The first argument can be a multiOmicDataset
object (moo
) or a data.frame
containing counts.
For a moo
, choose which counts slot to use with count_type
& (optionally) sub_count_type
.
Methods
link to docs | class |
plot_read_depth_moo | multiOmicDataSet |
plot_read_depth_dat | data.frame |
See also
Other plotters:
plot_corr_heatmap()
,
plot_expr_heatmap()
,
plot_histogram()
,
plot_pca()
,
print_or_save_plot()
Other moo methods:
batch_correct_counts()
,
clean_raw_counts()
,
filter_counts()
,
normalize_counts()
,
plot_corr_heatmap()
,
plot_expr_heatmap()
,
plot_histogram()
,
plot_pca()
,
run_deseq2()
,
set_color_pal()
Examples
# multiOmicDataSet
moo <- multiOmicDataSet(
sample_metadata = nidap_sample_metadata,
anno_dat = data.frame(),
counts_lst = list(
"raw" = nidap_raw_counts,
"clean" = nidap_clean_raw_counts
)
)
plot_read_depth(moo, count_type = "clean")
# dataframe
plot_read_depth(nidap_clean_raw_counts)