frma normalization
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9 months ago

Hello everyone!

I have bulk rna-seq data and would like to do some analysis to see what cell types I have, with the MCP-counter package. However, they require that the matrix be normalized with frma in r and here I am running into problems.

I have a data matrix and in order to normalize it in frma it has to be "AffyBatch," "ExonFeatureSet," "GeneFeatureSet" objects. I've been trying for days but I don't understand how to do it.

I installed affy but when I try to use the function:

affy_obj <- AffyBatch(data = as.matrix(matrixFiltered))
Error in AffyBatch(data = as.matrix(matrixFiltered)) : 
  can't find the function "AffyBatch"

Do you know why? What I have to do?

Thank you
affybatch frma mcp-counter • 1.1k views
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Did you load the package using library(affy) after installing it?

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yes, but nothing change

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Please show your full code as well as the output to sessionInfo()

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> sessionInfo()
R version 4.3.2 (2023-10-31 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 11 x64 (build 22631)

Matrix products: default

locale:
[1] LC_COLLATE=Italian_Italy.utf8  LC_CTYPE=Italian_Italy.utf8    LC_MONETARY=Italian_Italy.utf8
[4] LC_NUMERIC=C                   LC_TIME=Italian_Italy.utf8

time zone: Europe/Rome
tzcode source: internal

attached base packages:
 [1] parallel  grid      stats4    stats     graphics  grDevices utils     datasets  methods   base

other attached packages:
 [1] frma_1.54.0                             MCPcounter_1.2.0
 [3] curl_5.2.0                              immunedeconv_2.1.0
 [5] EPIC_1.1.7                              GSVA_1.50.0
 [7] preprocessCore_1.64.0                   e1071_1.7-14
 [9] Homo.sapiens_1.3.1                      TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2
[11] GO.db_3.18.0                            OrganismDbi_1.44.0
[13] GenomicFeatures_1.54.3                  goseq_1.54.0
[15] geneLenDataBase_1.38.0                  BiasedUrn_2.0.11
[17] GOfuncR_1.22.2                          vioplot_0.4.0
[19] zoo_1.8-12                              sm_2.2-5.7.1
[21] RColorBrewer_1.1-3                      org.Hs.eg.db_3.18.0
[23] org.Mm.eg.db_3.18.0                     Glimma_2.12.0
[25] GSEABase_1.64.0                         graph_1.80.0
[27] annotate_1.80.0                         XML_3.99-0.16.1
[29] fgsea_1.28.0                            EnhancedVolcano_1.20.0
[31] ggrepel_0.9.5                           DGEobj.utils_1.0.6
[33] clusterProfiler_4.10.0                  DESeq2_1.42.0
[35] msigdbr_7.5.1                           affy_1.80.0
[37] readxl_1.4.3                            xCell_1.1.0
[39] recount_1.28.0                          enrichR_3.2
[41] ComplexHeatmap_2.18.0                   Rtsne_0.17
[43] AnnotationDbi_1.64.1                    SummarizedExperiment_1.32.0
[45] Biobase_2.62.0                          GenomicRanges_1.54.1
[47] GenomeInfoDb_1.38.6                     IRanges_2.36.0
[49] S4Vectors_0.40.2                        BiocGenerics_0.48.1
[51] MatrixGenerics_1.14.0                   matrixStats_1.2.0
[53] lubridate_1.9.3                         forcats_1.0.0
[55] stringr_1.5.1                           purrr_1.0.2
[57] readr_2.1.5                             tidyr_1.3.1
[59] tibble_3.2.1                            ggplot2_3.4.4
[61] tidyverse_2.0.0                         knitr_1.45
[63] dplyr_1.1.4                             edgeR_4.0.15
[65] limma_3.58.1

