MetaBridge_sampling_methods
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB87831 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Profiling of mRNA abundances with high-throughput platforms such as microarrays and RNA-Seq has become an important tool in both basic and biomedical research. However these platforms remain prone to systematic errors, and have challenges in clinical and industrial application. As a result it is standard practice to validate a subset of key results using alternate technologies. Similarly, clinical and industrial applications typically involve transitions from high-throughput discovery platform to medium-throughput validation ones. These medium-throughput validation platforms have high technical reproducibility and reduced sample input needs, and low sensitivity to sample-quality (e.g. for processing FFPE specimens). Unfortunately, while medium-throughput platforms have proliferated, there are no comprehensive comparisons of them. Here we present ABI's OpenArray and qPCR systems.
2012-10-18 | GSE41388 | GEO
Project description:We reported a Concanavalin A-based Barcoding Strategy (CASB) for single-cell and single-nucleus sample multiplexing, which could be followed by different single-cell sequencing techniques. The method involves minimal sample processing, thereby preserving intact transcriptomic or epigenomic patterns. Besides sample multiplexing, the CASB could further improve data quality through doublet identification.
2021-03-09 | GSE153115 | GEO
Project description:We reported a Concanavalin A-based Barcoding Strategy (CASB) for single-cell and single-nucleus sample multiplexing, which could be followed by different single-cell sequencing techniques. The method involves minimal sample processing, thereby preserving intact transcriptomic or epigenomic patterns. Besides sample multiplexing, the CASB could further improve data quality through doublet identification.
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Project description:Chromatin immunoprecipitation with high-throughput sequencing (ChIP-seq) is a widely used technique for genome-wide analyses of protein-DNA interactions. This protocol provides a guide to ChIP-seq data processing in Saccharomyces cerevisiae, with a focus on signal normalization to address data biases and enable meaningful comparisons within and between samples. Designed for researchers with minimal bioinformatics experience, it includes practical overviews and refers to scripting examples for key tasks, such as configuring computational environments, trimming and aligning reads, processing alignments, and visualizing signals. This protocol employs the sans-spike-in method for quantitative ChIP-seq (siQ-ChIP) and normalized coverage for absolute and relative comparisons of ChIP-seq data, respectively. While spike-in normalization, which is semiquantitative, is addressed for context, siQ-ChIP and normalized coverage are recommended as mathematically rigorous and reliable alternatives.
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Project description:Six sets of kidney EC and non-EC comparisons and the calculated mean. Keywords: repeat sample
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Project description:Four sets of kidney EC and non-EC comparisons and the calculated mean. Keywords: repeat sample
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Project description:Profiling of mRNA abundances with high-throughput platforms such as microarrays and RNA-Seq has become an important tool in both basic and biomedical research. However these platforms remain prone to systematic errors, and have challenges in clinical and industrial application. As a result it is standard practice to validate a subset of key results using alternate technologies. Similarly, clinical and industrial applications typically involve transitions from high-throughput discovery platform to medium-throughput validation ones. These medium-throughput validation platforms have high technical reproducibility and reduced sample input needs, and low sensitivity to sample-quality (e.g. for processing FFPE specimens). Unfortunately, while medium-throughput platforms have proliferated, there are no comprehensive comparisons of them. Here we fill that gap by comparing two key medium-throughput platforms – NanoString’s nCounter Analysis System and ABI’s OpenArray System – to gold-standard quantitative real-time RT-PCR.
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