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Hi, I am new to DNA methylation array analysis and I am using ChAMP pipeline to identify DMRs. I am using GEO dataset containing 75 diseased and control samples. I have downloaded the dataset using getGEOSuppFiles function and untar it. Now when I am using the champ.load function to load my data, it is giving me an error as follows: I looked on GEO but there is no sample sheet for the dataset. Can anyone please let me know the way to create/find the sample sheet for ChAMP analysis. I greatly appreciate your help. Thank you!
> [===========================] [<<<< ChAMP.LOAD START >>>>>]
> ----------------------------- [ Loading Data with ChAMP Method ]
> ---------------------------------- Note that ChAMP method will NOT return rgSet or mset, they object defined by minfi. Which means, if
> you use ChAMP method to load data, you can not use SWAN or
> FunctionNormliazation method in champ.norm() (you can use BMIQ or PBC
> still). But All other function should not be influenced.
> [===========================] [<<<< ChAMP.IMPORT START >>>>>]
> -----------------------------
>
> [ Section 1: Read PD Files Start ] Error in champ.import(directory,
> arraytype = arraytype) :
> champ.import can not find any csv file
> sessionInfo()
R version 4.4.2 (2024-10-31)
Platform: aarch64-apple-darwin20
Running under: macOS Sequoia 15.2
Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRlapack.dylib; LAPACK version 3.12.0
locale:
[1] en_US.UTF-_US.UTF-8/en_US.UTF-8/C/en_US.UTF-
attached base packages:
[1] parallel stats4 stats graphics grDevices utils datasets methods base
other attached packages:
[1] R.utils_2.12.3 R.oo_1.27.0
[3] R.methodsS3_1.8.2 GEOquery_2.74.0
[5] ChAMP_2.36.0 RPMM_1.25
[7] cluster_2.1.8 DT_0.33
[9] IlluminaHumanMethylationEPICmanifest_0.3.0 Illumina450ProbeVariants.db_1.42.0
[11] DMRcate_3.2.1 ChAMPdata_2.38.0
[13] minfi_1.52.1 bumphunter_1.48.0
[15] locfit_1.5-9.10 iterators_1.0.14
[17] foreach_1.5.2 Biostrings_2.74.1
[19] XVector_0.46.0 SummarizedExperiment_1.36.0
[21] Biobase_2.66.0 MatrixGenerics_1.18.1
[23] matrixStats_1.5.0 GenomicRanges_1.58.0
[25] GenomeInfoDb_1.42.1 IRanges_2.40.1
[27] S4Vectors_0.44.0 BiocGenerics_0.52.0
loaded via a namespace (and not attached):
[1] ProtGenerics_1.38.0 bitops_1.0-9
[3] doParallel_1.0.17 httr_1.4.7
[5] RColorBrewer_1.1-3 tools_4.4.2
[7] doRNG_1.8.6.1 backports_1.5.0
[9] R6_2.5.1 HDF5Array_1.34.0
[11] lazyeval_0.2.2 mgcv_1.9-1
[13] Gviz_1.50.0 rhdf5filters_1.18.0
[15] permute_0.9-7 methylumi_2.52.0
[17] ROC_1.82.0 prettyunits_1.2.0
[19] gridExtra_2.3 base64_2.0.2
[21] preprocessCore_1.68.0 cli_3.6.3
[23] wateRmelon_2.12.0 JADE_2.0-4
[25] IlluminaHumanMethylationEPICanno.ilm10b4.hg19_0.6.0 readr_2.1.5
[27] genefilter_1.88.0 goseq_1.58.0
[29] askpass_1.2.1 Rsamtools_2.22.0
[31] txdbmaker_1.2.1 foreign_0.8-88
[33] siggenes_1.80.0 illuminaio_0.48.0
