ArticleDisease markers2013
Rapid and inexpensive screening of genomic copy number variations using a novel quantitative fluorescent PCR method.
Article in Disease markers, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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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0 citing papers in PubMed, 1 citations in OpenAlex.
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Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
Abstract
Detection of human microdeletion and microduplication syndromes poses significant burden on public healthcare systems in developing countries. With genome-wide diagnostic assays frequently inaccessible, targeted low-cost PCR-based approaches are preferred. However, their reproducibility depends on equally efficient amplification using a number of target and control primers. To address this, the recently described technique called Microdeletion/Microduplication Quantitative Fluorescent PCR (MQF-PCR) was shown to reliably detect four human syndromes by quantifying DNA amplification in an internally controlled PCR reaction. Here, we confirm its utility in the detection of eight human microdeletion syndromes, including the more common WAGR, Smith-Magenis, and Potocki-Lupski syndromes with 100% sensitivity and 100% specificity. We present selection, design, and performance evaluation of detection primers using variety of approaches. We conclude that MQF-PCR is an easily adaptable method for detection of human pathological chromosomal aberrations.
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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.