Additional file 1 of A deconvolution method and its application in analyzing the cellular fractions in acute myeloid leukemia samples

Additional file 1: Table S0. Datasets and their application in this study. Table S1. Gene Ontology (Biological Processes (BP)) annotation for the marker genes identified by LinDeconSeq. Table S2. Gold-standard marker genes. Table S3. Signature matrix of 13 cell types revealed by LinDeconSeq in AML and Healthy samples. Table S4. The estimated cellular fractions by LinDeconSeq for 179 TCGA-AML samples. Table S5. The estimated cellular fractions for the 100 transcriptomic data of the healthy samples in GSE134080 using LinDeconSeq. Table S6. Comparison of the actual and predicted classification for 2138 independent test samples based on the SVM, Random Forest and Logistic Regression. Table S7. Two subgroups derived from TCGA-AML samples using PAM clustering method. Table S8. Differentially expressed genes (DEGs) revealed by DESeq2 between SubgroupA and SubgroupB. Table S9. Gene Ontology analysis for the DEGs with tool DAVID. Table S10. The estimated cellular fractions for the 187 TARGET-AML samples with LinDeconSeq. Table S11. The feature genes selected from the DEGs for training random forest classifier. Table S12. The subgroups predicted by the trained random forest classifier for TARGET-AML samples.