| anova.bfaov | ANOVA table of balanced factorial designs |
| array2rg | Balanced factorial array from RG structure |
| bfaov | Efficient ANOVA of balanced factorial designs |
| coef.bfaov | Coefficients and residuals of bfaov ANOVA |
| data.over.under | Analysis of over- and under-expressed genes |
| diff.vg | Significance of variety-gene effects from ANOVA analysis |
| hist.vg | Significance of variety-gene effects from ANOVA analysis |
| interpolate.bfaov | Interpolate missing values in balanced factorial data array |
| limit.vg | Significance of variety-gene effects from ANOVA analysis |
| log.array2rg | Balanced factorial array from RG structure |
| ma.cor | Loess normalization of RG values |
| ma.plot | Plots log G over log R for RG structure |
| ma.plot.single | Plots log G over log R for RG structure |
| ma.write | Interconversion of RG and MA structure |
| ma2rg | Interconversion of RG and MA structure |
| optim.design | REML estimates of variance components |
| over.under | Analysis of over- and under-expression from ANOVA |
| over.under.level | Analysis of over- and under-expression from ANOVA |
| plot.residuals | Coefficients and residuals of bfaov ANOVA |
| print.reml | REML estimates of variance components |
| pvalue.fdr | Benjamini-Hochberg FDR adjustment for multiple testing p-values |
| read.rg | RG structure from microarray data table file |
| reml.bfaov | REML estimates of variance components |
| reml.kt | REML estimates of variance components |
| residuals.bfaov | Coefficients and residuals of bfaov ANOVA |
| rg.add2bg | Background manipulation |
| rg.cor | Correlation between experiments |
| rg.duplicate.genes | Transforms multiple spots into extra experiments |
| rg.failure.histogram | Plot of number of low expression genes |
| rg.keep | Removal of genes and experiments from RG structure |
| rg.keep.containing | Removal of genes and experiments from RG structure |
| rg.linear.normalize | Loess normalization of RG values |
| rg.loess.array.normalize | Loess normalization of RG values over microarray |
| rg.loess.normalize | Loess normalization of RG values |
| rg.log.matrix | Log2 matrix from RG structure |
| rg.log.plot | Plots log G over log R for RG structure |
| rg.project | Removal of genes and experiments from RG structure |
| rg.rank.normalize | Loess normalization of RG values |
| rg.remove | Removal of genes and experiments from RG structure |
| rg.remove.containing | Removal of genes and experiments from RG structure |
| rg.remove.quantile | Removal of genes with low expression levels |
| rg.rsq | Diagnostics of low expression genes |
| rg.rsq.plot | Diagnostics of low expression genes |
| rg.scale.normalize | Loess normalization of RG values |
| rg.shift.normalize | Loess normalization of RG values |
| rg.sub.bg | Background manipulation |
| rg.write | Removal of genes and experiments from RG structure |
| rg.zero.bg | Background manipulation |
| rg2array | Balanced factorial array from RG structure |
| rg2log.array | Balanced factorial array from RG structure |
| rg2ma | Interconversion of RG and MA structure |
| sd.vg | Significance of variety-gene effects from ANOVA analysis |
| set.formula | Efficient ANOVA of balanced factorial designs |
| stat.Newton.multi | Logodds of differential expression derived from hierarchical Gamma models |
| t.boots | t-statistic bootstrap for differential gene expression |
| t.statistic | t-statistic for differential gene expression |
| t.statistic.2 | t-statistic for differential gene expression |
| write.over.under | Analysis of over- and under-expressed genes |