DTA.dynamic.estimate: Estimation of synthesis and decay rates upon perturbation
In DTA: Dynamic Transcriptome Analysis

Description Usage Arguments Value Author(s) References See Also Examples

DTA.dynamic.estimate uses an experiment, given by a phenotype matrix, data matrix and the number of uridines for each gene to estimate synthesis and decay rate of the genes.

DTA.dynamic.estimate(phenomat = NULL,datamat = NULL,tnumber = NULL,ccl = NULL,mRNAs = NULL,reliable = NULL,mediancenter = TRUE,usefractions = "LandT",LtoTratio = NULL,ratiomethod = "tls",largest = 5,weighted = TRUE,relevant = NULL,check = TRUE,error = TRUE,samplesize = 1000,confidence.range = c(0.025,0.975),bicor = TRUE,condition = "",upper = 700,lower = 500,save.plots = FALSE,resolution = 1,folder = NULL,fileformat = "jpeg",totaloverwt = 1,sr.vs.dr.folds.lims = c(-5,5),te.vs.to.folds.lims = c(-6,6),robust = FALSE,clusters = "sr",ranktime = NULL,upperquant = 0.8,lowerquant = 0.6,notinR = FALSE,RStudio = FALSE,simulation = FALSE,sim.object = NULL)

`phenomat`	A phenotype matrix, containing the design of the experiment as produced by `DTA.phenomat`. Columns are name, fraction (U=unlabebeld, L=labeled, T=total), time and nr (=replicate number). Rows represent individual experiments.
`datamat`	A matrix, containing the measurements from U, L and T, according to the design given in phenomat. Matrix should only contain the rows of phenomat as columns.
`tnumber`	Integer vector, containing the numbers of uridines. Elements should have the rownames of datamat.
`ccl`	The cell cycle length of the cells.
`mRNAs`	Estimated number of mRNAs in a cell (optional).
`reliable`	Vector of 'reliable' genes, which are used for parameter estimation.
`mediancenter`	Should the quotient Labeled/Total resp. Unlabeled/Total be rescaled to a common median over it's replicates before building the genewise median.
`usefractions`	From which fractions should the decay rate be calculated: "LandT", "UandT" or "both".
`LtoTratio`	Coefficient to rescale Labeled/Total. Is estimated from the data, if not specified. See ratiomethod.
`ratiomethod`	Choose the regression method to be used, possible methods are: "tls", "bias" and "lm". For details, see supplemental material of Sun et al. (see references).
`largest`	Percentage of largest residues from the first regression not to be used in the second regression step. For details, see supplemental material of Sun et al. (see references).
`weighted`	Should the regression be weighted with 1/(Total^2 + median(Total))?
`relevant`	Choose the arrays to be used for halflives calculation, vector due to nr (=replicate number) in phenomat.
`check`	If check = TRUE, control messages and plots will be generated.
`error`	If TRUE, the measurement error is assessed by means of an error model and resampling to gain confidence regions.
`samplesize`	Error model samplesize for resampling.
`confidence.range`	Confidence region for error model as quantiles. Interval should be between 0 and 1.
`bicor`	Should the labeling bias be corrected?
`condition`	String, to be added to the plotnames.
`upper`	Upper bound for labeling bias estimation. For details, see supplemental material of Sun et al. (see references).
`lower`	Lower bound for labeling bias estimation. For details, see supplemental material of Sun et al. (see references).
`save.plots`	If save.plots = TRUE, control plots will be saved.
`resolution`	Resolution scaling factor for plotting.
`folder`	Path to the folder, where to save the plots.
`fileformat`	Fileformat for plots to be saved. See `plotit` function (`LSD` package).
`totaloverwt`	Will be available in the very near future for comparative DTA data.
`sr.vs.dr.folds.lims`	Limits of the folds plot (dr vs sr).
`te.vs.to.folds.lims`	Limits of the folds plot (LT vs LE).
`robust`	If robust = TRUE, LE resp. LT is chosen instead of sr resp. dr.
`clusters`	should the dr vs sr folds be plotted with clusters, choose 'sr', 'dr' for cluster selection or 'none' to omit it
`ranktime`	at which time should the rankgain be calculated, default is the last column
`upperquant`	upper quantile for cluster selection
`lowerquant`	lower quantile for cluster selection
`notinR`	Should plots be not plotted in R.
`RStudio`	For RStudio users. Suppresses the opening of a new device, as RStudio allows only one.
`simulation`	True, if data was generated by `DTA.generate`.
`sim.object`	Simulation object created by `DTA.generate`.

