amplify.handling.effect | Handling effect amplification |
blocking.design | Blocking Design |
calc.confounding.level | Level of confounding calculation |
confounding.design | Confounding Design |
estimate.biological.effect | Estimated Sample Effects |
estimate.handling.effect | Estimated handling effects |
extract.precision.error | Extracting errors from PRECISION (both non-FLEX and FLEX)... |
lasso.intcv | Least absolute shrinkage and selection operator through... |
lasso.predict | Prediction with least absolute shrinkage and selection... |
limma.pbset | Differential expression analysis of probe-set data |
med.norm | Median normalization |
med.sum.pbset | Probe-set median summarization |
nuhdata.pl | The nonuniformly-handled probe-level dataset, 10 probes for... |
pam.intcv | Nearest shrunken centroid through internal cross validation |
pam.predict | Prediction with nearest shrunken centroid classifier |
per.unipbset.truncate | Probe-level data truncation to a fixed number of probes per... |
plot.precision | Plot misclassification error rates from PRECISION (both... |
precision.simulate | Classification analysis of simulation study |
precision.simulate.flex | Classification analysis of simulation study (with more... |
quant.norm | Quantile normalization |
reduce.signal | Biological signal reduction |
rehybridize | Virtual rehybridization with an array-to-sample assignment |
stratification.design | Stratification Design |
uhdata.pl | The uniformly-handled probe-level dataset, 10 probes for each... |
uni.handled.simulate | Classification analysis of uniformly-handled data |
vs.norm | Variance stabilizing normalization |
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