Hi
I am recently learning the MetaboAnalystR (3.2.0) in R following the detailed instruction on the website.
However, errors occurred when I tried to run the following lines
mSet<-MetaboAnalystR::InitDataObjects("pktable", "stat", FALSE)
mSet<- Read.TextData(mSet, "metaboanalyst_input.csv", "colu", "disc")
Firstly, the "InitDataObjects" function could be overridden by the same function in the OptiLCMS package, which would throw a null mSet. I replaced the line with:
MetaboAnalystR::InitDataObjects("pktable", "stat", FALSE)
which give a mSet with dataSet and analSet.
Then, the second line would report the "object 'anal.type' not found".
I checked the function "Read.TextData" and found there is no input for anal.type.
I am wondering if the anal.type is meant for mSetObj$analSet$type ?
Similar questions could be found in https://github.com/xia-lab/MetaboAnalystR/issues/218 and https://github.com/xia-lab/MetaboAnalystR/issues/215.
Thank you for your time and effort !
Looking forward to your reply.
Siwei
R version 4.2.1 (2022-06-23 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 22621)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.utf8 LC_CTYPE=English_United States.utf8
[3] LC_MONETARY=English_United States.utf8 LC_NUMERIC=C
[5] LC_TIME=English_United States.utf8
attached base packages:
[1] stats4 stats graphics grDevices utils datasets methods base
other attached packages:
[1] OptiLCMS_0.99.4 MSnbase_2.24.0 ProtGenerics_1.30.0 S4Vectors_0.36.0 mzR_2.32.0
[6] Rcpp_1.0.9 BiocParallel_1.32.1 Biobase_2.58.0 BiocGenerics_0.44.0 MetaboAnalystR_3.2.0
loaded via a namespace (and not attached):
[1] estimability_1.4.1 rappdirs_0.3.3 ModelMetrics_1.2.2.2
[4] tidyr_1.2.1 ggplot2_3.4.0 bit64_4.0.5
[7] knitr_1.40 multcomp_1.4-20 DelayedArray_0.24.0
[10] data.table_1.14.6 rpart_4.1.19 KEGGREST_1.38.0
[13] hardhat_1.2.0 RCurl_1.98-1.9 GEOquery_2.66.0
[16] doParallel_1.0.17 generics_0.1.3 snow_0.4-4
[19] preprocessCore_1.60.0 cowplot_1.1.1 TH.data_1.1-1
[22] RSQLite_2.2.18 RApiSerialize_0.1.2 future_1.29.0
[25] bit_4.0.5 tzdb_0.3.0 xml2_1.3.3
[28] lubridate_1.9.0 httpuv_1.6.6 SummarizedExperiment_1.28.0
[31] assertthat_0.2.1 gower_1.0.0 xfun_0.35
[34] celldex_1.8.0 hms_1.1.2 promises_1.2.0.1
[37] fansi_1.0.3 scrime_1.3.5 progress_1.2.2
[40] caTools_1.18.2 dbplyr_2.2.1 igraph_1.3.5
[43] DBI_1.1.3 htmlwidgets_1.5.4 purrr_0.3.5
[46] ellipsis_0.3.2 dplyr_1.0.10 backports_1.4.1
[49] RcppParallel_5.1.5 deldir_1.0-6 sparseMatrixStats_1.10.0
[52] MatrixGenerics_1.10.0 vctrs_0.5.1 Cairo_1.6-0
[55] entropy_1.3.1 caret_6.0-93 cachem_1.0.6
[58] withr_2.5.0 checkmate_2.1.0 emmeans_1.8.2
[61] prettyunits_1.1.1 cluster_2.1.4 ExperimentHub_2.6.0
[64] lazyeval_0.2.2 crayon_1.5.2 labeling_0.4.2
[67] edgeR_3.40.0 recipes_1.0.3 pkgconfig_2.0.3
[70] GenomeInfoDb_1.34.3 nlme_3.1-160 nnet_7.3-18
[73] rlang_1.0.6 globals_0.16.2 RJSONIO_1.3-1.6
[76] lifecycle_1.0.3 sandwich_3.0-2 filelock_1.0.2
[79] affyio_1.68.0 BiocFileCache_2.6.0 AnnotationHub_3.6.0
[82] matrixStats_0.63.0 graph_1.76.0 Matrix_1.5-3
[85] zoo_1.8-11 base64enc_0.1-3 png_0.1-7
[88] viridisLite_0.4.1 stringfish_0.15.7 rsm_2.10.3
