diff --git a/examples/fully_coherent_search_using_MCMC.py b/examples/fully_coherent_search_using_MCMC.py
index 82fd4dd37425573a127c03e7580e7a2a2d956d12..72874c74e5b0fdc9270607f7a1a8d1b28f004aed 100644
--- a/examples/fully_coherent_search_using_MCMC.py
+++ b/examples/fully_coherent_search_using_MCMC.py
@@ -47,8 +47,8 @@ theta_prior = {'F0': {'type': 'unif',
                'Delta': Delta
                }
 
-ntemps = 1
-log10beta_min = -1
+ntemps = 2
+log10beta_min = -0.5
 nwalkers = 100
 nsteps = [300, 300]
 
@@ -57,6 +57,9 @@ mcmc = pyfstat.MCMCSearch(
     sftfilepattern='{}/*{}*sft'.format(outdir, label), theta_prior=theta_prior,
     tref=tref, minStartTime=tstart, maxStartTime=tend, nsteps=nsteps,
     nwalkers=nwalkers, ntemps=ntemps, log10beta_min=log10beta_min)
-mcmc.run(subtractions=[F0, F1])
+mcmc.transform_dictionary = dict(
+    F0=dict(subtractor=F0, symbol='$f-f^\mathrm{s}$'),
+    F1=dict(subtractor=F1, symbol='$\dot{f}-\dot{f}^\mathrm{s}$'))
+mcmc.run()
 mcmc.plot_corner(add_prior=True)
 mcmc.print_summary()
diff --git a/examples/grid_examples/grid_F0F1F2.py b/examples/grid_examples/grid_F0F1F2.py
index 7456e535a19bf9de2faea5ae348b898f72036cfe..d3583f1298b6ba14a95102b77d4fd11aba1f922f 100644
--- a/examples/grid_examples/grid_F0F1F2.py
+++ b/examples/grid_examples/grid_F0F1F2.py
@@ -3,8 +3,6 @@ import numpy as np
 import matplotlib.pyplot as plt
 from projection_matrix import projection_matrix
 
-plt.style.use('paper')
-
 F0 = 30.0
 F1 = 1e-10
 F2 = 0
diff --git a/examples/grid_examples/grided_frequency_search.py b/examples/grid_examples/grided_frequency_search.py
index 5e4a423ce8a080081de364bf058287d184df9b01..e8f5d55f1a362c79bb631d2ea2b5dd428d3550f7 100644
--- a/examples/grid_examples/grided_frequency_search.py
+++ b/examples/grid_examples/grided_frequency_search.py
@@ -2,8 +2,6 @@ import pyfstat
 import numpy as np
 import matplotlib.pyplot as plt
 
-plt.style.use('paper')
-
 F0 = 30.0
 F1 = 0
 F2 = 0
diff --git a/examples/other_examples/twoF_cumulative.py b/examples/other_examples/twoF_cumulative.py
index cd7f0426b7fc92a8244b17958877c3e8a1672d47..760fd23e90068ad589918e6a5694e568b0a31cdf 100644
--- a/examples/other_examples/twoF_cumulative.py
+++ b/examples/other_examples/twoF_cumulative.py
@@ -56,7 +56,7 @@ mcmc = pyfstat.MCMCSearch(
     sftfilepattern='data/*'+data_label+'*sft', theta_prior=theta_prior, tref=tref,
     minStartTime=tstart, maxStartTime=tend, nsteps=nsteps, nwalkers=nwalkers,
     ntemps=ntemps, log10beta_min=log10beta_min)
-mcmc.run(context='paper', subtractions=[30, -1e-10])
+mcmc.run()
 mcmc.plot_corner(add_prior=True)
 mcmc.print_summary()
 
diff --git a/examples/semi_coherent_directed_follow_up.py b/examples/semi_coherent_directed_follow_up.py
index 1ae81449b1e4c8f171559f73118366f07b485b63..e84976e34b6e28e68e9dcfe04d8067735843ed6e 100644
--- a/examples/semi_coherent_directed_follow_up.py
+++ b/examples/semi_coherent_directed_follow_up.py
@@ -2,8 +2,6 @@ import pyfstat
 import numpy as np
 import matplotlib.pyplot as plt
 
-plt.style.use('./paper-style.mplstyle')
-
 F0 = 30.0
 F1 = -1e-10
 F2 = 0
@@ -63,8 +61,8 @@ NstarMax = 1000
 Nsegs0 = 100
 fig, axes = plt.subplots(nrows=2, figsize=(3.4, 3.5))
 fig, axes = mcmc.run(
-    NstarMax=NstarMax, Nsegs0=Nsegs0, subtractions=[F0, F1], labelpad=0.01,
-    plot_det_stat=False, return_fig=True, context='paper', fig=fig,
+    NstarMax=NstarMax, Nsegs0=Nsegs0, labelpad=0.01,
+    plot_det_stat=False, return_fig=True, fig=fig,
     axes=axes)
 for ax in axes:
     ax.grid()
diff --git a/examples/semi_coherent_search_using_MCMC.py b/examples/semi_coherent_search_using_MCMC.py
index cd8d95acb64775b25a4140760bd3dceb07b3119d..1422fd344ac0191291832f2cd225d6e6eb06eb84 100644
--- a/examples/semi_coherent_search_using_MCMC.py
+++ b/examples/semi_coherent_search_using_MCMC.py
@@ -58,6 +58,9 @@ mcmc = pyfstat.MCMCSemiCoherentSearch(
     theta_prior=theta_prior, tref=tref, minStartTime=tstart, maxStartTime=tend,
     nsteps=nsteps, nwalkers=nwalkers, ntemps=ntemps,
     log10beta_min=log10beta_min)
+mcmc.transform_dictionary = dict(
+    F0=dict(subtractor=F0, symbol='$f-f^\mathrm{s}$'),
+    F1=dict(subtractor=F1, symbol='$\dot{f}-\dot{f}^\mathrm{s}$'))
 mcmc.run()
 mcmc.plot_corner(add_prior=True)
 mcmc.print_summary()
diff --git a/examples/using_initialisation.py b/examples/using_initialisation.py
index 5e7ea5e019f0d8b3abf155c41d861d6b7a0ad825..efe43364f0ea6ada232d6fbb972b39ad9550aef3 100644
--- a/examples/using_initialisation.py
+++ b/examples/using_initialisation.py
@@ -59,6 +59,6 @@ mcmc = pyfstat.MCMCSearch(
     nsteps=nsteps, nwalkers=nwalkers, ntemps=ntemps,
     log10beta_min=log10beta_min)
 mcmc.setup_initialisation(100, scatter_val=1e-10)
-mcmc.run(subtractions=[F0, F1])
+mcmc.run()
 mcmc.plot_corner(add_prior=True)
 mcmc.print_summary()