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NormQ: RNASeq normalization based on RT-qPCR derived size factors
- Source :
- Computational and Structural Biotechnology Journal, Computational and Structural Biotechnology Journal, Vol 18, Iss, Pp 1173-1181 (2020)
- Publication Year :
- 2020
- Publisher :
- Research Network of Computational and Structural Biotechnology, 2020.
-
Abstract
- Graphical abstract<br />The merit of RNASeq data relies heavily on correct normalization. However, most methods assume that the majority of transcripts show no differential expression between conditions. This assumption may not always be correct, especially when one condition results in overexpression. We present a new method (NormQ) to normalize the RNASeq library size, using the relative proportion observed from RT-qPCR of selected marker genes. The method was compared against the popular median-of-ratios method, using simulated and real-datasets. NormQ produced more matches to differentially expressed genes in the simulated dataset and more distribution profile matches for both simulated and real datasets.
- Subjects :
- Normalization (statistics)
lcsh:Biotechnology
Biophysics
Computational biology
Biology
Biochemistry
RNASeq
Transcriptome
03 medical and health sciences
0302 clinical medicine
Structural Biology
lcsh:TP248.13-248.65
Genetics
TOMOSeq
Differential expression
Transcriptomics
Gene
030304 developmental biology
ComputingMethodologies_COMPUTERGRAPHICS
0303 health sciences
Computer Science Applications
Normalization
Differentially expressed genes
Median-of-ratios
030220 oncology & carcinogenesis
DESeq
Biotechnology
Research Article
Subjects
Details
- Language :
- English
- ISSN :
- 20010370
- Volume :
- 18
- Database :
- OpenAIRE
- Journal :
- Computational and Structural Biotechnology Journal
- Accession number :
- edsair.doi.dedup.....b3311618bdbf0753512bdba579dd5512