diff options
Diffstat (limited to 'vignettes')
| -rw-r--r-- | vignettes/examples-L1_SFO_plots.pdf | bin | 6265 -> 0 bytes | |||
| -rw-r--r-- | vignettes/examples.Rnw | 106 | ||||
| -rw-r--r-- | vignettes/examples.pdf | bin | 176985 -> 281843 bytes | |||
| -rw-r--r-- | vignettes/mkin.pdf | bin | 162839 -> 162843 bytes | |||
| -rw-r--r-- | vignettes/run.bat | 5 | 
5 files changed, 60 insertions, 51 deletions
| diff --git a/vignettes/examples-L1_SFO_plots.pdf b/vignettes/examples-L1_SFO_plots.pdfBinary files differ deleted file mode 100644 index d34116fe..00000000 --- a/vignettes/examples-L1_SFO_plots.pdf +++ /dev/null diff --git a/vignettes/examples.Rnw b/vignettes/examples.Rnw index 340d75f7..6f3cfc9d 100644 --- a/vignettes/examples.Rnw +++ b/vignettes/examples.Rnw @@ -108,8 +108,7 @@ is checked.  <<L1_FOMC, echo=TRUE>>=
  m.L1.FOMC <- mkinfit(FOMC, FOCUS_2006_L1_mkin, quiet=TRUE)
 -s.m.L1.FOMC <- summary(m.L1.FOMC)
 -s.m.L1.FOMC$errmin
 +summary(m.L1.FOMC)
  @
  Due to the higher number of parameters, and the lower number of degrees of freedom
 @@ -196,7 +195,6 @@ m.L2.DFOP <- mkinfit(DFOP, FOCUS_2006_L2_mkin,    parms.ini = c(k1 = 1, k2 = 0.01, g = 0.8),
    quiet=TRUE)
  plot(m.L2.DFOP)
 -summary(m.L2.DFOP)
  s.m.L2.DFOP <- summary(m.L2.DFOP)
  s.m.L2.DFOP$errmin
  @
 @@ -219,7 +217,7 @@ FOCUS_2006_L3_mkin <- mkin_wide_to_long(FOCUS_2006_L3)  SFO model, summary and plot:
  <<L3_SFO, echo=TRUE, fig=TRUE>>=
 -m.L3.SFO <- mkinfit(SFO, FOCUS_2006_L3_mkin, quiet=TRUE)
 +m.L3.SFO <- mkinfit(SFO, FOCUS_2006_L3_mkin, quiet = TRUE)
  summary(m.L3.SFO)
  plot(m.L3.SFO)
  @
 @@ -230,7 +228,7 @@ does not fit very well.  The FOMC model performs better:
  <<L3_FOMC, echo=TRUE, fig=TRUE>>=
 -m.L3.FOMC <- mkinfit(FOMC, FOCUS_2006_L3_mkin, quiet=TRUE)
 +m.L3.FOMC <- mkinfit(FOMC, FOCUS_2006_L3_mkin, quiet = TRUE)
  plot(m.L3.FOMC)
  s.m.L3.FOMC <- summary(m.L3.FOMC)
  s.m.L3.FOMC$errmin
 @@ -243,7 +241,7 @@ Fitting the four parameter DFOP model further reduces the $\chi^2$ error level  considerably:
  <<L3_DFOP, echo=TRUE, fig=TRUE>>=
 -m.L3.DFOP <- mkinfit(DFOP, FOCUS_2006_L3_mkin, quiet=TRUE)
 +m.L3.DFOP <- mkinfit(DFOP, FOCUS_2006_L3_mkin, quiet = TRUE)
  plot(m.L3.DFOP)
  s.m.L3.DFOP <- summary(m.L3.DFOP)
  s.m.L3.DFOP$errmin
 @@ -267,7 +265,7 @@ FOCUS_2006_L4_mkin <- mkin_wide_to_long(FOCUS_2006_L4)  SFO model, summary and plot:
  <<L4_SFO, echo=TRUE, fig=TRUE>>=
 -m.L4.SFO <- mkinfit(SFO, FOCUS_2006_L4_mkin, quiet=TRUE)
 +m.L4.SFO <- mkinfit(SFO, FOCUS_2006_L4_mkin, quiet = TRUE)
  summary(m.L4.SFO)
  plot(m.L4.SFO)
  @
 @@ -278,7 +276,7 @@ fits very well.  The FOMC model for comparison
  <<L4_FOMC, echo=TRUE, fig=TRUE>>=
 -m.L4.FOMC <- mkinfit(FOMC, FOCUS_2006_L4_mkin, quiet=TRUE)
 +m.L4.FOMC <- mkinfit(FOMC, FOCUS_2006_L4_mkin, quiet = TRUE)
  plot(m.L4.FOMC)
  s.m.L4.FOMC <- summary(m.L4.FOMC)
  s.m.L4.FOMC$errmin
 @@ -287,9 +285,6 @@ s.m.L4.FOMC$errmin  The error level at which the $\chi^2$ test passes is slightly lower for the FOMC 
  model. However, the difference appears negligible.
