Vignette of the a4Classif package

Introduction

This document explains the functionalities available in the a4Classif package.

This package contains for classification of Affymetrix microarray data, stored in an ExpressionSet. This package integrates within the Automated Affymetrix Array Analysis suite of packages.

## Loading required package: a4Core
## Loading required package: a4Preproc
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## a4Classif version 1.60.0
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## Welcome to Bioconductor
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##     Vignettes contain introductory material; view with
##     'browseVignettes()'. To cite Bioconductor, see
##     'citation("Biobase")', and for packages 'citation("pkgname")'.

To demonstrate the functionalities of the package, the ALL dataset is used. The genes are annotated thanks to the addGeneInfo utility function of the a4Preproc package.

data(ALL, package = "ALL")
ALL <- addGeneInfo(ALL)
## Loading required package: hgu95av2.db
## Loading required package: AnnotationDbi
## Loading required package: stats4
## Loading required package: IRanges
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ALL$BTtype <- as.factor(substr(ALL$BT,0,1))

Classify microarray data

Lasso regression

resultLasso <- lassoClass(object = ALL, groups = "BTtype")
plot(resultLasso, 
    label = TRUE, 
    main = "Lasso coefficients in relation to degree of penalization."
)

topTable(resultLasso, n = 15)
## The lasso selected 16 genes. The top 15 genes are:
## 
##             Gene Coefficient
## 38319_at    CD3D  0.95966733
## 35016_at    CD74 -0.60928095
## 38147_at  SH2D1A  0.49240967
## 35792_at    MGLL  0.46856925
## 37563_at  SRGAP3  0.26648240
## 38917_at  YME1L1  0.25100075
## 40278_at    GGA2 -0.25017550
## 41164_at    IGHM -0.12387272
## 41409_at THEMIS2 -0.10581122
## 38242_at    BLNK -0.10309606
## 35523_at   HPGDS  0.10169706
## 38949_at   PRKCQ  0.07832802
## 33316_at     TOX  0.06963509
## 33839_at   ITPR2  0.05801832
## 40570_at   FOXO1 -0.04858863

PAM regression

resultPam <- pamClass(object = ALL, groups = "BTtype")
plot(resultPam, 
    main = "Pam misclassification error versus number of genes."
)

topTable(resultPam, n = 15)
## Pam selected  1  genes. The top  15  genes are:
## 
##          GeneSymbol B.score T.score av.rank.in.CV prop.selected.in.CV
## 38319_at       CD3D -0.1693  0.4875             1                   1
confusionMatrix(resultPam)
##     predicted
## true  B  T
##    B 95  0
##    T  1 32

Random forest

# select only a subset of the data for computation time reason
ALLSubset <- ALL[sample.int(n = nrow(ALL), size = 100, replace = FALSE), ]

resultRf <- rfClass(object = ALLSubset, groups = "BTtype")
plot(resultRf)

topTable(resultRf, n = 15)
## Random forest selected 11 genes. The top 15 genes are:
## 
##            GeneSymbol
## 1369_s_at       CXCL8
## 172_at         INPP5D
## 31596_f_at    GUSBP11
## 31997_at         <NA>
## 34796_at        TRAM1
## 39643_at        POLG2
## 40050_at      CBFA2T2
## 40159_r_at       <NA>
## 40779_at       KIFAP3
## 41654_at          ADA
## 41718_g_at      FADS1

ROC curve

ROCcurve(gene = "ABL1", object = ALL, groups = "BTtype")
## Warning in ROCcurve(gene = "ABL1", object = ALL, groups = "BTtype"): Gene ABL1 corresponds to 6 probesets; only the first probeset ( 1635_at ) has been displayed on the plot.

Appendix

Session information

## R version 4.6.1 (2026-06-24)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 26.04.1 LTS
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## Matrix products: default
## BLAS:   /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3 
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## time zone: Etc/UTC
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## attached base packages:
## [1] stats4    stats     graphics  grDevices utils     datasets  methods   base     
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## other attached packages:
##  [1] hgu95av2.db_3.13.0   org.Hs.eg.db_3.23.1  AnnotationDbi_1.74.0 IRanges_2.46.0       S4Vectors_0.50.3     ALL_1.54.0           Biobase_2.72.0       BiocGenerics_0.58.1  generics_0.1.4       a4Classif_1.60.0     a4Preproc_1.60.0     a4Core_1.60.0        rmarkdown_2.32      
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## [24] rlang_1.3.0          XVector_0.52.0       pamr_1.57            bit64_4.8.6          splines_4.6.1        cachem_1.1.0         yaml_2.3.12          tools_4.6.1          parallel_4.6.1       memoise_2.0.1        ROCR_1.0-12          png_0.1-9            buildtools_1.0.0     vctrs_0.7.3          R6_2.6.1             lifecycle_1.0.5      Seqinfo_1.2.0        KEGGREST_1.52.2      randomForest_4.7-1.2 bit_4.6.0            cluster_2.1.8.3      pkgconfig_2.0.3      bslib_0.12.0        
## [47] Rcpp_1.1.2           xfun_0.61            sys_3.4.3            knitr_1.52           htmltools_0.5.9      maketools_1.3.2      compiler_4.6.1