preprocess {CGHcall}R Documentation

Preprocess arrayCGH data

Description

This function performs the following actions on arrayCGH data:

Usage

preprocess(input, type = "file", maxmiss = 30, nchrom = 22, ...)

Arguments

input Either the name of a file or a dataframe. See details for the format.
type What kind of data format is used as input? Either 'dataframe' or 'file'.
maxmiss Maximum percentage of missing values per row.
nchrom Number of chromosomes.
... Arguments for impute.knn from the impute package.

Details

The input should be either a dataframe or a tabseparated textfile (textfiles must contain a header). The first three columns should contain the name, chromosome and position in bp for each array target respectively. The chromosome and position column must contain numbers only. Following these is a column with raw log2 ratios for each of your samples. If the input type is a textfile, missing values should be represented as 'NA' or an empty field.

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(Wilting)
  raw.data <- preprocess(Wilting, type="dataframe")

[Package CGHcall version 1.0.1 Index]