DTA.dynamic.estimate {DTA} | R Documentation

## Estimation of synthesis and decay rates upon perturbation

### Description

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.

### Usage

    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)

### Arguments

`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`.

### Value

`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.

### Author(s)

Bjoern Schwalb schwalb@lmb.uni-muenchen.de

### References

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.

### See Also

`heatscatter`, `plotit`, `tls`

### Examples

    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)

[Package DTA version 2.34.0 Index]