Open priyanka-1802 opened 10 months ago
Hi, thanks for reporting. To help us, it is always best to provide a copy&pasteable code snippet so we can reproduce things. Another easy thing to try after an error occurs is to run traceback()
which gives the context where the error occurred.
In this case you seem to have hit an issue that featureDefinitions()
is a method expecting an MsFeatureData
, where you supplied an xcmsSet
which is the old, deprecated XCMS data structure.
Yours, Steffen
Hi, we tried to replicate the code in RAMClustR vignette. However, I providing the code below for your immediate reference:
library(BiocManager) library(xcms) library(faahKO) library(devtools) library(RAMClustR)
cdfpath <- system.file("cdf", package = "faahKO")
cdffiles <- list.files(cdfpath, recursive = TRUE, full.names = TRUE)
xset <- xcmsSet(cdffiles)
xset <- group(xset)
xset <- retcor(xset, family = "symmetric", plottype = NULL)
xset <- group(xset, bw = 10)
xset <- fillPeaks(xset)
experiment <- defineExperiment(csv = TRUE) # experiment <- defineExperiment(force.skip = TRUE)
RC <- ramclustR(xcmsObj = xset, ExpDes=experiment)
We got the error in the last step stating "Error in (function (classes, fdef, mtable) : unable to find an inherited method for function ‘featureDefinitions’ for signature "xcmsSet"".
The traceback of error is provided below:
6: stop(gettextf("unable to find an inherited method for function %s for signature %s", sQuote(fdef@generic), sQuote(cnames)), domain = NA) 5: (function (classes, fdef, mtable) { methods <- .findInheritedMethods(classes, fdef, mtable) if (length(methods) == 1L) return(methods[[1L]]) else if (length(methods) == 0L) { cnames <- paste0("\"", vapply(classes, as.character, ""), "\"", collapse = ", ") stop(gettextf("unable to find an inherited method for function %s for signature %s", sQuote(fdef@generic), sQuote(cnames)), domain = NA) } else stop("Internal error in finding inherited methods; didn't return a unique method", domain = NA) })(list(structure("xcmsSet", package = "xcms")), new("standardGeneric", .Data = function (object, ...) standardGeneric("featureDefinitions"), generic = structure("featureDefinitions", package = "xcms"), package = "xcms", group = list(), valueClass = character(0), signature = "object", default = NULL, skeleton = (function (object, ...) stop(gettextf("invalid call in method dispatch to '%s' (no default method)", ... 4: xcms::featureDefinitions(xcmsObj) 3: rownames(xcms::featureDefinitions(xcmsObj)) 2: rc.get.xcms.data(xcmsObj = xcmsObj, taglocation = taglocation, MStag = MStag, MSMStag = idMSMStag, ExpDes = ExpDes, mzdec = mzdec, ensure.no.na = replace.zeros) 1: ramclustR(xcmsObj = xset, ExpDes = experiment)
Hence, we are confused how the xcmsSet object is handled in the RAMClustR vignette tutorial? Is that mean that the vignette of RAMClustR has to be updated?
Thanks, Priyanka
Hi,
we tried to perform RAMClustR by importing the xcms preprocessed data as provided in your vignette. However, we couldn't proceed further due to the following error:
Error in (function (classes, fdef, mtable) : unable to find an inherited method for function ‘featureDefinitions’ for signature ‘"xcmsSet"’
Note: we also got the same error on trying with the dataset from "faahKO" library that had been demonstrated in the RAMClustR vignette.