 -\bibliographystyle{plainnat}
 -\bibliography{references}
 -
  \section{Kinetic evaluations for parent and metabolites}
  \subsection{Laboratory Data for example compound Z}
 @@ -300,15 +295,16 @@ report, p.350  <<FOCUS_2006_Z_data, echo=TRUE, eval=TRUE>>=
  LOD = 0.5
  FOCUS_2006_Z = data.frame(
 -  t = c(0, 0.04, 0.125, 0.29, 0.54, 1, 2, 3, 4, 7, 10, 14, 21, 42, 61, 96, 124),
 -  Z0 = c(100, 81.7, 70.4, 51.1, 41.2, 6.6, 4.6, 3.9, 4.6, 4.3, 6.8, 2.9, 3.5,
 -             5.3, 4.4, 1.2, 0.7),
 -  Z1 = c(0, 18.3, 29.6, 46.3, 55.1, 65.7, 39.1, 36, 15.3, 5.6, 1.1, 1.6, 0.6,
 -         0.5 * LOD, NA, NA, NA),
 -  Z2 = c(0, NA, 0.5 * LOD, 2.6, 3.8, 15.3, 37.2, 31.7, 35.6, 14.5, 0.8, 2.1,
 -         1.9, 0.5 * LOD, NA, NA, NA),
 -  Z3 = c(0, NA, NA, NA, NA, 0.5 * LOD, 9.2, 13.1, 22.3, 28.4, 32.5, 25.2, 17.2,
 -         4.8, 4.5, 2.8, 4.4))
 +  t = c(0, 0.04, 0.125, 0.29, 0.54, 1, 2, 3, 4, 7, 10, 14, 21, 
 +        42, 61, 96, 124),
 +  Z0 = c(100, 81.7, 70.4, 51.1, 41.2, 6.6, 4.6, 3.9, 4.6, 4.3, 6.8, 
 +         2.9, 3.5, 5.3, 4.4, 1.2, 0.7),
 +  Z1 = c(0, 18.3, 29.6, 46.3, 55.1, 65.7, 39.1, 36, 15.3, 5.6, 1.1, 
 +         1.6, 0.6, 0.5 * LOD, NA, NA, NA),
 +  Z2 = c(0, NA, 0.5 * LOD, 2.6, 3.8, 15.3, 37.2, 31.7, 35.6, 14.5, 
 +         0.8, 2.1, 1.9, 0.5 * LOD, NA, NA, NA),
 +  Z3 = c(0, NA, NA, NA, NA, 0.5 * LOD, 9.2, 13.1, 22.3, 28.4, 32.5, 
 +         25.2, 17.2, 4.8, 4.5, 2.8, 4.4))
  FOCUS_2006_Z_mkin <- mkin_wide_to_long(FOCUS_2006_Z)
  @
 @@ -320,10 +316,9 @@ with formation and decline of metabolite Z1 and the pathway from parent  directly to sink included (default in mkin).
  <<FOCUS_2006_Z_fits_1, echo=TRUE, fig=TRUE>>=
 -debug(mkinmod)
  Z.2a <- mkinmod(Z0 = list(type = "SFO", to = "Z1"),
                  Z1 = list(type = "SFO"))
 -m.Z.2a <- mkinfit(Z.2a, FOCUS_2006_Z_mkin)
 +m.Z.2a <- mkinfit(Z.2a, FOCUS_2006_Z_mkin, quiet = TRUE)
  summary(m.Z.2a, data = FALSE)
  plot(m.Z.2a)
  @
 @@ -340,7 +335,7 @@ A similar result can be obtained when formation fractions are used in the model  Z.2a.ff <- mkinmod(Z0 = list(type = "SFO", to = "Z1"),
                  Z1 = list(type = "SFO"), use_of_ff = "max")
 -m.Z.2a.ff <- mkinfit(Z.2a.ff, FOCUS_2006_Z_mkin)
 +m.Z.2a.ff <- mkinfit(Z.2a.ff, FOCUS_2006_Z_mkin, quiet = TRUE)
  summary(m.Z.2a.ff, data = FALSE)
  plot(m.Z.2a.ff)
  @
 @@ -355,9 +350,11 @@ are used.  <<FOCUS_2006_Z_fits_3, echo=TRUE, fig=TRUE>>=
  Z.3 <- mkinmod(Z0 = list(type = "SFO", to = "Z1", sink = FALSE),
 -                Z1 = list(type = "SFO"))
 -m.Z.3 <- mkinfit(Z.3, FOCUS_2006_Z_mkin, parms.ini = c(k_Z0_Z1 = 0.5))
 -m.Z.3 <- mkinfit(Z.3, FOCUS_2006_Z_mkin, solution_type = "deSolve")
 +               Z1 = list(type = "SFO"))
 +m.Z.3 <- mkinfit(Z.3, FOCUS_2006_Z_mkin, parms.ini = c(k_Z0_Z1 = 0.5), 
 +                quiet = TRUE)
 +m.Z.3 <- mkinfit(Z.3, FOCUS_2006_Z_mkin, solution_type = "deSolve", 
 +                 quiet = TRUE)
  summary(m.Z.3, data = FALSE)
  plot(m.Z.3)
  @
 @@ -374,7 +371,8 @@ solution can be chosen, at the cost of a bit more computing time.  Z.4a <- mkinmod(Z0 = list(type = "SFO", to = "Z1", sink = FALSE),
