get_pca_plot | R Documentation |
Generate a PCA plot.
get_pca_plot(
x,
samples = NULL,
genes = NULL,
circle_size = 10,
label_replicates = FALSE,
sample_colors = FALSE,
sample.seed = 123
)
x |
an abject of class "parcutils". This is an output of the function |
samples |
a character vector denoting samples to plot in PCA plot, default |
genes |
a character vector denoting genes to consider for PCA plot, default |
circle_size |
a numeric value, default 10, denoting size of the circles in PCA plot. |
label_replicates |
logical, default FALSE, denoting whether to label each replicate in the plot. |
sample_colors |
a logical, default FALSE, denoting whether to shuffle colors of dots in PCA plot. |
sample.seed |
an integer, default 123, denoting a value for |
an object of ggplot2.
count_file <- system.file("extdata","toy_counts.txt" , package = "parcutils")
count_data <- readr::read_delim(count_file, delim = "\t")
sample_info <- count_data %>% colnames() %>% .[-1] %>%
tibble::tibble(samples = . , groups = rep(c("control" ,"treatment1" , "treatment2"), each = 3) )
res <- run_deseq_analysis(counts = count_data ,
sample_info = sample_info,
column_geneid = "gene_id" ,
group_numerator = c("treatment1", "treatment2") ,
group_denominator = c("control"))
get_pca_plot(x = res,sample_colors = TRUE) %>% print()
# reproduce sampled colors with argument `sample.seed`
get_pca_plot(x = res,sample_colors = TRUE, sample.seed = 345) %>% print()
# label replicates
get_pca_plot(x = res, sample_colors = FALSE,label_replicates = TRUE)
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