The session info of the same is given below for your reference:
Matrix products: default
locale: [1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252 LC_MONETARY=English_United States.1252 [4] LC_NUMERIC=C LC_TIME=English_United States.1252
time zone: America/New_York tzcode source: internal
attached base packages: [1] stats4 stats graphics grDevices utils datasets methods base
other attached packages: [1] devtools_2.4.5 usethis_2.2.2 RAMClustR_1.3.1 SummarizedExperiment_1.32.0 [5] GenomicRanges_1.54.1 GenomeInfoDb_1.38.2 IRanges_2.36.0 MatrixGenerics_1.14.0
[9] matrixStats_1.2.0 MsExperiment_1.4.0 pheatmap_1.0.12 pander_0.6.5
[13] RColorBrewer_1.1-3 faahKO_1.40.0 xcms_4.0.1 MSnbase_2.28.1
[17] ProtGenerics_1.34.0 S4Vectors_0.40.2 mzR_2.36.0 Rcpp_1.0.11
[21] Biobase_2.62.0 BiocGenerics_0.48.1 BiocParallel_1.36.0
loaded via a namespace (and not attached): [1] rstudioapi_0.15.0 MultiAssayExperiment_1.28.0 magrittr_2.0.3 farver_2.1.1
[5] MALDIquant_1.22.1 fs_1.6.3 zlibbioc_1.48.0 vctrs_0.6.4
[9] multtest_2.58.0 memoise_2.0.1 RCurl_1.98-1.13 MultiDataSet_1.28.0
[13] htmltools_0.5.7 S4Arrays_1.2.0 progress_1.2.3 curl_5.2.0
[17] dynamicTreeCut_1.63-1 SparseArray_1.2.2 mzID_1.40.0 desc_1.4.3
[21] htmlwidgets_1.6.4 plyr_1.8.9 impute_1.76.0 cachem_1.0.8
[25] qqman_0.1.9 igraph_1.6.0 mime_0.12 lifecycle_1.0.4
[29] iterators_1.0.14 ropls_1.32.0 pkgconfig_2.0.3 Matrix_1.6-1.1
[33] R6_2.5.1 fastmap_1.1.1 GenomeInfoDbData_1.2.11 shiny_1.7.5.1
[37] clue_0.3-65 digest_0.6.33 pcaMethods_1.94.0 colorspace_2.1-0
[41] ps_1.7.5 pkgload_1.3.3 Spectra_1.12.0 fansi_1.0.6
[45] abind_1.4-5 compiler_4.3.1 remotes_2.4.2.1 proxy_0.4-27
[49] doParallel_1.0.17 pkgbuild_1.4.3 MASS_7.3-60 sessioninfo_1.2.2
[53] DelayedArray_0.28.0 tools_4.3.1 httpuv_1.6.13 glue_1.6.2
[57] callr_3.7.3 promises_1.2.1 QFeatures_1.12.0 grid_4.3.1
[61] cluster_2.1.4 generics_0.1.3 snow_0.4-4 gtable_0.3.4
[65] class_7.3-22 preprocessCore_1.64.0 hms_1.1.3 MetaboCoreUtils_1.10.0
[69] utf8_1.2.4 XVector_0.42.0 stringr_1.5.1 RANN_2.6.1
[73] foreach_1.5.2 pillar_1.9.0 limma_3.58.1 later_1.3.2
[77] robustbase_0.99-1 splines_4.3.1 dplyr_1.1.4 lattice_0.21-9
[81] survival_3.5-7 tidyselect_1.2.0 miniUI_0.1.1.1 statmod_1.5.0
[85] DEoptimR_1.1-3 stringi_1.7.12 lazyeval_0.2.2 codetools_0.2-19
[89] MsCoreUtils_1.14.1 tibble_3.2.1 BiocManager_1.30.22 cli_3.6.1
[93] affyio_1.72.0 xtable_1.8-4 processx_3.8.3 munsell_0.5.0
[97] MassSpecWavelet_1.68.0 XML_3.99-0.16 fastcluster_1.2.3 parallel_4.3.1
[101] ellipsis_0.3.2 ggplot2_3.4.4 prettyunits_1.2.0 profvis_0.3.8
[105] calibrate_1.7.7 urlchecker_1.0.1 AnnotationFilter_1.26.0 bitops_1.0-7
[109] MsFeatures_1.10.0 scales_1.3.0 affy_1.80.0 e1071_1.7-14
[113] ncdf4_1.22 purrr_1.0.2 crayon_1.5.2 rlang_1.1.1
[117] vsn_3.70.0