DTA.dynamic.generate: Simulation of DTA experiments upon perturbation
In DTA: Dynamic Transcriptome Analysis

Description Usage Arguments Value Author(s) References Examples

DTA.dynamic.generate produces the phenotype matrix and the matrix containing the simulated data according to the given parameters.

DTA.dynamic.generate(duration = 60,lab.duration = 6,tnumber = NULL,plabel = NULL,nrgenes = 5000,mediantime.halflives = 12,mediantime.synthesisrates = 18,n = 1,ccl = NULL,check = TRUE,plots = FALSE,save.plots = FALSE,folder = NULL,condition = "",addformat = NULL,sdnoise = 0.075,nobias = FALSE,unspecific.LtoU = 0,unspec.LtoU.weighted = FALSE,unspecific.UtoL = 0,unspec.UtoL.weighted = FALSE,mu.values.mat = NULL,mu.breaks.mat = NULL,lambda.values.mat = NULL,lambda.breaks.mat = NULL,truehalflives = NULL,truesynthesisrates = NULL,genenames = NULL)

`duration`	duration of the whole time course (min)
`lab.duration`	labeling duration for single experiments (min)
`tnumber`	Integer vector containing the number of uridine residues for each gene. If NULL, tnumber is sampled from an F-distribution within the function.
`plabel`	The labeling efficiency. If NULL, plabel is set to 0.005 within the function. For details, see supplemental material of Sun et al. (see references).
`nrgenes`	The number of genes the simulated experiment will have (will be cropped if it exceeds the length of tnumber).
`mediantime.halflives`	the median of the half life distribution
`mediantime.synthesisrates`	the median of the synthesis rates distribution (counts/cell/cellcycle)
`n`	the number of cells N(0)
`ccl`	The cell cycle length (in minutes).
`check`	if check=TRUE, control messages will be generated
`plots`	if plots = TRUE, control plots will be plotted
`save.plots`	if save.plots = TRUE, control plots will be saved
`folder`	folder, where to save the plots
`condition`	to be added to the plotnames
`addformat`	additional fileformat for plots to be saved
`sdnoise`	The amount of measurement noise (proportional to expression strength).
`nobias`	Should a labeling bias be added?
`unspecific.LtoU`	Proportion of labeled RNAs that unspecifically end up in the unlabeled fraction.
`unspec.LtoU.weighted`	Should unspecific proportion of labeled to unlabeled depend linearly on the length of the RNA?
`unspecific.UtoL`	Proportion of unlabeled RNAs that unspecifically end up in the labeled fraction.
`unspec.UtoL.weighted`	Should unspecific proportion of unlabeled to labeled depend linearly on the length of the RNA?
`mu.values.mat`	if the data should be generated using given synthesis rates, this matrix must contain the respective values for each gene
`mu.breaks.mat`	timepoints of synthesis rate changes, this matrix must contain the respective values for each gene, only needed when mu.values.mat is given (one column less than mu.values.mat)
`lambda.values.mat`	if the data should be generated using given decay rates, this matrix must contain the respective values for each gene
`lambda.breaks.mat`	timepoints of decay rate changes, this matrix must contain the respective values for each gene, only needed when lambda.values.mat is given (one column less than lambda.values.mat)
`truehalflives`	If the data should be generated using a given half-life distribution, this vector must contain the respective values for each gene.
`truesynthesisrates`	If the data should be generated using a given synthesis rates distribution, this vector must contain the respective values for each gene
`genenames`	An optional list of gene names.

