Introduction | Installation | Generate random data with missing covariate data | RNAseqCovarImpute Demonstration | MI PCA method | Conduct PCA | Conduct MI with mice | Conduct limma-voom analysis | Adjust for FDR | Gene binning MI method | Bin the genes into smaller groups | Make imputed data sets for each bin of genes and conduct differential expression analysis | Estimate gene expression changes using voom followed by lmFit functions, separately on each M imputed dataset within each gene bin | Apply variance shrinking Bayesian procedure, pooling results with Rubins’ rules, and FDR-adjust P-values | Session info

Generate random data | Simulate missingness in the random data | Session info