Detect DE Genes Sample Clauses

Detect DE Genes. In this simulation study, we are going to use gene panels to identify DE genes. Although our major assumption is that log2CPM follows a normal distribution, we use a negative binomial distribution for counts to generate our simulation data. We follow the procedure of generating simulation data of DESeq2 (Love et al., 2014). Two samples are simulated in control and treatment group, respectively. 20000 genes are generated and 10% of them are DE genes with three-fold change. 50 samples are simulated as external data. Figure 28 shows false discoveries and false discovery rate when identify top genes as DE genes. We can see that with the help of gene panels, IPBTSeq could achieve a better performance than all existing methods. We use the imputation score in final results to exclude about 5% to 10% genes with unreliable imputation variance.
Sample 1
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