DTA.generate: Simulation of DTA experiments
In DTA: Dynamic Transcriptome Analysis

Description Usage Arguments Value Author(s) References Examples

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

DTA.generate(timepoints, tnumber = NULL, plabel = NULL, nrgenes = 5000, mediantime = 12, ccl = 150, delaytime = 0, sdnoise = 0.075, nobias = FALSE, unspecific.LtoU = 0, unspec.LtoU.weighted = FALSE, unspecific.UtoL = 0, unspec.UtoL.weighted = FALSE, truehalflives = NULL, truecomplete = NULL, genenames = NULL, cDTA = FALSE)

`timepoints`	Integer vector containing the labeling times for which the samples should be generated.
`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`	The median of the randomly drawn half-life distribution.
`ccl`	The cell cycle length (in minutes).
`delaytime`	Estimates the delay between the moment of 4sU/4tU labeling and actual incorporation of it into mRNA.
`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?
`truehalflives`	If the data should be generated using a given half-life distribution, this vector must contain the respective values for each gene.
`truecomplete`	If the data should be generated using a given expression distribution, this vector must contain the respective values for each gene.
`genenames`	An optional list of gene names.
`cDTA`	cDTA = FALSE does not rescale L and U.

DTA.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).
`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. Doelken, 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.

sim.object = DTA.generate(timepoints=rep(c(6,12),2))

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

res.sim = DTA.estimate(ratiomethod = "bias",simulation = TRUE,sim.object = sim.object,check = FALSE)