getBootCI: Compute variance partition coefficition (VPC) confidence...
In HeritSeq: Heritability of Gene Expression for Next-Generation Sequencing

Compute VPC CI based on parametric bootstrap for one or more features.

getBootCI(
  CountMatrix,
  Strains,
  which.features,
  num.boot,
  method = "NB-fit",
  alpha = 0.05,
  optimizer = "nlminb"
)

`CountMatrix`	A G\times N count matrix. G is the number of features; N is the total number of samples.
`Strains`	A 1\times N vector of strain labels corresponding to each sample.
`which.features`	A 1\times k vector of select feature numbers for which CI is desired. k≤q G.
`num.boot`	Number of bootstraps.
`method`	Which method should be used, "CP-fit", "NB-fit" (default), or "VST". "VST" method bootstraps data under negative binomial mixed models.
`alpha`	A numerical value between 0 and 1, indicating the significance level of the CI. The CI will be 100(1-alpha)* percent CI. Default value is 0.05.
`optimizer`	A character string that determines which optimization routine is to be used. It is only used for method = "CP-fit". Possible choices are "nlminb" (default), "L-BFGS-B", and "bobyqa".

A list of two objects. The first object is a k \times 2 matrix containing the CI. The second object consists of a k \timesnum.boot matrix of all bootsrapped VPC values.

HeritSeq documentation built on July 13, 2021, 1:06 a.m.