From e04fcfcfe06377ec180125e54fe4f458b0747a76 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Wed, 13 Nov 2019 21:48:52 +0100 Subject: Improve README --- README.html | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) (limited to 'README.html') diff --git a/README.html b/README.html index f4b33afe..1e9d7932 100644 --- a/README.html +++ b/README.html @@ -367,7 +367,7 @@ summary {

mkin

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Build Status codecov

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Build Status codecov

The R package mkin provides calculation routines for the analysis of chemical degradation data, including multicompartment kinetics as needed for modelling the formation and decline of transformation products, or if several compartments are involved.

Installation

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  • As of version 0.9-39, fitting of several models to several datasets, optionally in parallel, is supported, see for example plot.mmkin.
  • Model solution (forward modelling) in the function mkinpredict is performed either using the analytical solution for the case of parent only degradation, an eigenvalue based solution if only simple first-order (SFO) or SFORB kinetics are used in the model, or using a numeric solver from the deSolve package (default is lsoda).
  • If a C compiler is installed, the kinetic models are compiled from automatically generated C code, see vignette compiled_models. The autogeneration of C code was inspired by the ccSolve package. Thanks to Karline Soetaert for her work on that.
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  • By default, kinetic rate constants and kinetic formation fractions are transformed internally using transform_odeparms so their estimators can more reasonably be expected to follow a normal distribution. This has the side effect that no constraints are needed in the optimisation. Thanks to René Lehmann for the nice cooperation on this, especially the isometric logration transformation that is now used for the formation fractions.
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  • By default, kinetic rate constants and kinetic formation fractions are transformed internally using transform_odeparms so their estimators can more reasonably be expected to follow a normal distribution. This has the side effect that no constraints are needed in the optimisation. Thanks to René Lehmann for the nice cooperation on this, especially the isometric log-ratio transformation that is now used for the formation fractions.
  • A side effect of this is that when parameter estimates are backtransformed to match the model definition, confidence intervals calculated from standard errors are also backtransformed to the correct scale, and will not include meaningless values like negative rate constants or formation fractions adding up to more than 1, which can not occur in a single experiment with a single defined radiolabel position.
  • The usual one-sided t-test for significant difference from zero is nevertheless shown based on estimators for the untransformed parameters.
  • Summary and plotting functions. The summary of an mkinfit object is in fact a full report that should give enough information to be able to approximately reproduce the fit with other tools.
  • The chi-squared error level as defined in the FOCUS kinetics guidance (see below) is calculated for each observed variable.
  • When a metabolite decline phase is not described well by SFO kinetics, SFORB kinetics can be used for the metabolite.
  • Three different error models can be selected using the argument error_model to the mkinfit function.
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  • Iteratively reweighted least squares fitting is now obsolete, and the variance by variable error model should now be specified as error_model = "obs".
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  • The ‘variance by variable’ error model which is often fitted using Iteratively Reweighted Least Squares (IRLS) should now be specified as error_model = "obs".
  • A two-component error model similar to the one proposed by Rocke and Lorenzato can be selected using the argument error_model = "tc".
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    Development

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    Contributions are welcome! Your mkin fork is just a mouse click away… The master branch on github should always be in good shape, I implement new features in separate branches now. If you prefer subversion, project members for the r-forge project are welcome as well. Generally, the source code of the latest CRAN version should be available there. You can also browse the source code at cgit.jrwb.de/mkin.

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    Contributions are welcome!

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