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Table 1 Summary of studies comparing normalization methods for the DEG analysis

From: Choice of library size normalization and statistical methods for differential gene expression analysis in balanced two-group comparisons for RNA-seq studies

ReferencesNormalization methodsSoftware Packages/ pipelinesReplicates per condition (n)Conclusions
Bullard et al. 2010 [17]POLR2A, Q, TC, UQGenominator2, 4POLR2A and UQ with LRT/Exact test significantly reduced the bias of DE relative to qRT-PCR
Kvam et al. 2012 [33]DESeq, TMM, UQDESeq, edgeR, baySeq, TSPM2, 4, 5baySeq with UQ normalization performed best with highest sensitivity and low rates of false positives. But all the methods had an inflated true FDR (> 0.1).
Rapaport F. et al. 2013 [34]DESeq, TMM, UQ, RPKM, FPKM, Q, voom,Cuffdiff, DESeq, edgeR, baySeq, PoissonSeq, voom-limma2, 3No single method emerged as favorable in all comparisons, but baySeq with UQ method was least correlated with qRT-PCR and Cuffdiff had an inflated number of false positive predictions.
Li et al. 2015 [35]DESeq, Med, Q, RPKM, RC, TMM, UQ, ERPKMDESeq, edgeR, Cufflinks-CuffDiff, RSEM, Sailfis2, 4RC or RPKM seems to be adequate and the results from Sailfish and RSEM with RC or RPKM are inconsistent, resulting a conclusion of that normalization methods are not necessary for all sequence data.
Dilliest et al. 2013 [23]DESeq, Med, Q, RPKM, TC, TMM, UQDESeq, edgeR, Cufflinks-CuffDiff2, 3Exact test from DESeq combined with DESeq/TMM normalization performed best in terms of control of FDR below 0.05 for high-count genes; RPKM, TC and Q should be abandoned in DE gene analysis.
Soneson et al. 2013 [36]DESeq, TMM, UQ, RPKM, FPKM, voom, vstDESeq, edgeR, EBSeq, baySeq, NBPSeq,NOIseq, SAMseq, ShrinkSeq,TSPM, limma2, 5, 10, 11DESeq had poor FDR control with 2 samples and good FDR control for larger sample sizes and low TPR.edgeR had poor FDR control with high TPR. Voom/vst-limma had good FDR control, but low power for small sample size.
Seyednasroliah et al. 2013 [37]DESeq, TMM, UQ, RPKM, FPKM, voomDESeq, edgeR, baySeq, NOIseq, SAMseq, limma, CuffDiff2, EBSeq2:6, 8,10,12, 16, 20, 24, 28DESeq and limma were the safe choice and relatively conservative while edgeR and EBSeq were too liberal. DESeq and edgeR were the best tools
Zhang et al. 2014 [38]DESeq, TMM, FPKM,DESeq, edgeR, Cufflinks-CuffDiff1:6, 8, 14, 20TMM performed best in terms of sensitivity and DESeq was the best for control false positives. Both were not sensitive to the read depth.
Lin et al. 2016 [39]DESeq, Med, Q, RPKM, TC, TMM, UQDESeq, edgeR and SAS2, 3, 5DESeq and TMM normalization methods were recommended compared to the other methods.
Tang et al. 2015 [40]RLE,TMM, UQ, RPKM, FPKM, Q, voom,DESeq, DESeq2, edgeR, EBSeq, baySeq, SAMseq, PoissonSeq, voom-limma, TCC1, 3, 6, 9In multi-group comparison, the proposed pipeline internally using edgeR was recommended for count data with replicates while this pipeline with DESeq2 was recommended for data without replicates
Germain et al. 2016 [41]RLE, TMM, voom, TPMCufflinks-CuffDiff, DESeq2, edgeR, voom-limma3, 5With benchmarked differential expression analysis, in general voom and edgeR showed the most stable performance and be superior to other methods in most assay with replicates of 3 and 5. But voom significantly underperformed in transcript-level simulation and edgeR shown suboptimal results in the SEQC dataset
Maza E 2016 [42]TMM, RLE, MRNDESeq2, edgeR1The three methods gave the same results for a simple two-condition comparison withourt replicates.
Costa-Silva et al. 2017 [43]TMM, RLE, UQ, voomLimma-Voom, NOIseq, DESeq2, SAMSeq, EBSeq, sleuth, baySeq, edgeR1:8Limma-voom, NOIseq and DESeq2 had more consistent results for DEGs identification
Spies et al. 2019 [44]Vst, Med, RLE, TMMDyNB, EBSeq-HMM, FunPat, ImpulseDE2, Imms, next maSigPro, nsgp, splineTC, timeSeq, edgeR, DESeq22, 3, 5DESeq2 and edgeR with a pairwise comparison outperformed TC tools for short time course (< 8 time points) due to high false positive rate except ImpulseDE2, but they were less efficient on longer time series than splineTC and maSigPro tools.