In the introduction we have analysed a IC50 input file. We performed a full analysis that is we analyse all associations between all drugs and all features. This may take a while and sometimes one is just interested in a single drug or a sub set of drugs. In this notebook, we show how to restrict the analysis.
%pylab inline
matplotlib.rcParams['figure.figsize'] = (10,6)
Populating the interactive namespace from numpy and matplotlib
As before, we create an ANOVA instance. Pur input IC50 will be the test file
from gdsctools import ANOVA, ic50_test
an = ANOVA(ic50_test)
Drugs are stored in the drugIds in case you forgot the drug you are interested in.. eg. the first drug identifer is
drug_name = an.drugIds[0]
results = an.anova_one_drug(drug_name)
[-------- 21% ] 10 of 47 complete in 0.0 sec[---------------- 42% ] 20 of 47 complete in 0.1 sec[-----------------63%---- ] 30 of 47 complete in 0.1 sec[-----------------85%------------ ] 40 of 47 complete in 0.2 sec[-----------------100%-----------------] 47 of 47 complete in 0.2 sec
Now, you can create an HTML report or simply call one of the volcano plot
results.volcano()
from gdsctools.report import ReportMain
from gdsctools.volcano import VolcanoANOVAJS
v = VolcanoANOVAJS(results)
html = v.render_drug(999)
report = ReportMain(template_filename="volcano_standalone.html")
Created directory report
report.jinja['volcano_jsdata'] = html
report.write()
from IPython.display import HTML
display(HTML('<iframe src="report/index.html" width="100%" height="600px"></iframe>'))