Ontology highlight
ABSTRACT:
PROVIDER: PRJEB26397 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:The purpose of this work was to describe a computational and analytical methodology for profiling small RNA by high-throughput sequencing. The datasets here were used to assess the reproducibility of small RNA datasets produced using Illumina sequencing-by-synthesis technology (SBS). We analyzed the reproducibility of small RNA SBS datasets by comparing libraries generated for biological replicates (rep1 and rep2) and technical replicates (rep2 and rep3).
2009-06-02 | E-GEOD-14694 | biostudies-arrayexpress
Project description:To facilitate collaborative research efforts between multi-investigator teams using DNA microarrays, we identified sources of error and data variability between laboratories and across microarray platforms and methods to accommodate this variability. RNA expression data were generated in seven laboratories, comparing two standard RNA samples using twelve microarray platforms. At least two standard microarray types (one spotted, one commercial) were used by all laboratories. Reproducibility for most platforms within any laboratory was typically good, but reproducibility between platforms and across laboratories was generally poor. Reproducibility between laboratories dramatically increased when standardized protocols were implemented for RNA labeling, hybridization, microarray processing, data acquisition and data normalization. Nonetheless, concordance could be found across different laboratories and platforms when data were analyzed in terms of enriched Gene Ontology categories. These findings indicate that microarray results generated by multiple sites and platforms can be comparable, and that multi-investigator teams will maximize data comparability by adopting a common platform and a common set of procedures to generate compatible data. Keywords: other
2005-04-21 | GSE2458 | GEO
Project description:Recovery of biological information under heterogeneous experimental conditions using subgroup standardization.
| PRJNA102963 | ENA
Project description:<p>Next generation sequencing has aided characterization of genomic variation. While whole genome sequencing may capture all possible mutations, whole exome sequencing is more cost-effective and captures most phenotype-altering mutations. Initial strategies for exome enrichment utilized a hybridization-based capture approach. Recently, amplicon-based methods were designed to simplify preparation and utilize smaller DNA inputs. We appraised two hybridization capture-based and two amplicon-based whole exome sequencing methods, utilizing both Illumina and Ion Torrent sequencers, comparing on-target alignment, uniformity, and variant calling. While the amplicon methods had higher on-target rates, the hybridization capture-based approaches showed better uniformity. All methods identified many of the same single nucleotide variants, but each amplicon-based method missed variants detected by the other three methods and reported additional variants discordant with all three other technologies. Many of these potential false positives or negatives appear to result from limited coverage, low variant frequency, vicinity to read starts/ends, or the need for platform-specific variant calling algorithms. All methods demonstrated effective copy number variant calling when compared against a single nucleotide polymorphism array. This study illustrates some differences between various whole exome sequencing approaches, highlights the need for selecting appropriate variant calling based on capture method, and will aid laboratories in selecting their preferred approach.</p>
| phs000938 | dbGaP
Project description:High Reproducibility Using Sodium Hydroxide Stripped Long Oligonucleotide DNA Microarrays
| PRJNA90643 | ENA