DTA.dynamic.estimate returns a list, where each entry contains the estimation results for all replicates of one timecourse timepoint. Each result contains the following entries

`triples`	Mapping of each fraction and experiment to its corresponding column in the data matrix.
`plabel`	The labeling efficiency. For details, see the vignette.
`LtoTratio`	Estimated ratio of labeled to total fraction.
`UtoTratio`	Estimated ratio of unlabeled to total fraction.
`LtoUratio`	Estimated ratio of labeled to unlabeled fraction.
`correcteddatamat`	Labeling bias corrected data matrix.
`drmat`	Decay rates for each replicate. The last column gives the median decay rates.
`dr`	Median decay rates. The last column of drmat.
`dr.confidence`	Confidence regions of decay rates.
`hlmat`	Half-lives for each replicate. The last column gives the median half-lifes.
`hl`	Median half-lives. The last column of hlmat.
`hl.confidence`	Confidence regions of half-lives.
`TEmat`	Total expression for each replicate. The last column gives the median total expression values.
`TE`	Median total expression values. The last column of TEmat.
`TE.confidence`	Confidence regions of total expression values.
`LEmat`	Labeled expression for each replicate. The last column gives the median labeled expression values.
`LE`	Median labeled expression values. The last column of LEmat.
`LE.confidence`	Confidence regions of labeled expression values.
`UEmat`	Unlabeled expression for each replicate. The last column gives the median unlabeled expression values. (Only if unlabeled values exist in the experiment)
`UE`	Median unlabeled expression values. The last column of UEmat. (Only if unlabeled values exist in the experiment)
`UE.confidence`	Confidence regions of unlabeled expression values.
`srmat`	Synthesis rates for each replicate. The last column gives the median synthesis rates.
`sr`	Median synthesis rates. The last column of srmat.
`sr.confidence`	Confidence regions of synthesis rates.
`LtoTmat`	Labeled to total ratio for each replicate. The last column gives the median labeled to total ratios.
`LtoT`	Median labeled to total ratios. The last column of LtoTmat.
`LtoT.confidence`	Confidence regions of labeled to total ratios.
`UtoTmat`	Unlabeled to total ratio for each replicate. The last column gives the median unlabeled to total ratios.
`UtoT`	Median unlabeled to total ratios. The last column of UtoTmat.
`UtoT.confidence`	Confidence regions of unlabeled to total ratios.
`Rsrmat`	Rescaled synthesis rates for each replicate, if parameter `mRNAs` is specified. The last column gives the median synthesis rates.
`Rsr`	Rescaled median synthesis rates. The last column of Rsrmat.
`globaldrmat`	Decay rate for each replicate. Reciprocally weighted by the total expression. Last element contains (weighted) median decay rate.
`globaldr`	(Weighted) median decay rate.

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.

heatscatter, plotit, tls

dataPath = system.file("data", package="DTA")
load(file.path(dataPath, "Miller2011dynamic.RData"))

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

res = DTA.dynamic.estimate(Sc.phenomat.dynamic,Sc.datamat.dynamic,Sc.tnumber,ccl = 150,mRNAs = 60000,reliable = Sc.reliable.dynamic,LtoTratio = rep(0.1,7),check = FALSE)