def is_one_gene(p):
'''Test to see if most mutations are due to single gene'''
counts = hit_matrix.ix[run.gene_sets[p]].sum(1).dropna().order()
with_top = hit_matrix.ix[run.gene_sets[p]].sum().clip_upper(1).sum()
without = hit_matrix.ix[run.gene_sets[p] -
{counts.idxmax()}].sum().clip_upper(1).sum()
return ((with_top - without) / without) > .5
meta_matrix = meta_matrix[size_filter(meta_matrix)]
s = Series({p: is_one_gene(p) for p in meta_matrix.index})
meta_matrix = meta_matrix.ix[s==False]
hit_matrix = hit_matrix[size_filter(hit_matrix)]
'''Add passing features to the Data Object'''
mut.features = meta_matrix.append(hit_matrix)
mut.compress()
mut.uncompress()
'''Save updated Data Object (with additional features field'''
mut.save()
mut.uncompress()
'''Draw pathway_plots for pathway level features'''
meta_features = [f for f in mut.features.index if f in run.gene_sets]
pathway_plot_folder = mut.path + '/Figures/PathwayPlots/'
if not os.path.isdir(pathway_plot_folder):
os.makedirs(pathway_plot_folder)
for i,p in enumerate(meta_features):
df = mut.df.ix[run.gene_sets[p]]
pathway_plot(df)
