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Experience and experiments with Matlab...

"What a 'user-friendly' application!" This was my first impression when I first installed Matlab on my computer and it started up with screen with a command prompt and basically nothing else. But I gradually began to appreciate the flexibility and power of data analysis and the relative ease of programming of Matlab. I wrote Matlab code for fun and for developing applications for myself or my PhD students. Below I give you a selection of the utilities I developed.

regressContourPlot

You can fit a linear regression line on 2D histogram data, i.e. if you already don't have the original data set containing two measurements for each data point.


Syntax:[r,slope,intercept]=regressContourPlot(twoDHist,xScale,yScale)


Help is available by typing "help regressContourPlot" at the Matlab command prompt.


Download P-file; regressContourPlot.p

createTrend

A trend line can be created from a data set containing two measurements for each data point. In order to create a trend line the X range is divided into the given number of bins and the mean of the Y variable in each bin is calculated.


Syntax: createTrend(XYData) or [trendline,binsX. freq]= createTrend(XYData,XMin,XMax,NumBins)


Help is available by typing "help createTrend" at the Matlab command prompt.


Download P-file: createTrend.p

createContour

You can generate a 2D histogram (contour plot) interactively from a set of data containing two measurements for each data point.


Syntax: createContour(XYData)


Help is available by typing "help createContour" at the Matlab command prompt.


Download P-file: createContour.p

Fitting the Hill equation to data points: fithill

The program fits the Hill equation to measurement data. The Hill equation has the following forms depending on whether IC50 or EC50 is fitted on concentrations on a linear or logarithmic scale:

The program can be run in GUI mode or command-prompt mode.

  • GUI mode: In order to run the program in GUI mode start it without input arguments, i.e. type "fithill" at the Matlab command prompt.
  • command prompt mode:[fittedParameters,rsquared]=fithill(xdata,ydata,PropName,PropVal1,PropVal2,...) OR [fittedParameters,rsquared,fittedN]=fithill(xdata,ydata,PropName,PropVal1,ProbVal2,...)
    Output argument 'fittedN' is required if propName 'logconctoplot' is given among the arguments.

    xdata = LOG10 of the drug concentrations (LOG10!!!!!!!)
    ydata = cell numbers or absorbances
    fittedParameters = structure with the following fields:
    fittedParameters.min
    fittedParameters.max
    fittedParameters.kd
    fittedParameters.n
    fittedParameters.minCI
    fittedParameters.maxCI
    fittedParameters.kdCI
    fittedParameters.nCI

    rsquared = goodness of fit
    fittedN = calculated curve using the best fit parameters at the concentrations given in the argument list after 'logconctoplot'

The following parameters are followed by two numbers:
Parameter name
 Parameter value 1
 Parameter value 2
 
ic50
 1=to fit, 0=fixed parameter
if first parameter is 1 -> initial value
if first parameter is 0 -> value of the fixed parameter
 
 ec50
 same as above
 same as above
 
 n
 same as above
 same as above
 
 min
 same as above
 same as above
 
 max
 same as above
 same as above
 

If 'ec50' and 'ic50' is not followed by a numeric parameter, it only specifies whether a decreasing or increasing curve is to be fitted.


The following parameters are followed by one number or variable:
confint- confidence bounds will be calculated at the % level specified by the number following 'confint'
logconctoplot - LOG10concentrations (!!!!) at which fittedN will be calculated using the fit parameters


The following parameters aren't followed by anything.
ver - version of the program
version - same as above

help - displays this help


Download: fithill.p