October 2019
Intermediate to advanced
316 pages
9h 45m
English
Content preview from R Bioinformatics Cookbook
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How to do it...
We will do the power analysis using the following steps:
- Estimate simulation parameter values:
arab_data <- readRDS(file.path(getwd(), "datasets", "ch1", "arabidopsis.RDS" ))means_mock <- rowMeans(arab_data[, c("mock1", "mock2", "mock3")])means_hrcc <- rowMeans(arab_data[, c("hrcc1", "hrcc2", "hrcc3")])log2fc <- log2(means_hrcc / means_mock)prop_de <- sum(abs(log2fc) > 2) / length(log2fc)
- Examine the distribution of the log2 fold change ratios:
finite_log2fc <-log2fc[is.finite(log2fc)]plot(density(finite_log2fc))extRemes::qqnorm(finite_log2fc )
- Set up parameter values for the simulation run:
library(powsimR) library(dplyr) params <- estimateParam( countData = arab_data, Distribution = "NB", RNAseq = "bulk", normalization ...
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