DTA.dynamic.generate returns a list, containing the following entries

`phenomat`	A matrix, containing the design of the experiment as produced by `DTA.phenomat`.
`datamat`	A matrix, containing the simulated measurements from U, L and T, according to the design given in phenomat.
`tnumber`	Integer vector containing the number of uridine residues for each gene.
`ccl`	The cell cycle length (in minutes).
`truemus`	A vector, containing the true synthesis rates.
`truemusaveraged`	A vector, containing the true synthesis rates, averaged over the labeling period.
`truelambdas`	A vector, containing the true decay rates.
`truelambdasaveraged`	A vector, containing the true decay rates, averaged over the labeling period.
`truehalflives`	A vector, containing the true half-lives.
`truehalflivesaveraged`	A vector, containing the true half-lives, averaged over the labeling period.
`trueplabel`	The true labeling efficiency. For details, see supplemental material of Sun et al. (see references).
`truecomplete`	A vector, containing the true amount of total RNA.
`truelambdas`	A vector, containing the true decay rates.
`truemus`	A vector, containing the true synthesis rates.
`truehalflives`	A vector, containing the true half-lives.
`trueplabel`	The true labeling efficiency. For details, see supplemental material of Miller et al. (see references).
`truear`	The true parameter ar. For details, see supplemental material of Miller et al. (see references).
`truebr`	The true parameter br. For details, see supplemental material of Miller et al. (see references).
`truecr`	The true parameter cr. For details, see supplemental material of Miller et al. (see references).
`truecrbyar`	The true parameter cr/ar. For details, see supplemental material of Miller et al. (see references).
`truecrbybr`	The true parameter cr/br. For details, see supplemental material of Miller et al. (see references).
`truebrbyar`	The true parameter br/ar. For details, see supplemental material of Miller et al. (see references).
`trueLasymptote`	The true parameter asymptote (labeled bias). For details, see supplemental material of Miller et al. (see references).
`trueUasymptote`	The true parameter asymptote (unlabeled bias). For details, see supplemental material of Miller et al. (see references).

Bjoern Schwalb schwalb@lmb.uni-muenchen.de

C. Miller, B. Schwalb, K. Maier, D. Schulz, S. Duemcke, B. Zacher, A. Mayer, J. Sydow, L. Marcinowski, L. Dolken, D. E. Martin, A. Tresch, and P. Cramer. Dynamic transcriptome analysis measures rates of mRNA synthesis and decay in yeast. Mol Syst Biol, 7:458, 2011. M. Sun, B. Schwalb, D. Schulz, N. Pirkl, L. Lariviere, K. Maier, A. Tresch, P. Cramer. Mutual feedback between mRNA synthesis and degradation buffers transcript levels in a eukaryote. Under review. B. Schwalb, B. Zacher, S. Duemcke, D. Martin, P. Cramer, A. Tresch. Measurement of genome-wide RNA synthesis and decay rates with Dynamic Transcriptome Analysis (DTA/cDTA). Bioinformatics.

nrgenes = 5000
truesynthesisrates = rf(nrgenes,5,5)*18
steady = rep(1,nrgenes)
shock = 1/pmax(rnorm(nrgenes,mean = 8,sd = 4),1)
induction = pmax(rnorm(nrgenes,mean = 8,sd = 4),1)
changes.mat = cbind(steady,shock,shock*induction)
mu.values.mat = changes.mat*truesynthesisrates
mu.breaks.mat = cbind(rep(12,nrgenes),rep(18,nrgenes))
truehalflives = rf(nrgenes,15,15)*12
truelambdas = log(2)/truehalflives
changes.mat = cbind(steady,shock,shock*induction,steady)
lambda.values.mat = changes.mat*truelambdas
lambda.breaks.mat = cbind(rep(12,nrgenes),rep(18,nrgenes),rep(27,nrgenes))

### it takes several min to build sim.object (depends on the number of genes 'nrgenes') ###

sim.object = DTA.dynamic.generate(duration = 36,lab.duration = 6,nrgenes = nrgenes,mu.values.mat = mu.values.mat,mu.breaks.mat = mu.breaks.mat,lambda.values.mat = lambda.values.mat,lambda.breaks.mat = lambda.breaks.mat)

### for control plots set 'check = TRUE' ###

res = DTA.dynamic.estimate(simulation = TRUE,sim.object = sim.object,check = FALSE)