`ALLCools.plot.qc_plots`¶

Module Contents¶

plot_on_plate(data, value_col, groupby, ncols=4, plate_base=384, figsize=(5, 3.5), row_base='Row384', col_base='Col384', vmin=0, vmax=1, heatmap_kws=None, aggregation_func=None)[source]¶: Plot metadata into 384 or 96 plate view (heatmap) :param data: dataframe contain all kinds of metadata :param value_col: value to be plotted on plate view :param groupby: groupby column, typically groupby plate id column(s) to plot each plate separately :param ncols: number of column for axes, nrows will be calculated accordingly :param plate_base: {384, 96} size of the plate view :param figsize: matplotlib.Figure figsize :param vmin: cmap vmin :param vmax: cmap vmax :param heatmap_kws: kws pass to sns.heatmap :param aggregation_func: apply to reduce rows after groupby if the row is not unique

cutoff_vs_cell_remain(data, name='', xlim_quantile=(0.001, 0.999), ylim=None, bins=100)[source]¶

plot_dispersion(data, hue='gene_subset', zlab='dispersion', data_quantile=(0.01, 0.99), save_animate_path=None, fig_kws=None)[source]¶