Description Usage Arguments Value
Implement SAM and compute significant genes given delta. Output will consist of all significant genes ordered by increasing q-value and decreasing d-score.
1 2 | SigGenesSAM(background.subtraction.obj, class.compare.cols,
class.compare.name, fdr.cutoff=0.1, response)
|
background.subtraction.obj |
Object returned from call to BackgroundSubtraction |
class.compare.cols |
Vector of column indices indicating which subset of arrays are to be compared for this comparison |
class.compare.name |
String title given to the name of the comparison |
fdr.cutoff |
Max FDR for SAM, will use delta value which results in max FDR below this cutoff |
response |
For two class unpaired: vector of 1, 2 values that indicate group membership. For two class paired: vector of -1, 1, -2, 2, etc. values that indicate pairings. |
A list with components
siggenes.table |
Combined data frame of genes having significant positive and negative correlation |
data.col |
Vector of column indices containing array data |
ntext |
Number of leading text columns |
response |
Vector of array group membership, 1=control, 2=experimental |
pipeline.name |
Name of pipeline generated from input file name sans extension |
data |
Data frame of chosen normalization method data |
class.compare.cols |
Value entered through class.compare.cols parameter |
class.compare.name |
Value entered through class.compare.name parameter |
symbol.index |
Column index that contains gene symbol |
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