def peak_tag_corr(df):
#Preprocessing
peak_score = pd.DataFrame(df['Peak Score'])
tag_data = pd.DataFrame([df.iloc[:, -i] for i in range(1, 7)]).T
data_to_plot = pd.concat([peak_score, tag_data], axis=1)
log_data = np.log10(data_to_plot)
#Instantiating graph variables
figsize = (12, 6)
fig_name = 'Peak score for each motif tag count with log scaling'
axis_names = [
'Peak Score', 'CCGTCC tag count (in bp)', 'ATGTCA tag count (in bp)',
'AGTTCC tag count (in bp)', 'AGTCAA tag count (in bp)',
'GTCCGC tag count (in bp)', 'GTAGAG tag count (in bp)'
]
cols_to_graph = list(range(7))
#Create Grapher object and make a big scatter
grapher = Grapher(log_data, figsize)
#grapher = Grapher(data_to_plot, figsize)
grapher.big_scatter(cols_to_graph,
shape=(2, 3),
fixed_y=0,
axis_names=axis_names,
fig_name=fig_name)
plt.show()
grapher.fig.savefig(out_dir, bbox_inches="tight", dpi=600)
