MAIT metabolomics analysis error
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YL • 0
@yl-23143
Last seen 19 months ago

Hi I am currently trialing out the MAIT package for untargetted metabolomics analysis, and I am running into issues with this command and I am not too sure how to resolve the error. Any assistance is much appreciated. Thanks

MAIT <- spectralSigFeatures(MAIT.object = MAIT, pvalue = 0.05, p.adj = "none", scale = FALSE)

Skipping peak aggregation step...Error in (which(paste("X", classes[length(classes)], sep = "") == colnames(peakList)) + : argument of length 0

sessionInfo() R version 3.6.0 (2019-04-26) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Red Hat Enterprise Linux Server 7.7 (Maipo)

Matrix products: default BLAS: /usr/lib64/libblas.so.3.4.2 LAPACK: /usr/lib64/liblapack.so.3.4.2

locale: [1] LCCTYPE=enUS.UTF-8 LCNUMERIC=C
[3] LC
TIME=enUS.UTF-8 LCCOLLATE=enUS.UTF-8
[5] LC
MONETARY=enUS.UTF-8 LCMESSAGES=enUS.UTF-8
[7] LC
PAPER=enUS.UTF-8 LCNAME=C
[9] LCADDRESS=C LCTELEPHONE=C
[11] LCMEASUREMENT=enUS.UTF-8 LC_IDENTIFICATION=C

attached base packages: [1] stats4 parallel stats graphics grDevices utils datasets [8] methods base

other attached packages: [1] MAIT1.20.0 pls2.7-2 CAMERA1.42.0
[4] xcms
3.8.2 MSnbase2.12.0 ProtGenerics1.18.0 [7] S4Vectors0.24.3 mzR2.20.0 Rcpp1.0.3
[10] BiocParallel
1.20.1 Biobase2.46.0 BiocGenerics0.32.0

loaded via a namespace (and not attached): [1] colorspace1.4-1 class7.3-15 htmlTable1.13.3
[4] base64enc
0.1-3 rstudioapi0.11 affyio1.56.0
[7] prodlim2019.11.13 lubridate1.7.4 codetools0.2-16
[10] splines
3.6.0 ncdf41.17 doParallel1.0.15
[13] impute1.60.0 robustbase0.93-5 knitr1.28
[16] spam
2.5-1 Formula1.2-3 pROC1.16.1
[19] caret6.0-85 RhpcBLASctl0.20-17 cluster2.1.0
[22] vsn
3.54.0 png0.1-7 graph1.64.0
[25] shiny1.4.0 BiocManager1.30.10 compiler3.6.0
[28] backports
1.1.5 fastmap1.0.1 assertthat0.2.1
[31] Matrix1.2-18 lazyeval0.2.2 limma3.42.2
[34] later
1.0.0 acepack1.4.1 htmltools0.4.0
[37] tools3.6.0 igraph1.2.4.2 dotCall641.0-0
[40] agricolae
1.3-2 gtable0.3.0 glue1.3.1
[43] affy1.64.0 RANN2.6.1 reshape21.4.3
[46] dplyr
0.8.5 maps3.3.0 MALDIquant1.19.3
[49] multtest2.42.0 gdata2.18.0 preprocessCore1.48.0 [52] nlme3.1-143 iterators1.0.12 timeDate3043.102
[55] xfun0.12 gower0.2.1 stringr1.4.0
[58] mime
0.9 miniUI0.1.1.1 lifecycle0.1.0
[61] gtools3.8.1 XML3.99-0.3 DEoptimR1.0-8
[64] zlibbioc
1.32.0 MASS7.3-51.5 scales1.1.0
[67] ipred0.9-9 promises1.1.0 pcaMethods1.78.0
[70] RBGL
1.62.1 MassSpecWavelet1.52.0 RColorBrewer1.1-2
[73] fields10.3 gridExtra2.3 ggplot23.2.1
[76] rpart
4.1-15 latticeExtra0.6-29 stringi1.4.6
[79] AlgDesign1.2.0 highr0.8 klaR0.6-15
[82] foreach
1.4.8 e10711.7-3 checkmate2.0.0
[85] caTools1.18.0 boot1.3-24 lava1.6.6
[88] rlang
0.4.5 pkgconfig2.0.3 bitops1.0-6
[91] mzID1.24.0 lattice0.20-38 purrr0.3.3
[94] recipes
0.1.9 htmlwidgets1.5.1 tidyselect1.0.0
[97] plyr1.8.6 magrittr1.5 R62.4.1
[100] IRanges
2.20.2 gplots3.0.3 generics0.0.2
[103] Hmisc4.3-1 combinat0.0-8 pillar1.4.3
[106] foreign
0.8-74 withr2.1.2 survival3.1-8
[109] nnet7.3-12 tibble2.1.3 questionr0.7.0
[112] crayon
1.3.4 KernSmooth2.23-16 jpeg0.1-8.1
[115] grid3.6.0 data.table1.12.8 ModelMetrics1.2.2.1
[118] digest
0.6.25 xtable1.8-4 httpuv1.5.2
[121] munsell0.5.0 plsgenomics1.5-2

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