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Fig. 8 | Biology Direct

Fig. 8

From: Finite-size effects in transcript sequencing count distribution: its power-law correction necessarily precedes downstream normalization and comparative analysis

Fig. 8

Receivers Operator Characteristics (ROC) curves of the spike-in data set before and after power-law correction. Figure 8 shows the receivers operator characteristics (ROC) curves for the 6 normalization methods: DESeq, Relative Log Expression (RLE), Trimmed Mean of M-values (TMM), UpperQuartile (UQ), Count Per Million (CPM) and Quantile normalization. For each ROC plot, the sensitivity and specificity values were derived through the permutation of the log fold-change range of the noise comparisons. The plot without correction is shown in red while the power-law corrected one is depicted in blue. Overall, an obvious improvement in the performance upon the power-law correction can be seen regardless of normalization methods. Among the methods, the quantile normalization method gave the worst performance

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Biology Direct

ISSN: 1745-6150

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