<jupyter_start><jupyter_text>Panel 2A<jupyter_code>opref = 'figures/bulk_vs_sc'
bulk = get_bulk_data()
sc = get_sc_data()
gtf = '/Users/fairliereese/Documents/programming/mortazavi_lab/ref/gencode.vM21/gencode.vM21.annotation.gtf'
_, _ = plot_upset_plot(bulk, sc, opref, gtf, kind='gene', novelty='Known')
plot_detection_venn(bulk, sc, opref, gene_nov='Known', \
                    sample='MB', cell_part='cell')
plot_detection_venn(bulk, sc, opref, gene_nov='Known', \
                    sample='MB', cell_part='nucleus')
plot_detection_venn(bulk, sc, opref, gene_nov='Known', \
                    sample='MT', cell_part='nucleus')<jupyter_output><empty_output><jupyter_text>Panel 2B<jupyter_code>_, _ = plot_upset_plot(bulk, sc, opref, gtf, kind='transcript', novelty='Known')
calc_detection_stats(bulk, sc, ['Known'])
plot_detection_venn(bulk, sc, opref, transcript_nov='Known', \
                    sample='MB', cell_part='cell')
plot_detection_venn(bulk, sc, opref, transcript_nov='Known', \
                    sample='MB', cell_part='nucleus')
plot_detection_venn(bulk, sc, opref, transcript_nov='Known', \
                    sample='MT', cell_part='nucleus')<jupyter_output><empty_output><jupyter_text>Panel 2D<jupyter_code>adata = get_sc_adata()
opref = 'figures/gene'
sns.set_context('paper', font_scale=2)    
print(len(adata.obs.loc[adata.obs.leiden == '4'].index))
print(len(adata.obs.loc[adata.obs.leiden == '5'].index))
sc.pl.umap(adata, color='leiden', frameon=False, size=120, show=False)
plt.savefig('{}_umap_leiden.pdf'.format(opref), dpi=300, bbox_inches='tight')<jupyter_output>/Users/fairliereese/miniconda3/lib/python3.7/site-packages/anndata/_core/anndata.py:1154: FutureWarning: is_categorical is deprecated and will be removed in a future version.  Use is_categorical_dtype instead
  if is_string_dtype(df[key]) and not is_categorical(df[key])<jupyter_text>Panel 2E<jupyter_code># visualize the UMAP by different variables
sc.pl.umap(adata, color='short_leiden', frameon=False, size=120, show=False)
plt.savefig('{}_umap_short_leiden.pdf'.format(opref), dpi=300, bbox_inches='tight')<jupyter_output><empty_output><jupyter_text>Panel 2F<jupyter_code>genes = ['Mki67', 'Hmga2', 'Pax7', 'Igfbp5',
         'Col3a1', 'Col1a1', 'Myog', 'Mybph', 
         'Myh3', 'Rbm24']
for g in genes:
    sc.pl.umap(adata, color=g, frameon=False, size=120)
    plt.savefig('{}_umap_{}.pdf'.format(opref, g), dpi=300, bbox_inches='tight')<jupyter_output><empty_output>
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