In iaradsouza1/MicroarrayMethods: Provide methods for microarray analysis

Raw data assessment

raw <- import_celfiles(celfiles_path = params$celfiles, pheno_data = params$pheno_data, sep = params$sep, filenames = params$filenames)

Plot densities

limma::plotDensities(raw@assayData$exprs, legend = FALSE, main = "Raw data samples density plot")

Boxplot

``` {r, echo=FALSE, message=FALSE, fig.height=5, fig.width=10} affy::boxplot(raw, las = 2, main = "")

## RNA degradation plot

```r
deg <- affy::AffyRNAdeg(raw)
affy::plotAffyRNAdeg(deg)

Normalized data

MA-plot from normalized data

eset <- affy::rma(raw)

par(mfrow = c(2, 2))
oligo::MAplot(eset, plot.method = "smoothScatter", main = "")

Density plot

par(mfrow = c(1,1))
limma::plotDensities(eset, legend = F, main = "Normalized samples density")

Boxplot

par(mfrow = c(1,1))
affy::boxplot(eset, las = 2, main = "", col = "white")

PCA

plot_pca(eset, components = params$components, groups = params$group, batch = params$batch)

PCs proportion

pca_prop(eset)

Dendrogram

plot_dendrogram(eset, groups = params$group)

Compare variances

exp <- Biobase::exprs(eset)
a <- calc_var_groups(exp, as.factor(Biobase::pData(eset)[,params$group]))
b <- calc_var_total(exp)
compare_variances(a, b)

The result shows the proportion of probes in each group which the group variance is greater than the total variance.

rm(eset, raw, deg)

iaradsouza1/MicroarrayMethods documentation built on Nov. 3, 2021, 2 p.m.