MOESM2 of Improved cell composition deconvolution method of bulk gene expression profiles to quantify subsets of immune cells

Additional file 2: Table S1. The microarray samples downloaded from NCBI GEO as the raw data to be used as the reference gene expression profiles, each being annotated with its source NCBI GEO sample accession numbers (GSM). Table S2. The reference gene expression signature (RefGES) matrix created in this study. Table S3. The cumulative percentages of observations for the difference between predictions and real values in the benchmark using the simulated bulk tissues with 30% expression levels from breast tissues and 70% from immune cells. Table S4. The cumulative percentages of observations for the difference between predictions and real values in the benchmark using the simulated bulk tissues with 50% expression levels from breast tissues and 50% from immune cells. Table S5. The cumulative percentages of observations for the difference between predictions and real values in the benchmark using the simulated bulk tissues with 70% expression levels from breast tissues and 30% from immune cells. Table S6. The mapping of the cell types of NCBI GEO GSE65133 to those of LM22 (CIBERSORT) and the RefGES used in this study. Table S7. The cumulative percentages of observations for the difference between predictions and real values in the benchmark using the 20 human PBMC samples of NCBI GEO GSE65133. Table S8. The mapping of the cell types of NCBI GEO GSE106898 to those of LM22 (CIBERSORT) and the RefGES used in this study. Table S9. The cumulative percentages of observations for the difference between predictions and real values in the benchmark using the 12 human PBMC samples of NCBI GEO GSE106898. Table S10. The mapping of the cell types of NCBI GEO GSE107990 to those of LM22 (CIBERSORT) and the RefGES used in this study. Table S11. The cumulative percentages of observations for the difference between predictions and real values in the benchmark using the 164 human PBMC samples of NCBI GEO GSE107990.