ManjotVirdee
commented
5 years ago Hello Raj,
I have encountered the same error you have. After looking into the calculate_MS() function code I implemented my solution from the 'na_heatmap()' issue; which in this case goes as follows:
trace(calculate_MS, edit=TRUE) # change line 10 from: for (x in 1:nrow(df)) { # to: for (x in 1:nrow(res_df)) {
I am reasonably certain that this solves the problem, but my data does not differentiate between subgroups. Good luck Raj,
Best, M. Virdee
andreasmock
RDastgh1
Hi Andreas Mock,
Thanks for the nice R package to perform basic Metabolomic analysis. I was able to get through most of the steps. However, i got an error while calculating the module significance in relating sample trait to the module. The following is the error and the session info. Could please see if there is bug in the function. I looked into it, but nothing was obvious.
Error in
$<-.data.frame(*tmp*, av_fold_change, value = c(0, -0.499286089069959, : replacement has 87 rows, data has 86Matrix products: default
locale: [1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252
[3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C
[5] LC_TIME=English_United States.1252
attached base packages: [1] grid parallel stats4 stats graphics grDevices utils datasets methods base
other attached packages: [1] WGCNA_1.63 fastcluster_1.1.25 dynamicTreeCut_1.63-1 MetaboDiff_0.9.2
[5] forcats_0.3.0 stringr_1.3.0 dplyr_0.7.4 purrr_0.2.4
[9] readr_1.1.1 tidyr_0.8.0 tibble_1.4.2 ggplot2_2.2.1
[13] tidyverse_1.2.1 ComplexHeatmap_1.17.1 MultiAssayExperiment_1.4.9 SummarizedExperiment_1.8.1 [17] DelayedArray_0.4.1 matrixStats_0.53.1 Biobase_2.38.0 GenomicRanges_1.30.3
[21] GenomeInfoDb_1.14.0 IRanges_2.12.0 S4Vectors_0.16.0 BiocGenerics_0.24.0
[25] devtools_1.13.5 BiocInstaller_1.28.0
loaded via a namespace (and not attached): [1] readxl_1.1.0 backports_1.1.2 circlize_0.4.4 Hmisc_4.1-1
[5] plyr_1.8.4 lazyeval_0.2.1 shinydashboard_0.7.0 splines_3.4.3
[9] robust_0.4-18 digest_0.6.15 foreach_1.4.4 htmltools_0.3.6
[13] GO.db_3.5.0 magrittr_1.5 checkmate_1.8.5 memoise_1.1.0
[17] fit.models_0.5-14 cluster_2.0.6 doParallel_1.0.11 limma_3.34.9
[21] annotate_1.56.2 modelr_0.1.2 colorspace_1.3-2 blob_1.1.1
[25] rvest_0.3.2 rrcov_1.4-4 haven_1.1.1 crayon_1.3.4
[29] RCurl_1.95-4.10 jsonlite_1.5 genefilter_1.60.0 bindr_0.1.1
[33] impute_1.52.0 ape_5.1 survival_2.41-3 iterators_1.0.9
[37] glue_1.2.0 gtable_0.2.0 zlibbioc_1.24.0 XVector_0.18.0
[41] GetoptLong_0.1.7 shape_1.4.4 DEoptimR_1.0-8 scales_0.5.0
[45] vsn_3.46.0 mvtnorm_1.0-7 DBI_0.8 Rcpp_0.12.16
[49] xtable_1.8-2 htmlTable_1.11.2 foreign_0.8-69 bit_1.1-12
[53] preprocessCore_1.40.0 Formula_1.2-2 tsne_0.1-3 htmlwidgets_1.0
[57] httr_1.3.1 RColorBrewer_1.1-2 acepack_1.4.1 XML_3.98-1.10
[61] pkgconfig_2.0.1 nnet_7.3-12 labeling_0.3 rlang_0.2.0
[65] reshape2_1.4.3 AnnotationDbi_1.40.0 munsell_0.4.3 cellranger_1.1.0
[69] tools_3.4.3 cli_1.0.0 RSQLite_2.1.0 broom_0.4.4
[73] yaml_2.1.18 knitr_1.20 bit64_0.9-7 robustbase_0.92-8
[77] bindrcpp_0.2.2 nlme_3.1-131 mime_0.5 xml2_1.2.0
[81] compiler_3.4.3 rstudioapi_0.7 curl_3.2 affyio_1.48.0
[85] pcaPP_1.9-73 stringi_1.1.7 lattice_0.20-35 Matrix_1.2-12
[89] psych_1.8.4 pillar_1.2.1 GlobalOptions_0.1.0 data.table_1.10.4-3
[93] cowplot_0.9.3 bitops_1.0-6 httpuv_1.3.6.2 R6_2.2.2
[97] latticeExtra_0.6-28 affy_1.56.0 gridExtra_2.3 codetools_0.2-15
[101] MASS_7.3-47 assertthat_0.2.0 rjson_0.2.20 withr_2.1.2
[105] mnormt_1.5-5 GenomeInfoDbData_1.0.0 hms_0.4.2 rpart_4.1-11
[109] git2r_0.21.0 shiny_1.0.5 lubridate_1.7.4 base64enc_0.1-3
Thank you.
Raj