                  Z1 = list(type = "SFO", to = "Z2"),
                  Z2 = list(type = "SFO"))
 -m.Z.4a <- mkinfit(Z.4a, FOCUS_2006_Z_mkin, parms.ini = c(k_Z0_Z1 = 0.5))
 +m.Z.4a <- mkinfit(Z.4a, FOCUS_2006_Z_mkin, parms.ini = c(k_Z0_Z1 = 0.5),
 +                  quiet = TRUE)
  summary(m.Z.4a, data = FALSE)
  plot(m.Z.4a)
  @
 @@ -391,7 +389,7 @@ Z.5 <- mkinmod(Z0 = list(type = "SFO", to = "Z1", sink = FALSE),                  Z1 = list(type = "SFO", to = "Z2", sink = FALSE),
                  Z2 = list(type = "SFO"))
  m.Z.5 <- mkinfit(Z.5, FOCUS_2006_Z_mkin, 
 -                  parms.ini = c(k_Z0_Z1 = 0.5, k_Z1_Z2 = 0.2))
 +                  parms.ini = c(k_Z0_Z1 = 0.5, k_Z1_Z2 = 0.2), quiet = TRUE)
  summary(m.Z.5, data = FALSE)
  plot(m.Z.5)
  @
 @@ -404,7 +402,8 @@ Z.FOCUS <- mkinmod(Z0 = list(type = "SFO", to = "Z1", sink = FALSE),                  Z2 = list(type = "SFO", to = "Z3"),
                  Z3 = list(type = "SFO"))
  m.Z.FOCUS <- mkinfit(Z.FOCUS, FOCUS_2006_Z_mkin, 
 -                  parms.ini = c(k_Z0_Z1 = 0.5, k_Z1_Z2 = 0.2, k_Z2_Z3 = 0.3))
 +                  parms.ini = c(k_Z0_Z1 = 0.5, k_Z1_Z2 = 0.2, k_Z2_Z3 = 0.3),
 +                  quiet = TRUE)
  summary(m.Z.FOCUS, data = FALSE)
  plot(m.Z.FOCUS)
  @
 @@ -420,16 +419,14 @@ mkinresplot(m.Z.FOCUS, "Z2", lpos = "bottomright")  mkinresplot(m.Z.FOCUS, "Z3", lpos = "bottomright")
  @
 -
  As the FOCUS report states, there is a certain tailing of the time course of metabolite 
  Z3. Also, the time course of the parent compound is not fitted very well using the 
  SFO model, as residues at a certain low level remain.
  Therefore, an additional model is offered here, using the single first-order 
 -reversible binding (SFORB) model for metabolite Z3. However, the $\chi^2$ error 
 -level is higher for metabolite Z3 using this model, the covariance matrix is
 -not returned, and graphically the fit is not significantly improved. Therefore,
 -this appears to be a case of overparamterisation.
 +reversible binding (SFORB) model for metabolite Z3. As expected, the $\chi^2$
 +error level is lower for metabolite Z3 using this model and the graphical 
 +fit for Z3 is improved. However, the covariance matrix is not returned.
  <<FOCUS_2006_Z_fits_7, echo=TRUE, fig=TRUE>>=
  Z.mkin.1 <- mkinmod(Z0 = list(type = "SFO", to = "Z1", sink = FALSE),
 @@ -437,18 +434,20 @@ Z.mkin.1 <- mkinmod(Z0 = list(type = "SFO", to = "Z1", sink = FALSE),                  Z2 = list(type = "SFO", to = "Z3"),
                  Z3 = list(type = "SFORB"))
  m.Z.mkin.1 <- mkinfit(Z.mkin.1, FOCUS_2006_Z_mkin, 
 -                  parms.ini = c(k_Z0_Z1 = 0.5, k_Z1_Z2 = 0.3, k_Z2_Z3 = 0.2))
 +                  parms.ini = c(k_Z0_Z1 = 0.5, k_Z1_Z2 = 0.3, k_Z2_Z3 = 0.2), 
 +                  quiet = TRUE)
  summary(m.Z.mkin.1, data = FALSE)
  plot(m.Z.mkin.1)
  @
 -On the other hand, the model fit for the parent compound can be improved by
 -using the SFORB model.
