getMeanVariance: Calculate mean and variance of expression samples

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

View source: R/getMeanVariance_call.R

Description

Calculate mean and variance of expression samples or log-expression samples

Usage

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getMeanVariance(sampleFiles, outFile, log=NULL, type=NULL, verbose=NULL,
      norm=NULL, pretend=FALSE)

Arguments

sampleFiles

Vector of one or more files containing the expression samples.

outFile

Name of the output file.

log

Use logged values.

type

Type of variance, possible values: sample,sqDif for sample variance or squared difference.

verbose

Verbose output.

norm

Vector of (multiplicative) normalization constants for library size normalization of expression samples. Number of constants has to match the number of expression samples files.

pretend

Do not execute, only print out command line calls for the C++ version of the program.

Details

The getMeanVariance function computes means and variances of MCMC expression samples. These can be computed either from single file or from multiple files using sample variance. Variance of two experiments (i.e. technical or biological replicates) can be estimated also by using sqDif option for type which specify the computation of the average square distance between the samples from two sets.

Value

.means

File containing means (first column) and variance (second column) for each transcript (or row in the sample files)

Author(s)

Peter Glaus

See Also

estimateExpression

Examples

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setwd(system.file("extdata",package="BitSeq"));
sampleFileNames = c("data-c1b0.rpkm","data-c1b1.rpkm")
getMeanVariance(sampleFiles=sampleFileNames, outFile="data-c1.Lmean", log=1,
      norm=c(1.0017, 0.9998))

BitSeq documentation built on Nov. 8, 2020, 5:25 p.m.