Figure 4.
Retrospective relapse detection using stable and gained mutations between diagnosis and relapse. Polynomic curve interpolation based on stable mutations (n = 132), which are present at diagnosis and relapse, and gained mutations (n = 48), which are only present at relapse. f(xs)=0.98+0.4xs+0.06xs2+0.004xs3−0.0001xs4−0.0000015xs5, f(xG)=0.97+0.7xG+0.2xG2+0.03xG3−0.002xG4−0.00005xG5.

Retrospective relapse detection using stable and gained mutations between diagnosis and relapse. Polynomic curve interpolation based on stable mutations (n = 132), which are present at diagnosis and relapse, and gained mutations (n = 48), which are only present at relapse. f(xs)=0.98+0.4xs+0.06xs2+0.004xs30.0001xs40.0000015xs5, f(xG)=0.97+0.7xG+0.2xG2+0.03xG30.002xG40.00005xG5.

or Create an Account

Close Modal
Close Modal