calculate.p.values {OutSeekR}R Documentation

Calculate p-values

Description

Calculate p-values for each sample of a single transcript.

Usage

calculate.p.values(
  x,
  x.distribution,
  x.zrange.mean,
  x.zrange.median,
  x.zrange.trimmean,
  x.fraction.kmeans,
  x.cosine.similarity,
  null.zrange.mean,
  null.zrange.median,
  null.zrange.trimmean,
  null.fraction.kmeans,
  null.cosine.similarity,
  kmeans.nstart = 1
)

Arguments

x

A numeric vector of values for an observed transcript.

x.distribution

A numeric code corresponding to the optimal distribution of x as returned by identify.bic.optimal.data.distribution().

x.zrange.mean

A number, the range of the z-scores calculated using the mean and standard deviation of x.

x.zrange.median

A number, the range of the z-scores calculated using the median and median absolute deviation of x.

x.zrange.trimmean

A number, the range of the z-scores calculated using the trimmed mean and trimmed standard deviation of x.

x.fraction.kmeans

A number, the k-means fraction of x.

x.cosine.similarity

A number, the cosine similarity of x.

null.zrange.mean

A numeric vector, the ranges of the z-scores calculated using the mean and standard deviation of each transcript in the null data.

null.zrange.median

A numeric vector, the ranges of the z-scores calculated using the median and median absolute deviation of each transcript in the null data.

null.zrange.trimmean

A numeric vector, the ranges of the z-scores calculated using the trimmed mean and trimmed standard deviation of each transcript in the null data.

null.fraction.kmeans

A numeric vector, the k-means fraction of each transcript in the null data.

null.cosine.similarity

A numeric vector, the cosine similarity of each transcript in the null data.

kmeans.nstart

The number of random starts when computing k-means fraction; default is 1. See ?stats::kmeans for further details.

Value

A list consisting of the following entries:

Examples

data(example.data.for.calculate.p.values);
i <- 1; # row index of transcript to test
calculate.p.values(
   x = example.data.for.calculate.p.values$data[i,],
   x.distribution = example.data.for.calculate.p.values$x.distribution[i],
   x.zrange.mean = example.data.for.calculate.p.values$x.zrange.mean[i],
   x.zrange.median = example.data.for.calculate.p.values$x.zrange.median[i],
   x.zrange.trimmean = example.data.for.calculate.p.values$x.zrange.trimmean[i],
   x.fraction.kmeans = example.data.for.calculate.p.values$x.fraction.kmeans[i],
   x.cosine.similarity = example.data.for.calculate.p.values$x.cosine.similarity[i],
   null.zrange.mean = example.data.for.calculate.p.values$null.zrange.mean,
   null.zrange.median = example.data.for.calculate.p.values$null.zrange.median,
   null.zrange.trimmean = example.data.for.calculate.p.values$null.zrange.trimmean,
   null.fraction.kmeans = example.data.for.calculate.p.values$null.fraction.kmeans,
   null.cosine.similarity = example.data.for.calculate.p.values$null.cosine.similarity,
   kmeans.nstart = example.data.for.calculate.p.values$kmeans.nstart
   );

[Package OutSeekR version 1.0.0 Index]