getT: Estimate the shrinkage target based on the initial estimates

In sSeq: Shrinkage estimation of dispersion in Negative Binomial models for RNA-seq experiments with small sample size

Description

This function is recommended to estimate the shrinkage target.

Usage

getT(countsTable, sizeFactors = NULL, q.vec = NULL, plotASD = FALSE, 
    numPart = 1, propForSigma = c(0, 1), verbose = TRUE, 
    shrinkTarget = NULL, shrinkQuantile = NULL, shrinkVar = FALSE, 
    eSlope = 0.05, disp = NULL, dispXX = NULL, normalize = FALSE, 
    lwd1 = 4.5, cexlab1 = 1.2)

Arguments

countsTable	A data.frame or a matrix of counts in which a row represents for a gene and a column represents for a sample. There must be at least two columns in countsTable.
sizeFactors	A vector of values around 1 which are used to normalize between samples or libraries. The length of this vector equals to the number of columns in countsTable.
q.vec	A vector of sequence defines the quantiles. When q.vec=NULL, this function will generate a sequence for q.vec using seq(0.05, 0.995, 0.005).
plotASD	A logic value. If plotASD=TRUE, then the plot of ASD versus target points will be drawn. The SH estimates are obtained by shrinking the MM estimates toward a target point. Different SH estimates are generated using different target points. The target point that helps produce a small and stable averaged squared difference (ASD) between the MM estimates and the SH estimates is the point that approximates the common information across per- gene dispersion. This target point is termed as the point of stabilization.
numPart	An integer indicates the number of groups for dispersion estimation. ‘numPart=1’ is the default value. It assumes that most of the genes share one point of stabilization (POS), and calculates the SH estimates without separating data into groups. When we assumes that genes can share different points of stabilization, the grouped SH estimates on dispersion can be be utilized. In this situation, users need to provide a number indicating the number of POS.
propForSigma	A range vector between 0 and 1 that is used to select a subset of data. It helps users to make a flexible choice on the subset of data when they believe only part of data should be used to estimate the variation among per-gene dispersion. A default input propForSigma=c(0, 1) is recommended. It means that we want to use all the data to estimate the variation.
verbose	A logic value. When verbose=TRUE, the detail information will be printed in the console.
shrinkTarget	A value for the shrinkage target of dispersion estimates. If “shrinkTarget=NULL" and “shrinkQuantile" is a value instead of NULL, then the quantile value for “shrinkQuantile" is converted into the scale of dispersion estimates and used as the target. If both of them are NULL, then a value that is small and minimizes the average squared difference is automatically used as the target value. If both of them are not NULL, then the value of “shrinkTarget" is used as the target.
shrinkQuantile	A quantile value for the shrinkage target of dispersion estimates. If “shrinkTarget=NULL" and “shrinkQuantile" is a value instead of NULL, then the quantile value for “shrinkQuantile" is converted into the scale of dispersion estimates and used as the target. If both of them are NULL, then a value that is small and minimizes the average squared difference is automatically used as the target value. If both of them are not NULL, then the value of “shrinkTarget" is used as the target.
shrinkVar	A logic value. When “shrinkVariance=TRUE", the testing is based on the shrinkage estimates for variance instead of dispersion.
eSlope	A positive value near to zero. When selecting the shrinkage target that is small and minimizing the average squared difference (ASD), the value of “elope" is a threshold to stop the selection steps if the absolute value of a local slope for the ASD is less than the threshold. The default value is 0.05.
disp	A vector of initial estimates of dispersions. The length of this vector equals to the number of rows in countsTable.
dispXX	A vector of normalized mean expression. The length of this vector equals to the number of rows in countsTable.
normalize	A logic value. When estimating the shrinkage target based on the average squared difference (ASD) between the shrinkage estimates and the initial estimates, the initial estimates and ASD are normalized when “normalize=TRUE".
lwd1	A value specifying the width of the curve shown in the plot for the average squared difference when “plotASD=TRUE". The default value is 4.5.
cexlab1	A value specifying the size of label text shown in the plot for the average squared difference when “plotASD=TRUE". The default value is 1.2.

Value

target	The estimated point for stabilization that represents the common in formation across per-gene dispersion.
q	A value that shows the quantile of the target value across per- gene dispersion.

Examples

#load a simulated data that includes a count table
data("countsTable")
conds <- c("A",  "B")
getT(countsTable, plotASD=TRUE)

sSeq documentation built on Nov. 8, 2020, 5:52 p.m.