data analysis parameters. Conclusions: High-resolution microarrays will continue to be used as reliable, cost- and time-efficient tools for CNV analysis. However, different applications tolerate different limitations in CNV detection. Our study quantified how these arrays differ in total number and size range of detected CNVs as well as sensitivity, and determined how each array balances these attributes. This analysis will inform appropriate array selection for future CNV studies, and allow better assessment of the CNV-analytical power of both published and ongoing array-based genomics studies. Furthermore, our findings emphasize the importance of concurrent use of multiple analysis algorithms and independent experimental validation in array-based CNV detection studies. NA12878 hybridization to Affymetrix CytoScan HD array for CNV detection
2017-03-23 | GSE96897 | GEO
Project description: Not available
| S-EPMC4686780 | biostudies-literature