computeNoiseForSubset {noise} | R Documentation |
Select a random subset of data for noise estimation.
Description
This function randomly selects a subset of cells (rows) from the data set, computes multiple estimates of intrinsic and extrinsic noise, as well as their mean and standard deviation.
Usage
computeNoiseForSubset(data, sample.size, n.iter)
Arguments
data |
A numeric matrix of two columns. Each row is a cell, and each column expression of a reporter gene. |
sample.size |
An integer that specifies the number of cells in the subset. |
n.iter |
An integer that specifies the number of iterations (for calcuation of mean and standard deviation). |
Value
A list that consists of the following components:
intrinsic |
A numeric matrix of esimated intrinsic noise. 7 rows and n.iter columns. |
extrinsic |
A numeric matrix of esimated extrinsic noise. 4 rows and n.iter columns. |
intrinsic.mean |
A numeric vector of length 7 that contains the mean estimates of intrinsic noise. |
intrinsic.sd |
A numeric vector of length 7 that contains the standard deviation of the estimates of intrinsic noise. |
extrinsic.mean |
A numeric vector of length 7 that contains the mean estimates of extrinsic noise. |
extrinsic.sd |
A numeric vector of length 7 that contains the standard deviation of the estimates of extrinsic noise. |
Author(s)
Audrey Q. Fu
References
Fu, A. Q. and Pachter, L. (2016). Estimating intrinsic and extrinsic noise from single-cell gene expression measurements. arXiv:1601.03334.
See Also
computeIntrinsicNoise
, computeExtrinsicNoise
, elowitz_data
, yang_nl10
.
Examples
data(yang_nl10)
# quantile normalization on log2 transformed data
# install bioconductor package for quantile normalization
# source('http://bioconductor.org/biocLite.R')
# biocLite('preprocessCore')
library(preprocessCore)
# ignore a few values that are negative
yang_nl10.pos <- yang_nl10[-which (yang_nl10[,1]<0),]
yang_nl10.pos.log2.quant <- normalize.quantiles (as.matrix (log2 (yang_nl10.pos[,c(1,3)])))
# subset the data and compute noise estimates
yang.50 <- computeNoiseForSubset (yang_nl10.pos.log2.quant, sample.size=50, n.iter=1000)
summary (yang.50)