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Additional file 2 of m6A regulator-mediated methylation modification patterns and tumor microenvironment infiltration characterization in gastric cancer

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posted on 13.03.2020 by Bo Zhang, Qiong Wu, Ben Li, Defeng Wang, Lei Wang, You Lang Zhou
Additional file 2:Table S1. Basic information of datasets included in this study for identifying distinct m6A methylation modification patterns. Table S2. The gene sets used in this work for marking each TME infiltration cell type. Table S3. Spearman correlation analysis of the 21 m6A modification regulators. Table S4. Estimating relative abundance of tumor microenvironment cells in 1059 gastric cancer patients by the Single-Sample Gene-Set. Table S5. The activation states of biological pathways in distinct m6A modification patterns by GSVA enrichment analysis. Table S6. The changes of m6Aclusters, ACRG molecular subtypes, gene clusters and m6Ascore. Table S7. Prognostic analysis of 718 m6A phenotype-related genes using a univariate Cox regression model. Table S8. Functional annotation for m6A phenotype -related genes (Gene Ontology-Biological process). Table S9. Spearman correlation between m6Ascore and other known signatures within the gastric cancer.

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