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Figure S1. Quality control processes for DNA methylation chip data. Quality control measures and exclusion criteria as applied to Harvard, Spain, Norway, Sweden, and The Cancer Genome Atlas (TCGA) sample cohorts. (PDF 642 kb)

Figure S2. Analysis work flow. Adenocarcinoma and squamous cell carcinoma samples from Harvard, Spain, Norway, and Sweden cohorts were used for the discovery phase of analysis. Data from The Cancer Genome Atlas (TCGA) were used for Validation. Ranger is a weighted version of random forest for controlling for the covariates including age, gender, smoking status, and histological stage. Variable importance score (VIS) was estimated for each CpG site and was ranked in descending order. CpG sites ranked in top 10% in both discovery and validation sets were selected for further evaluation by Cox regression. Multiple testing correction by false discovery rate (FDR) method was used if necessary. (PDF 357 kb)

Figure S3. DNA methylation probes identified by flexible criterion in squamous cell carcinoma and their correlation with corresponding gene expression. Three more sites were identified in SCC samples under flexible criterion: cg06646494 in KDM2B, cg00121158 in KDM4C, and cg06615743 in KDM4B. The cg00121158 (A) and cg06615743 (B) showed a statistical correlation with the corresponding gene expression. DNA methylation level was categorized to six quantiles and box plot for gene expression was drawn for each quantile. Pearson correlation was used to estimate the correlation coefficient (r) and the P value, Gene expression was log2 transformed before analysis. (PDF 571 kb)

Study required risk factors for ARDS on admission to ICU [6]. Table S2. Demographic characteristics of MEARDS miRNA study cohorts (n = 529). Table S3. MicroRNA candidate screening in discovery study. Table S4. Diagnostic performance of sepsis, pneumonia, and miRNA biomarkers for ARDS. Figure S1. MEARDS cohort recruitment process. Figure S2. Sample A (A) and sample B (B) from two patients both showed strong correlations between duplicate samples on different chips and different profiling day in discovery study (R 2 = 0.99), indicating that detectable miRNAs (after meeting quality control criteria) are experimentally consistent. Figure S3. Sample duplicate consistency between discovery and validation phase (after meeting quality control criteria). The figure showed high correlation (R 2 = 0.90) between miRNA expression in discovery study and validation study. Figure S4. Gene set enrichment analysis of 22 candidate miRNAs. Seventeen of them found to be significantly overrepresented (FDR q

Study required risk factors for ARDS on admission to ICU [6]. Table S2. Demographic characteristics of MEARDS miRNA study cohorts (n = 529). Table S3. MicroRNA candidate screening in discovery study. Table S4. Diagnostic performance of sepsis, pneumonia, and miRNA biomarkers for ARDS. Figure S1. MEARDS cohort recruitment process. Figure S2. Sample A (A) and sample B (B) from two patients both showed strong correlations between duplicate samples on different chips and different profiling day in discovery study (R 2 = 0.99), indicating that detectable miRNAs (after meeting quality control criteria) are experimentally consistent. Figure S3. Sample duplicate consistency between discovery and validation phase (after meeting quality control criteria). The figure showed high correlation (R 2 = 0.90) between miRNA expression in discovery study and validation study. Figure S4. Gene set enrichment analysis of 22 candidate miRNAs. Seventeen of them found to be significantly overrepresented (FDR q