[35] rentrez_1.2.3 lumi_2.58.0
[37] dichromat_2.0-0.1 scrime_1.3.5
[39] BSgenome_1.74.0 limma_3.62.2
[41] impute_1.80.0 rstudioapi_0.17.1
[43] RSQLite_2.3.9 generics_0.1.3
[45] BiocIO_1.16.0 combinat_0.0-8
[47] gtools_3.9.5 dendextend_1.19.0
[49] dplyr_1.1.4 GO.db_3.20.0
[51] Matrix_1.7-1 interp_1.1-6
[53] abind_1.4-8 lifecycle_1.0.4
[55] yaml_2.3.10 edgeR_4.4.1
[57] qvalue_2.38.0 rhdf5_2.50.2
[59] SparseArray_1.6.1 BiocFileCache_2.14.0
[61] grid_4.4.2 blob_1.2.4
[63] promises_1.3.2 ExperimentHub_2.14.0
[65] crayon_1.5.3 lattice_0.22-6
[67] GenomicFeatures_1.58.0 annotate_1.84.0
[69] KEGGREST_1.46.0 pillar_1.10.1
[71] knitr_1.49 beanplot_1.3.1
[73] rjson_0.2.23 marray_1.84.0
[75] codetools_0.2-20 glue_1.8.0
[77] data.table_1.16.4 vctrs_0.6.5
[79] png_0.1-8 gtable_0.3.6
[81] IlluminaHumanMethylation450kanno.ilmn12.hg19_0.6.1 cachem_1.1.0
[83] xfun_0.50 mime_0.12
[85] S4Arrays_1.6.0 survival_3.8-3
[87] shinythemes_1.2.0 fastICA_1.2-7
[89] statmod_1.5.0 nlme_3.1-166
[91] kpmt_0.1.0 bit64_4.6.0-1
[93] bsseq_1.42.0 progress_1.2.3
[95] filelock_1.0.3 nor1mix_1.3-3
[97] affyio_1.76.0 KernSmooth_2.23-26
[99] IlluminaHumanMethylation450kmanifest_0.4.0 rpart_4.1.24
[101] colorspace_2.1-1 DBI_1.2.3
[103] Hmisc_5.2-2 nnet_7.3-20
[105] DNAcopy_1.80.0 tidyselect_1.2.1
[107] bit_4.5.0.1 compiler_4.4.2
[109] curl_6.1.0 httr2_1.1.0
[111] htmlTable_2.4.3 BiasedUrn_2.0.12
[113] xml2_1.3.6 plotly_4.10.4
[115] DelayedArray_0.32.0 rtracklayer_1.66.0
[117] checkmate_2.3.2 scales_1.3.0
[119] affy_1.84.0 quadprog_1.5-8
[121] rappdirs_0.3.3 stringr_1.5.1
[123] digest_0.6.37 rmarkdown_2.29
[125] htmltools_0.5.8.1 pkgconfig_2.0.3
[127] jpeg_0.1-10 base64enc_0.1-3
[129] sparseMatrixStats_1.18.0 dbplyr_2.5.0
[131] fastmap_1.2.0 ensembldb_2.30.0
[133] rlang_1.1.4 htmlwidgets_1.6.4
[135] UCSC.utils_1.2.0 shiny_1.10.0
[137] DelayedMatrixStats_1.28.1 jsonlite_1.8.9
[139] BiocParallel_1.40.0 mclust_6.1.1
[141] VariantAnnotation_1.52.0 RCurl_1.98-1.16
[143] magrittr_2.0.3 Formula_1.2-5
[145] GenomeInfoDbData_1.2.13 Rhdf5lib_1.28.0
[147] munsell_0.5.1 Rcpp_1.0.14
[149] viridis_0.6.5 stringi_1.8.4
[151] nleqslv_3.3.5 zlibbioc_1.52.0
[153] MASS_7.3-64 globaltest_5.60.0
[155] AnnotationHub_3.14.0 plyr_1.8.9
[157] org.Hs.eg.db_3.20.0 deldir_2.0-4
[159] splines_4.4.2 multtest_2.62.0
[161] geneLenDataBase_1.42.0 hms_1.1.3
[163] rngtools_1.5.2 reshape2_1.4.4
[165] biomaRt_2.62.0 BiocVersion_3.20.0
[167] missMethyl_1.40.0 XML_3.99-0.18
[169] evaluate_1.0.3 latticeExtra_0.6-30
[171] biovizBase_1.54.0 BiocManager_1.30.25
[173] isva_1.9 httpuv_1.6.15
[175] tzdb_0.4.0 tidyr_1.3.1
[177] openssl_2.3.1 purrr_1.0.2
[179] clue_0.3-66 reshape_0.8.9
[181] ggplot2_3.5.1 xtable_1.8-4
[183] restfulr_0.0.15 AnnotationFilter_1.30.0
[185] later_1.4.1 viridisLite_0.4.2
[187] tibble_3.2.1 memoise_2.0.1
[189] AnnotationDbi_1.68.0 GenomicAlignments_1.42.0
[191] sva_3.54.0
