Actually I know that they set the algorithm in a way that 

Only proteins with fold changes bigger than [fcCutoff * (1 - fcTolerance) or smaller than 1/(fcCutoff * (1 - fcTolerance))] will be used for curve fitting. Additionally, the proteins fulfilling the fcCutoff criterion without tolerance will be marked in the output column meets_FC_requirement.

I tried to set the fcCutoff = 1,fcTolerance = 0

because I thought 1*1 =1 for bigger situation and 1/1 will be 1 so I will set them somehow to a number that I will be able to plot the curve for all proteins. 

and I got the following error 

Fitting 3663 individual dose response curves to 3663 proteins.
Error in fitDRCurve(protID = unique(fcSplit[[i]]$id), expName = unique(fcSplit[[i]]$experiment),  : 
  task 557 failed - "missing value where TRUE/FALSE needed"

I want to obtain the curve fitting for all proteins and not only those that met the above criteria , how can I do it?

I also would like to know the fcCutoff and fcTolerance they use or how to select a optimal one. 

What I take their data example and use analyzeTPPCCR which automatically do all the steps.

Many thanks in advance again

Dear Mohammad,

yes, if you want to obtain dose response curves and pEC50 values for all proteins, it is possible to set fcCutoff = 1. Then, all proteins for which the fold change increases at the highest drug concentration will be marked as 'stabilized' and all others as 'destabilized'. The transformation then takes place as shown in Box 3 of Franken et al. (2015). Nature Protocols, 10(10), 1567–1593. Please be aware that many of the proteins now marked as stabilized or destabilized may not be truly affected by the drug and that the apparent increase or decrease is due to random variation. It is advisable to carefully inspect the fitted curves and apply appropriate filters on the goodness-of-fit (measured here by the R^2 value) before further processing.

The default thresholds used are fcCutoff = 1.5 (according to Box 3 in the paper) and fcTolerance = 0.1. Please see also ?analyzeTPPCCR for all the default values and further details.

The bug you reported has been fixed. It originated from a division by 0 during the transformation with fcCutoff = 1.