 +Therefore, a further stepwise model building is performed starting from the
 +stage of parent and one metabolite, starting from the assumption that the model
 +fit for the parent compound can be improved by using the SFORB model.
  <<FOCUS_2006_Z_fits_8, echo=TRUE, fig=TRUE>>=
  Z.mkin.2 <- mkinmod(Z0 = list(type = "SFORB", to = "Z1", sink = FALSE),
                  Z1 = list(type = "SFO"))
 -m.Z.mkin.2 <- mkinfit(Z.mkin.2, FOCUS_2006_Z_mkin)
 +m.Z.mkin.2 <- mkinfit(Z.mkin.2, FOCUS_2006_Z_mkin, quiet = TRUE)
  summary(m.Z.mkin.2, data = FALSE)
  plot(m.Z.mkin.2)
  @
 @@ -460,7 +459,7 @@ Then, metabolite Z2 is added.  Z.mkin.3 <- mkinmod(Z0 = list(type = "SFORB", to = "Z1", sink = FALSE),
                  Z1 = list(type = "SFO", to = "Z2"),
                  Z2 = list(type = "SFO"))
 -m.Z.mkin.3 <- mkinfit(Z.mkin.3, FOCUS_2006_Z_mkin)
 +m.Z.mkin.3 <- mkinfit(Z.mkin.3, FOCUS_2006_Z_mkin, quiet = TRUE)
  summary(m.Z.mkin.3, data = FALSE)
  plot(m.Z.mkin.3)
  @
 @@ -474,18 +473,33 @@ Z.mkin.4 <- mkinmod(Z0 = list(type = "SFORB", to = "Z1", sink = FALSE),                  Z2 = list(type = "SFO", to = "Z3"),
                  Z3 = list(type = "SFO"))
  m.Z.mkin.4 <- mkinfit(Z.mkin.4, FOCUS_2006_Z_mkin, 
 -  parms.ini = c(k_Z1_Z2 = 0.05))
 +  parms.ini = c(k_Z1_Z2 = 0.05), quiet = TRUE)
  summary(m.Z.mkin.4, data = FALSE)
  plot(m.Z.mkin.4)
  @
 -The error level of the fit, but especially of metabolite Z3, can 
 -be improved if the SFORB model is chosen for this metabolite, as this 
 -model is capable of representing the tailing of the metabolite 
 -decline phase.
 +The error level of the fit, but especially of metabolite Z3, can be improved if
 +the SFORB model is chosen for this metabolite, as this model is capable of
 +representing the tailing of the metabolite decline phase.
 +
 +Using the SFORB additionally for Z1 or Z2 did not further improve the result.
 +Therefore, the model \texttt{Z.mkin.5} is proposed as the best-fit model
 +for the dataset from Appendix 7 of the FOCUS report.
 +
 +<<FOCUS_2006_Z_fits_11, echo=TRUE, fig=TRUE>>=
 +Z.mkin.5 <- mkinmod(Z0 = list(type = "SFORB", to = "Z1", sink = FALSE),
 +                Z1 = list(type = "SFO", to = "Z2", sink = FALSE),
 +                Z2 = list(type = "SFO", to = "Z3"),
 +                Z3 = list(type = "SFORB"))
 +m.Z.mkin.5 <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin, 
 +  parms.ini = c(k_Z1_Z2 = 0.2), quiet = TRUE)
 +summary(m.Z.mkin.5, data = FALSE)
 +plot(m.Z.mkin.5)
 +@
 +
 +\bibliographystyle{plainnat}
 +\bibliography{references}
 -Using the SFORB additionally for Z1 or Z2 did not further improve
 -the result.
  \end{document}
  % vim: set foldmethod=syntax:
 diff --git a/vignettes/examples.pdf b/vignettes/examples.pdfBinary files differ index 92375460..3bd0c37e 100644 --- a/vignettes/examples.pdf +++ b/vignettes/examples.pdf diff --git a/vignettes/mkin.pdf b/vignettes/mkin.pdfBinary files differ index 9738230e..073e3610 100644 --- a/vignettes/mkin.pdf +++ b/vignettes/mkin.pdf diff --git a/vignettes/run.bat b/vignettes/run.bat deleted file mode 100644 index c28c6663..00000000 --- a/vignettes/run.bat +++ /dev/null @@ -1,5 +0,0 @@ -R.exe -e "Sweave('mkin.Rnw', stylepath=FALSE)"
 -pdflatex.exe mkin
 -bibtex.exe mkin
 -pdflatex.exe mkin
 -pdflatex.exe mkin
 | 