[91] bitops_1.0-7 KernSmooth_2.23-20 pROC_1.18.0
[94] Biostrings_2.66.0 blob_1.2.3 DelayedMatrixStats_1.20.0
[97] stringr_1.4.1 parallelly_1.32.1 readr_2.1.3
[100] jpeg_0.1-9 scales_1.2.1 memoise_2.0.1
[103] magrittr_2.0.3 plyr_1.8.8 gplots_3.1.3
[106] zlibbioc_1.44.0 compiler_4.2.1 RColorBrewer_1.1-3
[109] pcaMethods_1.90.0 clue_0.3-63 cli_3.4.1
[112] affy_1.76.0 XVector_0.38.0 listenv_0.8.0
[115] htmlTable_2.4.1 Formula_1.2-4 MASS_7.3-58.1
[118] tidyselect_1.2.0 vsn_3.66.0 stringi_1.7.8
[121] yaml_2.3.6 locfit_1.5-9.6 latticeExtra_0.6-30
[124] MALDIquant_1.22 ggrepel_0.9.2 grid_4.2.1
[127] fastmatch_1.1-3 tools_4.2.1 timechange_0.1.1
[130] future.apply_1.10.0 parallel_4.2.1 rstudioapi_0.14
[133] qs_0.25.4 MsCoreUtils_1.10.0 foreach_1.5.2
[136] foreign_0.8-83 crmn_0.0.21 gridExtra_2.3
[139] prodlim_2019.11.13 farver_2.1.1 mzID_1.36.0
[142] digest_0.6.30 BiocManager_1.30.19 shiny_1.7.3
[145] lava_1.7.0 GenomicRanges_1.50.1 siggenes_1.72.0
[148] BiocVersion_3.16.0 later_1.3.0 ncdf4_1.19
[151] httr_1.4.4 AnnotationDbi_1.60.0 colorspace_2.0-3
[154] XML_3.99-0.12 IRanges_2.32.0 splines_4.2.1
[157] RBGL_1.74.0 multtest_2.54.0 plotly_4.10.1
[160] xtable_1.8-4 jsonlite_1.8.3 timeDate_4021.106
[163] glasso_1.11 ipred_0.9-13 R6_2.5.1
[166] Hmisc_4.7-1 pillar_1.8.1 htmltools_0.5.3
[169] mime_0.12 glue_1.6.2 fastmap_1.1.0
[172] class_7.3-20 interactiveDisplayBase_1.36.0 codetools_0.2-18
[175] fgsea_1.24.0 mvtnorm_1.1-3 utf8_1.2.2
[178] lattice_0.20-45 tibble_3.1.8 curl_4.3.3
[181] gtools_3.9.3 interp_1.1-3 survival_3.4-0
[184] limma_3.54.0 munsell_0.5.0 GenomeInfoDbData_1.2.9
[187] iterators_1.0.14 impute_1.72.1 reshape2_1.4.4
[190] gtable_0.3.1
Hi
I am recently learning the MetaboAnalystR (3.2.0) in R following the detailed instruction on the website.
However, errors occurred when I tried to run the following lines
Firstly, the "InitDataObjects" function could be overridden by the same function in the OptiLCMS package, which would throw a null mSet. I replaced the line with:
which give a mSet with dataSet and analSet.
Then, the second line would report the "object 'anal.type' not found".
I checked the function "Read.TextData" and found there is no input for anal.type.
I am wondering if the anal.type is meant for mSetObj$analSet$type ?
Similar questions could be found in https://github.com/xia-lab/MetaboAnalystR/issues/218 and https://github.com/xia-lab/MetaboAnalystR/issues/215.
Thank you for your time and effort !
Looking forward to your reply.
Siwei
R version 4.2.1 (2022-06-23 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 22621)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.utf8 LC_CTYPE=English_United States.utf8
[3] LC_MONETARY=English_United States.utf8 LC_NUMERIC=C
[5] LC_TIME=English_United States.utf8
attached base packages:
[1] stats4 stats graphics grDevices utils datasets methods base
other attached packages:
[1] OptiLCMS_0.99.4 MSnbase_2.24.0 ProtGenerics_1.30.0 S4Vectors_0.36.0 mzR_2.32.0
[6] Rcpp_1.0.9 BiocParallel_1.32.1 Biobase_2.58.0 BiocGenerics_0.44.0 MetaboAnalystR_3.2.0
loaded via a namespace (and not attached):
[1] estimability_1.4.1 rappdirs_0.3.3 ModelMetrics_1.2.2.2
