computeNoiseForSubset: Select a random subset of data for noise estimation.

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

View source: R/computeNoiseForSubset.R

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

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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

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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)

noise documentation built on May 29, 2017, 12:04 p.m.