ReviewCancer informatics2014
Statistical Issues in the Design and Analysis of nCounter Projects.
Review in Cancer informatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- Quantitating the effect of prosthesis design on femoral remodeling using high-resolution region-free densitometric analysis (DXA-RFA).Journal of orthopaedic research : official publication of the Orthopaedic Research Society · 2017Trial
- Hormonal contraceptives during adolescence impact the female brain and behavior in a rat model.Hormones and behavior · 2025Article
- Time of day bias for biological sampling in studies of mammary cancer.Scientific reports · 2024Article
- Detection of ALK fusion transcripts in FFPE lung cancer samples by NanoString technology.BMC pulmonary medicine · 2017Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Numerous statistical methods have been published for designing and analyzing microarray projects. Traditional genome-wide microarray platforms (such as Affymetrix, Illumina, and DASL) measure the expression level of tens of thousands genes. Since the sets of genes included in these array chips are selected by the manufacturers, the number of genes associated with a specific disease outcome is limited and a large portion of the genes are not associated. nCounter is a new technology by NanoString to measure the expression of a selected number (up to 800) of genes. The list of genes for nCounter chips can be selected by customers. Due to the limited number of genes and the price increase in the number of selected genes, the genes for nCounter chips are carefully selected among those discovered from previous studies, usually using traditional high-throughput platforms, and only a small number of definitely unassociated genes, called control genes, are included to standardize the overall expression level across different chips. Furthermore, nCounter chips measure the expression level of each gene using a counting observation while the traditional high-throughput platforms produce continuous observations. Due to these differences, some statistical methods developed for the design and analysis of high-throughput projects may need modification or may be inappropriate for nCounter projects. In this paper, we discuss statistical methods that can be used for designing and analyzing nCounter projects.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.