data wrangling functions

query_df_groupby_by_clone_channel[source]

query_df_groupby_by_clone_channel(df, queries:dict, clone_channel:str='C1', additional_agg_functions:dict=None)

additional agg_functions could be something like: additional_agg_functions = {"mean_intensity": [np.mean, np.std]}

data visualization functions

create_stack_bar_plot[source]

create_stack_bar_plot(df, df_error_bar=None, x_figSize=2.5, y_figSize=2.5, y_label=None, y_axis_start=0, y_axis_limit=None, color_pal=[(0.044059976931949255, 0.3338869665513264, 0.6244521337946944), (0.16696655132641294, 0.48069204152249134, 0.7291503267973857), (0.3262898885044214, 0.6186236063052672, 0.802798923490965), (0.5356862745098039, 0.746082276047674, 0.8642522106881968), (0.7309496347558632, 0.8394771241830065, 0.9213225682429834), (0.8584083044982699, 0.9134486735870818, 0.9645674740484429)], bar_width=0.8)

plot_stat_annotation[source]

plot_stat_annotation(x_indexes:tuple, y:int, p_values:list, sep:int=None, text_colors:list=None)

pvals_to_stat_anots[source]

pvals_to_stat_anots(pvals_arr, pval_thresholds=(0.0001, 0.001, 0.01, 0.05, 1), annotations=`('**', '', '*', '', '$^{ns}$')`*)