def volcano(df="dataframe", lfc=None, pv=None, lfc_thr=(1, 1), pv_thr=(0.05, 0.05), color=("green", "grey", "red"),
            valpha=1, geneid=None, genenames=None, gfont=8, dim=(5, 5), r=300, ar=90, dotsize=8, markerdot="o",
            sign_line=False, gstyle=1, show=False, figtype='png', axtickfontsize=9,
            axtickfontname="Arial", axlabelfontsize=9, axlabelfontname="Arial", axxlabel=None,
            axylabel=None, xlm=None, ylm=None, plotlegend=False, legendpos='best',
            figname='volcano', legendanchor=None,
            legendlabels=['significant up', 'not significant', 'significant down'], theme=None):
    _x = r'$ log_{2}(Fold Change)$'
    _y = r'$ -log_{10}(P-value)$'
    color = color
    # check if dataframe contains any non-numeric character
    assert general.check_for_nonnumeric(df[lfc]) == 0, 'dataframe contains non-numeric values in lfc column'
    assert general.check_for_nonnumeric(df[pv]) == 0, 'dataframe contains non-numeric values in pv column'
    # this is important to check if color or logpv exists and drop them as if you run multiple times same command
    # it may update old instance of df
    df = df.drop(['color_add_axy', 'logpv_add_axy'], axis=1, errors='ignore')
    assert len(set(color)) == 3, 'unique color must be size of 3'
    df.loc[(df[lfc] >= lfc_thr[0]) & (df[pv] < pv_thr[0]), 'color_add_axy'] = color[0]  # upregulated
    df.loc[(df[lfc] <= -lfc_thr[1]) & (df[pv] < pv_thr[1]), 'color_add_axy'] = color[2]  # downregulated
    df['color_add_axy'].fillna(color[1], inplace=True)  # intermediate
    df['logpv_add_axy'] = -(np.log10(df[pv]))
    # plot
    assign_values = {col: i for i, col in enumerate(color)}
    color_result_num = [assign_values[i] for i in df['color_add_axy']]
    assert len(set(color_result_num)) == 3, \
        'either significant or non-significant genes are missing; try to change lfc_thr or pv_thr to include ' \
        'both significant and non-significant genes'
    if theme == 'dark':
        general.dark_bg()
    plt.subplots(figsize=dim)
    if plotlegend:
        s = plt.scatter(df[lfc], df['logpv_add_axy'], c=color_result_num, cmap=ListedColormap(color), alpha=valpha,
                        s=dotsize, marker=markerdot)
        assert len(legendlabels) == 3, 'legendlabels must be size of 3'
        plt.legend(handles=s.legend_elements()[0], labels=legendlabels, loc=legendpos, bbox_to_anchor=legendanchor)
    else:
        plt.scatter(df[lfc], df['logpv_add_axy'], c=color_result_num, cmap=ListedColormap(color), alpha=valpha,
                    s=dotsize, marker=markerdot)
    if sign_line:
        plt.axhline(y=-np.log10(pv_thr[0]), linestyle='--', color='#7d7d7d', linewidth=1)
        plt.axvline(x=lfc_thr[0], linestyle='--', color='#7d7d7d', linewidth=1)
        plt.axvline(x=-lfc_thr[1], linestyle='--', color='#7d7d7d', linewidth=1)
    GeneExpression.gene_plot(df, geneid, lfc, lfc_thr, pv_thr, genenames, gfont, pv, gstyle)

    if axxlabel:
        _x = axxlabel
    if axylabel:
        _y = axylabel
    general.axis_labels(_x, _y, axlabelfontsize, axlabelfontname)
    general.axis_ticks(xlm, ylm, axtickfontsize, axtickfontname, ar)
    general.get_figure(show, r, figtype, figname, theme)