CGHcall (version 2.34.0)

preprocess: Preprocess arrayCGH data

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.

Value

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

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.

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)