Predictors of Outcome in Aneurysmal Subarachnoid Hemorrhage Patients:Observations From a Multicenter Data Set

A table containing information on the qRT-PCR performed with seven novel miRNAs and two known miRNAs. Per miRNA, this information includes mean CT, range of CT, cDNA dilution, the number of samples (of 12) with CT < 40, the average read depth, and primer used. (XLSX 8 kb

Additional file 3: Figure S1. of Evaluation of logistic regression models and effect of covariates for case–control study in RNA-Seq analysis

Type-I error rates of regression methods from the balanced design. Type-I error rates of the Negative Binomial with true dispersion (NB), Classic Logistic (CL), Bayes Logistic (BL), and Firth’s Logistic (FL) regressions at alpha levels of 0.05 and 0.01 are shown. The black dotted horizontal lines represent 5 and 1% of Type-I error rates. Dispersion values (ϕ = 0.01 and 1) are separated by black dotted vertical lines. Four values of the number of cases (10, 25, 75 and 500) are placed within each dispersion value. Dotted lines within each symbol imply 95% confidence interval. Figure S1 (A): The figure presents the Type-I error rates when μ = 50. Figure S1 (B): This figure shows the Type-I error rates when μ = 1000. (PNG 399 kb

Additional file 15: Table S6. of Evaluation of logistic regression models and effect of covariates for case–control study in RNA-Seq analysis

Type-I error rates of the NB regression from the balanced design with N D=1  = 10 and μ = 1000. Disp: Dispersion, CovOR: Odds ratios between covariates and case–control status, Ncov: The number of covariates in a model, NB: Negative binomial regression, MLD: Maximum likelihood estimated Dispersion, QLD: Quasi-likelihood estimated Dispersion, TD: The dispersion is used for the sampling. (DOCX 59 kb

Additional file 13: Table S4. of Evaluation of logistic regression models and effect of covariates for case–control study in RNA-Seq analysis

Top 10 significant genes from DESeq2 among genes not significant in logistic regressions. Mean.Exp.Case: Normalized mean expression value in cases, Mean.Exp.Cont: Normalized mean expression value in controls, Disp: Dispersion, NB.Pval: P-values from negative binomial regression with true dispersion, CL.Pval: P-values from classical logistic regression, BL.Pval: P-values from Bayes logistic regression, FL.Pval: P-values from Firth’s logistic regression. (DOCX 53 kb

Additional file 10: Figure S6. of Evaluation of logistic regression models and effect of covariates for case–control study in RNA-Seq analysis

Bias from regression methods using the permuted HD data with μ g  > 3. Figure S6 contains bias from Negative Binomial regression using DESeq2, Classical Logistic regression (CL), Bayes Logistic regression (BL), and Firth’s Logistic regression (FL). Each black empty dot represents the bias of a gene. The black dotted horizontal line is no bias point. The bias of each gene is calculated using effect sizes of 10,000 permutations. (PNG 53 kb

Additional file 18: R code. of Evaluation of logistic regression models and effect of covariates for case–control study in RNA-Seq analysis

This R code regenerates the simulated data sets. (R 6 kb

Additional file 16: Table S7. of Evaluation of logistic regression models and effect of covariates for case–control study in RNA-Seq analysis

Bias with covariate models from the balanced design of N D=1  = 10 and μ D=0  = 1000. Disp: Dispersion, CovOR: Odds ratios between covariates and case–control status, Ncov: The number of covariates in a model, NB_TD: Negative binomial regression with the dispersion is used for the sampling, FL: Firth’s logistic regression. (DOCX 47 kb

Additional file 6: Figure S2. of Evaluation of logistic regression models and effect of covariates for case–control study in RNA-Seq analysis

Type-I error rates from DESeq2 analysis of the permuted HD data. This contains Type-I error rates from DESeq2 (negative binomial model) analysis of the permuted HD data at alpha levels of 0.05 and 0.01. Each black empty dot represents Type-I error rate of a gene. The red dots denote average values of Type-I error rates in each category of dispersion groups. The black dotted horizontal lines are our alpha levels. Figure S2 (A) shows Type-I error rates of all genes at alpha level of 0.05. Figure S2 (B) displays Type-I error rates of all genes at alpha level of 0.01. (PNG 309 kb

Additional file 12: Figure S8. of Evaluation of logistic regression models and effect of covariates for case–control study in RNA-Seq analysis

Venn diagram of HD analysis results using DA method. Each colored circle represents a different regression method. The numbers inside of the circles are the number of genes significant at FDR 0.05 based on p-values adjusted using the Data Adaptive (DA) method. There were 3,203 significant genes in common across all the methods. The FL identified the largest number of significant genes compared to CL and BL. The NB independently identified 944 genes. (PNG 474 kb

Additional file 4: Table S2. of Evaluation of logistic regression models and effect of covariates for case–control study in RNA-Seq analysis

Type-I error rates of regression methods from the unbalanced design with μ D=0  = 1000. Alpha: Significance levels, N D=1 : The number of cases, N D=0 : The number of controls, Disp: Dispersion, NB: Negative binomial regression with true dispersion, CL: Classical logistic regression, BL: Bayes logistic regression, FL: Firth’s logistic regression. (DOCX 65 kb