Description Usage Arguments Value
Normalize input raw data using quantile and mloess methods. Plots of the normalized data along with a dendrogram clustering all samples will be stored in newly created pipeline directory.
1 2 | preprocessPlots(input.file, file.sheet=1, ntext=2, data.col,
symbol.index=1, id.index=2)
|
input.file |
Path to the microarray expression file, be it .xlsx or .csv |
file.sheet |
Sheet number in the spreadsheet with data |
ntext |
Number of leading text columns |
data.col |
Range of columns which contain data (indexing begins with first column of file) |
symbol.index |
Column index which contains gene symbols |
id.index |
Column index which contains gene ID's |
batch.vector |
Character vector indicating to which batch each sample belongs |
A list with components
ntext |
Number of leading text columns |
data.col |
Vector of column indices containing array data |
id |
Vector containing gene ID's |
id.index |
Column index containing gene ID information |
symbol |
Vector containing gene symbols |
symbol.index |
Column index containing gene symbol information |
desc.stats |
Vector of column indices containing descriptive statistics |
pipeline.name |
Name of pipeline generated from input file name sans extension |
mloess |
Data rame of quantile normalized data |
quantile |
Data rame of quantile normalized data |
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