loaded via a namespace (and not attached):
  [1] progress_1.2.3                nnet_7.3-19                   Biostrings_2.70.1
  [4] HDF5Array_1.30.0              vctrs_0.6.5                   proxy_0.4-27
  [7] digest_0.6.34                 png_0.1-8                     shape_1.4.6
 [10] MASS_7.3-60                   reshape2_1.4.4                foreach_1.5.2
 [13] httpuv_1.6.14                 bumphunter_1.44.0             qvalue_2.34.0
 [16] withr_3.0.0                   xfun_0.42                     ggfun_0.1.4
 [19] survival_3.5-7                ellipsis_0.3.2                doRNG_1.8.6
 [22] memoise_2.0.1                 gson_0.1.0                    gtools_3.9.5
 [25] tidytree_0.4.6                GlobalOptions_0.1.2           Formula_1.2-5
 [28] prettyunits_1.2.0             derfinder_1.36.0              KEGGREST_1.42.0
 [31] promises_1.2.1                httr_1.4.7                    downloader_0.4
 [34] restfulr_0.0.15               rhdf5filters_1.14.1           ComICS_1.0.4
 [37] rhdf5_2.46.1                  rstudioapi_0.15.0             generics_0.1.3
 [40] DOSE_3.28.2                   base64enc_0.1-3               babelgene_22.9
 [43] zlibbioc_1.48.0               ScaledMatrix_1.10.0           ggraph_2.1.0
 [46] polyclip_1.10-6               GenomeInfoDbData_1.2.11       SparseArray_1.2.2
 [49] RBGL_1.78.0                   interactiveDisplayBase_1.40.0 xtable_1.8-4
 [52] pracma_2.4.4                  doParallel_1.0.17             evaluate_0.23
 [55] S4Arrays_1.2.0                BiocFileCache_2.10.1          hms_1.1.3
 [58] irlba_2.3.5.1                 colorspace_2.1-0              filelock_1.0.3
 [61] magrittr_2.0.3                later_1.3.2                   viridis_0.6.5
 [64] ggtree_3.10.0                 lattice_0.21-9                genefilter_1.84.0
 [67] derfinderHelper_1.36.0        shadowtext_0.1.3              cowplot_1.1.3
 [70] class_7.3-22                  Hmisc_5.1-1                   pillar_1.9.0
 [73] nlme_3.1-163                  iterators_1.0.14              mapplots_1.5.2
 [76] compiler_4.3.2                beachmat_2.18.0               stringi_1.8.3
 [79] GenomicAlignments_1.38.2      plyr_1.8.9                    crayon_1.5.2
 [82] abind_1.4-5                   BiocIO_1.12.0                 gridGraphics_0.5-1
 [85] locfit_1.5-9.8                graphlayouts_1.1.0            bit_4.0.5
 [88] fastmatch_1.1-4               codetools_0.2-19              BiocSingular_1.18.0
 [91] mMCPcounter_1.1.0             GetoptLong_1.0.5              mime_0.12
 [94] ff_4.0.12                     splines_4.3.2                 circlize_0.4.15
 [97] Rcpp_1.0.11                   dbplyr_2.4.0                  sparseMatrixStats_1.14.0
[100] HDO.db_0.99.1                 cellranger_1.1.0              GenomicFiles_1.38.0
[103] blob_1.2.4                    utf8_1.2.4                    clue_0.3-65
[106] BiocVersion_3.18.1            DGEobj_1.1.2                  WriteXLS_6.5.0
[109] fs_1.6.3                      oligo_1.66.0                  checkmate_2.3.1
[112] DelayedMatrixStats_1.24.0     ggplotify_0.1.2               Matrix_1.6-4
[115] statmod_1.5.0                 tzdb_0.4.0                    tweenr_2.0.2
[118] pkgconfig_2.0.3               tools_4.3.2                   cachem_1.0.8
[121] RSQLite_2.3.3                 viridisLite_0.4.2             DBI_1.2.1
[124] fastmap_1.1.1                 rmarkdown_2.25                scales_1.3.0
[127] Rsamtools_2.18.0              AnnotationHub_3.10.0          patchwork_1.2.0
[130] BiocManager_1.30.22           VariantAnnotation_1.48.1      rpart_4.1.21
[133] farver_2.1.1                  mgcv_1.9-0                    tidygraph_1.3.1
[136] scatterpie_0.2.1              yaml_2.3.8                    foreign_0.8-85
[139] rtracklayer_1.62.0            cli_3.6.1                     GEOquery_2.70.0
[142] lifecycle_1.0.4               backports_1.4.1               BiocParallel_1.36.0
[145] timechange_0.3.0              gtable_0.3.4                  rjson_0.2.21
[148] ape_5.7-1                     jsonlite_1.8.8                affxparser_1.74.0
[151] bitops_1.0-7                  bit64_4.0.5                   assertthat_0.2.1
[154] yulab.utils_0.1.4             GOSemSim_2.28.1               lazyeval_0.2.2
[157] shiny_1.8.0                   htmltools_0.5.7               enrichplot_1.22.0
[160] data.tree_1.1.0               rappdirs_0.3.3                glue_1.6.2
[163] XVector_0.42.0                RCurl_1.98-1.13               treeio_1.26.0
[166] BSgenome_1.70.2               gridExtra_2.3                 igraph_2.0.1.1
[169] R6_2.5.1                      sva_3.50.0                    SingleCellExperiment_1.24.0
[172] cluster_2.1.6                 rngtools_1.5.2                Rhdf5lib_1.24.2
[175] aplot_0.2.2                   DelayedArray_0.28.0           tidyselect_1.2.0
[178] htmlTable_2.4.2               ggforce_0.4.1                 xml2_1.3.6
[181] oligoClasses_1.64.0           testit_0.13                   rsvd_1.0.5
[184] munsell_0.5.0                 affyio_1.72.0                 data.table_1.15.0
[187] htmlwidgets_1.6.4             biomaRt_2.58.2                rlang_1.1.2
[190] rentrez_1.2.3                 fansi_1.0.5
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Include your full code (with the steps where you load the package, call the function and face the error).