[4] tidyr_1.2.1 ggplot2_3.4.0 bit64_4.0.5
[7] knitr_1.40 multcomp_1.4-20 DelayedArray_0.24.0
[10] data.table_1.14.6 rpart_4.1.19 KEGGREST_1.38.0
[13] hardhat_1.2.0 RCurl_1.98-1.9 GEOquery_2.66.0
[16] doParallel_1.0.17 generics_0.1.3 snow_0.4-4
[19] preprocessCore_1.60.0 cowplot_1.1.1 TH.data_1.1-1
[22] RSQLite_2.2.18 RApiSerialize_0.1.2 future_1.29.0
[25] bit_4.0.5 tzdb_0.3.0 xml2_1.3.3
[28] lubridate_1.9.0 httpuv_1.6.6 SummarizedExperiment_1.28.0
[31] assertthat_0.2.1 gower_1.0.0 xfun_0.35
[34] celldex_1.8.0 hms_1.1.2 promises_1.2.0.1
[37] fansi_1.0.3 scrime_1.3.5 progress_1.2.2
[40] caTools_1.18.2 dbplyr_2.2.1 igraph_1.3.5
[43] DBI_1.1.3 htmlwidgets_1.5.4 purrr_0.3.5
[46] ellipsis_0.3.2 dplyr_1.0.10 backports_1.4.1
[49] RcppParallel_5.1.5 deldir_1.0-6 sparseMatrixStats_1.10.0
[52] MatrixGenerics_1.10.0 vctrs_0.5.1 Cairo_1.6-0
[55] entropy_1.3.1 caret_6.0-93 cachem_1.0.6
[58] withr_2.5.0 checkmate_2.1.0 emmeans_1.8.2
[61] prettyunits_1.1.1 cluster_2.1.4 ExperimentHub_2.6.0
[64] lazyeval_0.2.2 crayon_1.5.2 labeling_0.4.2
[67] edgeR_3.40.0 recipes_1.0.3 pkgconfig_2.0.3
[70] GenomeInfoDb_1.34.3 nlme_3.1-160 nnet_7.3-18
[73] rlang_1.0.6 globals_0.16.2 RJSONIO_1.3-1.6
[76] lifecycle_1.0.3 sandwich_3.0-2 filelock_1.0.2
[79] affyio_1.68.0 BiocFileCache_2.6.0 AnnotationHub_3.6.0
[82] matrixStats_0.63.0 graph_1.76.0 Matrix_1.5-3
[85] zoo_1.8-11 base64enc_0.1-3 png_0.1-7
[88] viridisLite_0.4.1 stringfish_0.15.7 rsm_2.10.3
[91] bitops_1.0-7 KernSmooth_2.23-20 pROC_1.18.0
[94] Biostrings_2.66.0 blob_1.2.3 DelayedMatrixStats_1.20.0
[97] stringr_1.4.1 parallelly_1.32.1 readr_2.1.3
[100] jpeg_0.1-9 scales_1.2.1 memoise_2.0.1
[103] magrittr_2.0.3 plyr_1.8.8 gplots_3.1.3
[106] zlibbioc_1.44.0 compiler_4.2.1 RColorBrewer_1.1-3
[109] pcaMethods_1.90.0 clue_0.3-63 cli_3.4.1
[112] affy_1.76.0 XVector_0.38.0 listenv_0.8.0
[115] htmlTable_2.4.1 Formula_1.2-4 MASS_7.3-58.1
[118] tidyselect_1.2.0 vsn_3.66.0 stringi_1.7.8
[121] yaml_2.3.6 locfit_1.5-9.6 latticeExtra_0.6-30
[124] MALDIquant_1.22 ggrepel_0.9.2 grid_4.2.1
[127] fastmatch_1.1-3 tools_4.2.1 timechange_0.1.1
[130] future.apply_1.10.0 parallel_4.2.1 rstudioapi_0.14
[133] qs_0.25.4 MsCoreUtils_1.10.0 foreach_1.5.2
[136] foreign_0.8-83 crmn_0.0.21 gridExtra_2.3
[139] prodlim_2019.11.13 farver_2.1.1 mzID_1.36.0
[142] digest_0.6.30 BiocManager_1.30.19 shiny_1.7.3
[145] lava_1.7.0 GenomicRanges_1.50.1 siggenes_1.72.0
[148] BiocVersion_3.16.0 later_1.3.0 ncdf4_1.19
[151] httr_1.4.4 AnnotationDbi_1.60.0 colorspace_2.0-3
[154] XML_3.99-0.12 IRanges_2.32.0 splines_4.2.1
[157] RBGL_1.74.0 multtest_2.54.0 plotly_4.10.1
[160] xtable_1.8-4 jsonlite_1.8.3 timeDate_4021.106
[163] glasso_1.11 ipred_0.9-13 R6_2.5.1
[166] Hmisc_4.7-1 pillar_1.8.1 htmltools_0.5.3
[169] mime_0.12 glue_1.6.2 fastmap_1.1.0
[172] class_7.3-20 interactiveDisplayBase_1.36.0 codetools_0.2-18
[175] fgsea_1.24.0 mvtnorm_1.1-3 utf8_1.2.2
[178] lattice_0.20-45 tibble_3.1.8 curl_4.3.3
[181] gtools_3.9.3 interp_1.1-3 survival_3.4-0
[184] limma_3.54.0 munsell_0.5.0 GenomeInfoDbData_1.2.9
[187] iterators_1.0.14 impute_1.72.1 reshape2_1.4.4
[190] gtable_0.3.1