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Summarizing performance for genome scale measurement of miRNA: reference samples and metrics
- Source :
- BMC genomics, vol 19, iss 1, BMC Genomics, BMC Genomics, Vol 19, Iss 1, Pp 1-16 (2018)
- Publication Year :
- 2018
- Publisher :
- eScholarship, University of California, 2018.
-
Abstract
- BackgroundThe potential utility of microRNA as biomarkers for early detection of cancer and other diseases is being investigated with genome-scale profiling of differentially expressed microRNA. Processes for measurement assurance are critical components of genome-scale measurements. Here, we evaluated the utility of a set of total RNA samples, designed with between-sample differences in the relative abundance of miRNAs, as process controls.ResultsThree pure total human RNA samples (brain, liver, and placenta) and two different mixtures of these components were evaluated as measurement assurance control samples on multiple measurement systems at multiple sites and over multiple rounds. In silico modeling of mixtures provided benchmark values for comparison with physical mixtures. Biomarker development laboratories using next-generation sequencing (NGS) or genome-scale hybridization assays participated in the study and returned data from the samples using their routine workflows. Multiplexed and single assay reverse-transcription PCR (RT-PCR) was used to confirm in silico predicted sample differences. Data visualizations and summary metrics for genome-scale miRNA profiling assessment were developed using this dataset, and a range of performance was observed. These metrics have been incorporated into an online data analysis pipeline and provide a convenient dashboard view of results from experiments following the described design. The website also serves as a repository for the accumulation of performance values providing new participants in the project an opportunity to learn what may be achievable with similar measurement processes.ConclusionsThe set of reference samples used in this study provides benchmark values suitable for assessing genome-scale miRNA profiling processes. Incorporation of these metrics into an online resource allows laboratories to periodically evaluate their performance and assess any changes introduced into their measurement process.
- Subjects :
- 0301 basic medicine
Computer science
Placenta
Genome scale
computer.software_genre
Proteomics
Medical and Health Sciences
0302 clinical medicine
Reference samples
Pregnancy
Mirna profiling
Profiling (information science)
Cancer
0303 health sciences
Genome
microRNA
Methodology Article
Brain
High-Throughput Nucleotide Sequencing
Reference Standards
Biological Sciences
Liver
030220 oncology & carcinogenesis
Biomarker (medicine)
Female
Data mining
Process controls
DNA microarray
Biotechnology
Human
lcsh:QH426-470
Bioinformatics
lcsh:Biotechnology
In silico
Early detection
Bioengineering
Computational biology
Biology
03 medical and health sciences
Data visualization
Clinical Research
lcsh:TP248.13-248.65
Information and Computing Sciences
Genetics
Humans
030304 developmental biology
miRNA
Genome, Human
business.industry
Prevention
Gene Expression Profiling
Human Genome
RNA
lcsh:Genetics
MicroRNAs
030104 developmental biology
Workflow
Dashboard
business
computer
030217 neurology & neurosurgery
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- BMC genomics, vol 19, iss 1, BMC Genomics, BMC Genomics, Vol 19, Iss 1, Pp 1-16 (2018)
- Accession number :
- edsair.doi.dedup.....2796e04f2b465eb6d0eb1b995d0a0b20