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BiocManager::install("affy")
library(affy)

matriceFiltrata <- AffyBatch(matriceFiltrata)

> matriceFiltrata <- AffyBatch(matriceFiltrata)
Error in AffyBatch(matriceFiltrata) : function "AffyBatch" not found
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I read the docs, and AffyBatch is a class, not a function. Use read.affybatch() or ReadAffy() to create the AffyBatch object from input files.

https://web.mit.edu/~r/current/arch/i386_linux26/lib/R/library/affy/html/AffyBatch-class.html

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Yes! But now I have this error

> library(affy)
> matrixFiltered <- affy::AffyBatch(matrixFiltered)
Error: 'AffyBatch' is not an object exported from 'namespace:affy'
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Sorry, I changed my comment after I wrote that affy::AffyBatch part. Please try the new solution I posted. It will probably not work with your matrixFiltered object - you'd probably need to read in the files directly.

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I have two different errors now:

matriceFiltrata <- read.affybatch(matriceFiltrata)
    Errore: the following are not valid files:
        333
       821
       1004
       670
       1009
       3
       212
       659
       348
       118
       299
       797
       531
       93
       796
       1
       421
       27
       177
       436
       47
       256
       704
       1
       475
       406
       299
       567
       1009
       626
       95
       1
       7
       531
       18
       382
       626
       380
       2
       466
       298
       41
       947
       927
       698
       876
       203
       705
       242
       298
       156
       855
       803
       2
       678
       342
       1
       465
       1
       847
       339
       371
       2
       298
       705
       491
       1
       4
       498
       180
       449
       704
       927
       693
       637
       649
       466
       285
       2
       152
       355
       388
       203
       637
       551
       988
       547
       298
       1
       927
       465
       531
       85
       92
       355
       1
       632
       693
       265
       344
       591
       7
       465
       241
       501
       1
       1
       407
       821
       406
       298
       257
       946
       298
       1
       298
       227
       1
       580
       277
       449
       1
       2
       1
       2
       557
       591
       77
       406
       580
       704
       1
       865
       1
       580
       1
       232
       420
       1009
       111
       670
       491
       649
       350
       796

> matriceFiltrata <- ReadAffy(matriceFiltrata)
Errore: file names must be specified using a character vector, not a ‘list’
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Please read my reply to your other comment. This is as far as I can help you.

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I download my matrix and I try to read it and upload it on R through the function that suggest but nothing change

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enter image description here

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This is not required, sessionInfo() covers what's required while leaving out what's not.

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