Additional file 8 of Comparison of normalization methods for the analysis of metagenomic gene abundance data

Figure S5. True false discovery rate for p-values adjusted using Benjamini-Yekutieli method at an estimated false discovery rate of 0.05 (y-axis) for different distribution of effects between groups (x-axis): balanced (‘B’) with 10% of effects divided equally between the two groups, lightly-unbalanced (’LU’) with effects added 75%-25% in each group, unbalanced (‘U’) with all effects added to only one group, and heavily-unbalanced (’HU’) with 20% of effects added to only one group. The results were based on resampled data consisting of two groups with 10 samples in each, and an average fold-change of 3. Three metagenomic datasets were used Human gut I, Human gut II and Marine. The following methods are included in the figure trimmed mean of M-values (TMM), relative log expression (RLE), cumulative sum scaling (CSS), reversed cumulative sum scaling (RCSS), quantile-quantile (Quant), upper quartile (UQ), median (Med), total count (TC) and rarefying (Rare). (PDF 40 kb

Additional file 7 of Comparison of normalization methods for the analysis of metagenomic gene abundance data

Table S3. True false discovery rate at an estimated false discovery rate of 0.05 for a group size of 10+10. (PDF 16 kb

Additional file 9 of Comparison of normalization methods for the analysis of metagenomic gene abundance data

Figure S6. True false discovery rate for p-values adjusted using Storey q-values method at an estimated false discovery rate of 0.05 (y-axis) for different distribution of effects between groups (x-axis): balanced (‘B’) with 10% of effects divided equally between the two groups, lightly-unbalanced (‘LU’) with effects added 75–25% in each group, unbalanced (‘U’) with all effects added to only one group, and heavily-unbalanced (‘HU’) with 20% of effects added to only one group. The results were based on resampled data consisting of two groups with 10 samples in each, and an average fold-change of 3. Three metagenomic datasets were used Human gut I, Human gut II and Marine. The following methods are included in the figure trimmed mean of M-values (TMM), relative log expression (RLE), cumulative sum scaling (CSS), reversed cumulative sum scaling (RCSS), quantile-quantile (Quant), upper quartile (UQ), median (Med), total count (TC) and rarefying (Rare). (PDF 132 kb

Additional file 1 of Comparison of normalization methods for the analysis of metagenomic gene abundance data

Figure S1. Histograms of Spearman correlations between normalization factors and raw counts of non-differentially abundant genes (non-DAGs). Spearman correlations were compute per gene in the Human gut I, for group size 10+10, with 10% of effects divided equally between the two group, and fold-change 3. Affected genes were randomly selected in 100 iterations. The following methods are included in the figure trimmed mean of M-values (TMM), relative log expression (RLE), cumulative sum scaling (CSS), reversed cumulative sum scaling (RCSS), upper quartile (UQ), median (Med) and total count (TC). (PDF 76 kb

Additional file 4 of Comparison of normalization methods for the analysis of metagenomic gene abundance data

Table S1. True positive rate at a fixed false positive rate of 0.01 for a group size of 10+10. (PDF 16 kb

Additional file 2 of Comparison of normalization methods for the analysis of metagenomic gene abundance data

Figure S2. Scatterplot of normalization factors for each pair of scaling methods. Normalization factors estimated per sample in the Human gut I, for group size 10+10, with 10% of effects divided equally between the two group, and fold-change 3. Affected genes were randomly selected in 100 iterations. The number on the top-left of each plot indicates the Spearman correlation for the normalization factors presented in the plot. The following methods are included in the figure trimmed mean of M-values (TMM), relative log expression (RLE), cumulative sum scaling (CSS), reversed cumulative sum scaling (RCSS), upper quartile (UQ), median (Med) and total count (TC). (PDF 316 kb

Additional file 5 of Comparison of normalization methods for the analysis of metagenomic gene abundance data

Table S2. False positive rate at a fix true positive rate of 0.50 for a group size of 10+10. (PDF 16 kb

Additional file 3 of Comparison of normalization methods for the analysis of metagenomic gene abundance data

Figure S3. Mean Spearman correlation between raw and normalized counts. Spearman correlations were compute per gene before and after normalization in the Human gut I, for group size 10+10, with 10% of effects divided equally between the two group, and fold-change 3. Affected genes were randomly selected in 100 iterations. The following methods are included in the figure trimmed mean of M-values (TMM), relative log expression (RLE), cumulative sum scaling (CSS), reversed cumulative sum scaling (RCSS), quantile-quantile (Quant), upper quartile (UQ), median (Med), total count (TC) and rarefying (Rare). (PDF 8 kb