GenePix Auto Processor(GPAP) is designed to assist with preprocessing of raw microarray data and provides diagnostic
plots to evaluate the data quality and effects of preprocessing. GPAP will
perform signal filtering, background correction and signal normalization. GPAP will generate reports,
diagnostic plots and identify top differentially expressed genes for the user. GPAP upload check-list to avoid processing errors caused by improper file names and format.
Update: Please note that GAL files are no longer required for GPAP processing of GPR files. To correctly coordinate replicate spots between GPR files, please verify that all of your GRP files are sorted in exactly the same way (e.g., first by block, then row, then column). Please review the GPAP upload check-list to avoid processing errors caused by improper file names and format.
Fields marked with an * are required. A minimum of two GPR files with different names (biological and/or technical reps) is required for processing. Please review the checklist for further details.
Replicate
mapping for B-statistic ranking
regular intervals between replicate arrays
and
not within arrays
Number of
replicates on the microarray =
Unique Identifier:
1st GPR:
*
2nd GPR:
*
3rd GPR:
4th GPR:
5th GPR:
6th GPR:
*
Baseline Value:
Note: If signal in one channel falls below this
baseline, the signal in that channel will be increased to this value. If
in both channels, that feature will be discarded.
Parameter for Threshold Value: x=
Note: Threshold Value = B + x*SD(B) (x=1,2,3)
If signal in one channel falls below this threshold value, the signal in that channel will be increased to baseline value. If in both
channels, that feature will be discarded.
Parameter for Outliers Definition: x=
Note: Outlier > mean + x*SD or Outlier < mean - x*SD (x=1,2,3). For those replicate spots which are greater or lower than 2(default value)
standard deviations from mean are defined to be outliers and are eliminated from calculation when average is calculated for each gene.
Normalization:
--No Normalization--
Global Median Normalization
Global Loess Normalization- Global intensity dependent normalization
Local Loess Normalization- Pin-by-pin intensity dependent normalization
Composite Normalization
Robust Spline Normalization