check.pigengene.input: Quality check on the imput
In Pigengene: Infers biological signatures from gene expression data

Description Usage Arguments Value Author(s) See Also Examples

Checks Data and Labels for NA values, row and column names, etc.

1	check.pigengene.input(Data, Labels, na.rm = FALSE, naTolerance=0.05)

`Data`	A matrix or data frame containing the expression data, with genes corresponding to columns and rows corresponding to samples. Rows and columns must be named.
`Labels`	A (preferably named) vector containing the Labels (condition types) for `Data`. Names must agree with rows of `Data`.
`na.rm`	If `TRUE`, `NA`s in the Data will be replaces with the average of the column, however, if the frequency of `NA`s in the column is too high, the whole column will be removed.
`naTolerance`	Upper threshold on the fraction of entries per gene that can be missing. Genes with a larger fraction of missing entries are ignored. For genes with smaller fraction of NA entries, the missing values are imputed from their average expression in the other samples. See `check.pigengene.input`.

A list of:

`Data`	The checked `Data` matrix, `NA` possibly removed and rows are ordered as names of `Labels`.
`Labels`	The checked vector of `Labels`

Habil Zare

check.nas, one.step.pigengene, Pigengene-package

     data(aml)
     Labels <- c(rep("AML",nrow(aml)))
     names(Labels) <- rownames(aml)
     c1 <- check.pigengene.input(Data=aml, Labels=Labels,na.rm=TRUE)
     Data <- c1$Data
     Labels <- c1$Labels