GWAS effect-Size distribution plot
This function generates the effect-size distribution boxplot
created by QC_series.
plot_distribution(data_table,
names = 1:ncol(data_table),
include = TRUE,
plot_order = 1:ncol(data_table),
quantile_lines = FALSE,
save_name = "Graph_distribution",
save_dir = getwd(), ...)data_table |
table with a column of effect sizes for every dataset. |
names |
vector; the names for the datasets, for use in the
graph. Note: it's best to keep these very short, as long
labels won't be plotted. The default is
the column numbers of |
include |
logical vector indicating which columns of
|
plot_order |
numeric vector determining the left-to-right
order of plotting the datasets (columns). |
quantile_lines |
logical; should lines representing the median and quartile values be included? |
save_name |
character string; the filename, without extension, for the graph file. |
save_dir |
character string; the directory where the graph is saved. Note that R uses forward slash (/) where Windows uses backslash (\). |
... |
arguments passed to |
When running a QC over multiple files, QC_series
collects the values of the effectsize_HQ output of
QC_GWAS in a table, which is then passed to this
function. If there are significant
differences in the distribution of effect sizes, it usually
indicates that the datasets did not use the same model or unit.
An invisible NULL.
For comparing reported to expected effect-size distribution:
QC_histogram.
For other plots comparing GWAS results files:
plot_precision and plot_skewness.
data("gwa_sample")
chunk1 <- gwa_sample$EFFECT[1:1000]
chunk2 <- gwa_sample$EFFECT[1001:2000]
chunk3 <- gwa_sample$EFFECT[2001:3000]
plot_distribution(
data_table = data.frame(chunk1, chunk2, chunk3),
names = c("chunk 1", "chunk 2", "chunk 3"),
quantile_lines = TRUE,
save_name = "sample_distribution")Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.