Generate a box plot
Usage
get_gene_expression_box_plot(
x,
samples = NULL,
genes = NULL,
group_replicates = FALSE,
convert_log2 = TRUE
)Arguments
- x
an abject of class "parcutils". This is an output of the function
run_deseq_analysis().- samples
a character vector denoting samples to plot in boxplot, default
NULL. If set to NULL all samples are accounted.- genes
a character vector denoting genes to consider for boxplot, default
NULL. If set to NULL all genes are accounted.- group_replicates
logical, default
FALSE, whether to group replicates in individual plots.- convert_log2
logical, default
TRUE, whether to plot log2(noralised expression + 1) or not.
Examples
count_file <- system.file("extdata","toy_counts.txt" , package = "parcutils")
count_data <- readr::read_delim(count_file, delim = "\t")
#> Rows: 5000 Columns: 10
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: "\t"
#> chr (1): gene_id
#> dbl (9): control_rep1, control_rep2, control_rep3, treat1_rep1, treat1_rep2,...
#>
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
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"))
#> ℹ Running DESeq2 ...
#> converting counts to integer mode
#> Warning: some variables in design formula are characters, converting to factors
#> estimating size factors
#> estimating dispersions
#> gene-wise dispersion estimates
#> mean-dispersion relationship
#> final dispersion estimates
#> fitting model and testing
#> ✔ Done.
#> ℹ Summarizing DEG ...
#> ✔ Done.
get_gene_expression_box_plot(x = res ) %>% print()
get_gene_expression_box_plot(x = res , group_replicates = TRUE ) %>% print()
