preprocess: Preprocess arrayCGH data

In tgac-vumc/CGHcall: Calling aberrations for array CGH tumor profiles.

Description

This function preprocesses your aCGH data so it can be processed by other functions without errors.

Usage

preprocess(input, maxmiss = 30, nchrom = 23, ...)

Arguments

input	Object of class cghRaw.
maxmiss	Maximum percentage of missing values per row.
nchrom	Number of chromosomes.
...	Arguments for impute.knn from the impute package.

Details

This function performs the following actions on arrayCGH data:

• Filter out data with missing position information.

• Remove data on chromosomes larger than nchrom.

• Remove rows with more than maxmiss percentage missing values.

• Imputes missing values using the impute.knn function from the impute package.

Value

This function returns a dataframe in the same format as the input with missing values imputed.

Author(s)

Sjoerd Vosse & Mark van de Wiel

References

Olga Troyanskaya, Michael Cantor, Gavin Sherlock, Pat Brown, Trevor Hastie, Robert Tibshirani, David Botstein, and Russ B. Altman (2001). Missing value estimation methods for DNA microarrays. Bioinformatics, 17, 520-525.

Examples

  data(WiltingRaw)
  preprocessed <- preprocess(WiltingRaw, nchrom = 22)

tgac-vumc/CGHcall documentation built on May 31, 2019, 9 a.m.