synthesisAnalysis {FAMetA}

De novo synthesis analysis of fatty acids until 16 carbons.

Description

De novo synthesis analysis of fatty acids until 16 carbons.

Usage

synthesisAnalysis(
  fadata,
  R2Thr = 0.98,
  maxiter = 1000,
  maxconvergence = 100,
  D1 = NA,
  D2 = NA,
  P = NA,
  startpoints = 5,
  parameters = FAMetA::parameters,
  propagateD = TRUE,
  verbose = TRUE
)

Arguments

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.

Details

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.

Value

fadata list. Synthesis analysis results will be saved at the synthesis element of the fa list.

Author(s)

M Isabel Alcoriza-Balaguer <[e-mail]>

Examples

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)