ArticleRNA (New York, N.Y.)2012
Evaluation of normalization methods in mammalian microRNA-Seq data.
Article in RNA (New York, N.Y.), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers, 1 of them a synthesis that pooled it.
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Who cites it
64 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic Review of Micro-RNA Expression in Pre-Eclampsia Identifies a Number of Common Pathways Associated with the Disease.PloS one · 2016Pooled it
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- MicroRNAs in idiopathic childhood nephrotic syndrome.Clinical and experimental nephrology · 2025Article
- MicroRNAs as Targets for Cancer Diagnosis: Interests and Limitations.Advanced pharmaceutical bulletin · 2023Review
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- The hypoxia-induced changes in miRNA-mRNA in RNA-induced silencing complexes and HIF-2 induced miRNAs in human endothelial cells.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2022Article
- Differential microRNA profiles of intramuscular and secreted extracellular vesicles in human tissue-engineered muscle.Frontiers in physiology · 2022Article
- GET4 is a novel driver gene in colorectal cancer that regulates the localization of BAG6, a nucleocytoplasmic shuttling protein.Cancer science · 2022Article
- Altered non-coding RNA expression profile in FScientific reports · 2021Article
- Measurements Methods for the Development of MicroRNA-Based Tests for Cancer Diagnosis.International journal of molecular sciences · 2021Review
- Radiology- and gene-based risk stratification in small renal cell carcinoma: A preliminary study.PloS one · 2021Article
- Upregulated miR-224-5p suppresses osteoblast differentiation by increasing the expression of Pai-1 in the lumbar spine of a rat model of congenital kyphoscoliosis.Molecular and cellular biochemistry · 2020Article
- Circulating PD-1 mRNA in Peripheral Blood is a Potential Biomarker for Predicting Survival of Breast Cancer Patients.Annals of surgical oncology · 2020Article
- DeepImpute: an accurate, fast, and scalable deep neural network method to impute single-cell RNA-seq data.Genome biology · 2019Article
- Comprehensive assessment of multiple biases in small RNA sequencing reveals significant differences in the performance of widely used methods.BMC genomics · 2019Article
- MicroRNA Profile of HCV Spontaneous Clarified Individuals, Denotes Previous HCV Infection.Journal of clinical medicine · 2019Article
- Identifying and characterizing functional 3' nucleotide addition in the miRNA pathway.Methods (San Diego, Calif.) · 2019Review
- RATEmiRs: the rat atlas of tissue-specific and enriched miRNAs database.BMC genomics · 2018Article
4 more citing papers are in PubMed but not listed here.
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Abstract
Simple total tag count normalization is inadequate for microRNA sequencing data generated from the next generation sequencing technology. However, so far systematic evaluation of normalization methods on microRNA sequencing data is lacking. We comprehensively evaluate seven commonly used normalization methods including global normalization, Lowess normalization, Trimmed Mean Method (TMM), quantile normalization, scaling normalization, variance stabilization, and invariant method. We assess these methods on two individual experimental data sets with the empirical statistical metrics of mean square error (MSE) and Kolmogorov-Smirnov (K-S) statistic. Additionally, we evaluate the methods with results from quantitative PCR validation. Our results consistently show that Lowess normalization and quantile normalization perform the best, whereas TMM, a method applied to the RNA-Sequencing normalization, performs the worst. The poor performance of TMM normalization is further evidenced by abnormal results from the test of differential expression (DE) of microRNA-Seq data. Comparing with the models used for DE, the choice of normalization method is the primary factor that affects the results of DE. In summary, Lowess normalization and quantile normalization are recommended for normalizing microRNA-Seq data, whereas the TMM method should be used with caution.
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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.