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Limitations and possibilities of small RNA digital gene expression profiling

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NIAID Data Ecosystem2026-03-10 收录
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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE16374
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Analysis of RNA samples by massive parallel sequencing holds the promise to assay gene expression in both a quantitative and qualitative fashion and therefore allows for digital gene expression (DGE) profiling. We assessed the effect of different experimental approaches by generating small RNA libraries from a biological sample as well as an equimolar pool of synthetic miRNAs and analyzed the results using capillary dideoxy sequencing and next-generation sequencing platforms (Roche/454, AB/SOLiD and Illumina/Solexa). Whereas different sequencing platforms provided highly similar results, large differences in DGE profiles were observed depending on the library preparation method used. Nevertheless, our results indicate that the preferential nature of the library preparation methods is systematic and highly reproducible and we show that DGE is well suited for the quantification of relative expression differences between samples. This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
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2018-12-03
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