View source: R/metabolicanalysis.R
synthesisAnalysis | R Documentation |
De novo synthesis analysis of fatty acids until 16 carbons.
synthesisAnalysis( fadata, R2Thr = 0.98, maxiter = 1000, maxconvergence = 100, D1 = NA, D2 = NA, P = NA, startpoints = 5, parameters = FAMetA::parameters, propagateD = TRUE, verbose = TRUE )
fadata |
fadata obtained from the msbatch with searchFAisotopes function or read from csv file with readfadatafile function. |
R2Thr |
positive numeric between 0 and 1 specifying the minimum R2 allowed for fits. |
maxiter |
parameter passed to nls.control. Positive integer specifying the maximum number of iterations allowed. |
maxconvergence |
positive integer specifying the maximum number of successes before choosing the winning model. |
D1 |
positive numeric between 0 and 1 specifying the contribution of acetate M+1. If NA it is estimated. |
D2 |
positive numeric between 0 and 1 specifying the contribution of acetate M+2. If NA it is estimated. |
P |
overdispersion parameter. If NA it is estimated (quasi-multinomial distribution). If set to 0, no overdispersion is assumed (multinomial distribution). |
startpoints |
positive integer specifying the number of starting points for each parameter to be estimated. |
parameters |
parameters to be estimated for each fatty acid. It can be modified to change them or to add new fatty acids. |
propagateD |
logical. If TRUE, unsaturated fatty acids use estimated D0, D1,D2 and P values for saturated fatty acids (14:0 for FA shorter than 16C and 16:0 for FA with 16C.). |
verbose |
print information messages. |
Synthesis analysis will model FA data for FA up to 16 carbons to estimate 13C-tracer contribution to the acetyl-CoA pool for FA synthesis (D) and the FA fraction that has been synthesized de novo. D0, D1 and D2 represent the contribution of M+0, M+1 and M+2 acetate, respectively, and P (phi) is the overdispersion parameter of the quasi-multinomial distribution. D0, D1, D2 can also be fixed if they are known. This is particularly useful in case inhibitors have been used as they could reduce S below the confidence interval and thus, S and D parameters could be misestimated.
fadata list. Synthesis analysis results will be saved at the synthesis element of the fa list.
M Isabel Alcoriza-Balaguer <maribel_alcoriza@iislafe.es>
ssdata <- dataCorrection(ssexamplefadata, blankgroup="Blank") ssdata <- synthesisAnalysis(ssdata, R2Thr = 0.95, maxiter = 1e3, maxconvergence = 100, startpoints = 5) ## Not run: fadata <- dataCorrection(examplefadata, blankgroup = "Blank") fadata <- synthesisAnalysis(fadata, R2Thr = 0.95, maxiter = 1e3, maxconvergence = 100, startpoints = 5) # If inhibitors have been used, make sure D2 has not been underestimated. If so, # D2 could be set as the one calculated for 13-Glc Control samples to improve # the results: # D2 <- fadata$synthesis$results$D2[fadata$synthesis$results$FA == "FA(16:0)"] # fadata$synthesis$results$Group[fadata$synthesis$results$FA == "FA(16:0)"] # D2[4:12] <- rep(mean(D2[1:3])) # relaunch synthesis analysis fixing D2 # fadata <- synthesisAnalysis(fadata, R2Thr = 0.95, maxiter = 1e3, # maxconvergence = 100, startpoints = 5, D2 = D2) ## End(Not run)
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