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Hi
I am trying to use DEP to identify differentially expressed proteins in treated and untreated samples. I have created a SummarizedExperiment out of my data, however, at the filtering step I am getting an error that I cannot understand. Even if I am setting a filtering threshold in the proposed range, the function returns an error ...
less_stringent_filter <- filter_missval(data_se, thr = 0)
Error in filter_missval(data_se, thr = 0) :
invalid filter threshold applied
Run filter_missval() with a threshold ranging from 0 to 3
I went into the source code to see how the thresholds are calculated and they are based on replicates. I run the source code separately and indeed the function should not return an error. I would appreciate any kind of tips on how to solve this.
> sessionInfo()
R version 4.0.3 (2020-10-10)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.2 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=nb_NO.UTF-8
[4] LC_COLLATE=en_US.UTF-8 LC_MONETARY=nb_NO.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=nb_NO.UTF-8 LC_NAME=C LC_ADDRESS=C
[10] LC_TELEPHONE=C LC_MEASUREMENT=nb_NO.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats4 parallel grid stats graphics grDevices utils datasets
[9] methods base
other attached packages:
[1] SummarizedExperiment_1.20.0 GenomicRanges_1.42.0 GenomeInfoDb_1.26.2
[4] IRanges_2.24.1 S4Vectors_0.28.1 MatrixGenerics_1.2.1
[7] matrixStats_0.58.0 vsn_3.58.0 Biobase_2.50.0
[10] BiocGenerics_0.36.0 ggpubr_0.4.0 RColorBrewer_1.1-2
[13] VennDiagram_1.6.20 futile.logger_1.4.3 proBatch_1.3.0
[16] forcats_0.5.1 stringr_1.4.0 dplyr_1.0.4
[19] purrr_0.3.4 readr_1.4.0 tidyr_1.1.3
[22] tibble_3.1.0 ggplot2_3.3.3 tidyverse_1.3.0
[25] DEP_1.12.0
loaded via a namespace (and not attached):
[1] utf8_1.1.4 shinydashboard_0.7.1 gmm_1.6-6
[4] tidyselect_1.1.0 lme4_1.1-26 RSQLite_2.2.3
[7] AnnotationDbi_1.52.0 htmlwidgets_1.5.3 BiocParallel_1.24.1
[10] norm_1.0-9.5 munsell_0.5.0 codetools_0.2-16
[13] preprocessCore_1.52.1 statmod_1.4.35 DT_0.17
[16] withr_2.4.1 colorspace_2.0-0 ggfortify_0.4.11
[19] knitr_1.31 rstudioapi_0.13 ggsignif_0.6.1
[22] mzID_1.28.0 labeling_0.4.2 GenomeInfoDbData_1.2.4
[25] farver_2.1.0 bit64_4.0.5 pheatmap_1.0.12
[28] rprojroot_2.0.2 vctrs_0.3.6 generics_0.1.0
[31] lambda.r_1.2.4 xfun_0.21 fastcluster_1.1.25
[34] R6_2.5.0 doParallel_1.0.16 clue_0.3-58
[37] locfit_1.5-9.4 bitops_1.0-6 cachem_1.0.4
[40] DelayedArray_0.16.2 assertthat_0.2.1 promises_1.2.0.1
[43] scales_1.1.1 nnet_7.3-14 gtable_0.3.0
[46] sva_3.38.0 Cairo_1.5-12.2 affy_1.68.0
[49] WGCNA_1.70-3 sandwich_3.0-0 rlang_0.4.10
[52] genefilter_1.72.1 mzR_2.24.1 GlobalOptions_0.1.2
[55] splines_4.0.3 rstatix_0.7.0 lazyeval_0.2.2
[58] impute_1.64.0 broom_0.7.5 checkmate_2.0.0
[61] abind_1.4-5 BiocManager_1.30.10 reshape2_1.4.4
[64] modelr_0.1.8 backports_1.2.1 httpuv_1.5.5
[67] Hmisc_4.5-0 tools_4.0.3 affyio_1.60.0
[70] ellipsis_0.3.1 dynamicTreeCut_1.63-1 MSnbase_2.16.1
[73] Rcpp_1.0.6 plyr_1.8.6 base64enc_0.1-3
[76] zlibbioc_1.36.0 RCurl_1.98-1.2 rpart_4.1-15
[79] viridis_0.5.1 GetoptLong_1.0.5 cowplot_1.1.1
[82] zoo_1.8-8 haven_2.3.1 cluster_2.1.0
[85] fs_1.5.0 tinytex_0.30 magrittr_2.0.1
[88] futile.options_1.0.1 data.table_1.14.0 openxlsx_4.2.3
[91] circlize_0.4.12 reprex_1.0.0 pcaMethods_1.82.0
[94] mvtnorm_1.1-1 ProtGenerics_1.22.0 pkgload_1.2.0
[97] hms_1.0.0 mime_0.10 xtable_1.8-4
[100] XML_3.99-0.5 rio_0.5.26 jpeg_0.1-8.1
[103] readxl_1.3.1 gridExtra_2.3 shape_1.4.5
[106] testthat_3.0.2 compiler_4.0.3 ncdf4_1.17
[109] crayon_1.4.1 minqa_1.2.4 htmltools_0.5.1.1
[112] mgcv_1.8-33 later_1.1.0.1 Formula_1.2-4
[115] lubridate_1.7.10 pvca_1.30.0 DBI_1.1.1
[118] formatR_1.7 corrplot_0.84 dbplyr_2.1.0
[121] ComplexHeatmap_2.7.1 MASS_7.3-53 tmvtnorm_1.4-10
[124] boot_1.3-25 car_3.0-10 wesanderson_0.3.6
[127] Matrix_1.2-18 cli_2.3.1 imputeLCMD_2.0
[130] pkgconfig_2.0.3 foreign_0.8-79 MALDIquant_1.19.3
[133] xml2_1.3.2 foreach_1.5.1 annotate_1.68.0
[136] XVector_0.30.0 rvest_0.3.6 digest_0.6.27
[139] cellranger_1.1.0 htmlTable_2.1.0 edgeR_3.32.1
[142] curl_4.3 shiny_1.6.0 rjson_0.2.20
[145] nloptr_1.2.2.2 lifecycle_1.0.0 nlme_3.1-149
[148] jsonlite_1.7.2 carData_3.0-4 desc_1.2.0
[151] viridisLite_0.3.0 limma_3.46.0 fansi_0.4.2
[154] pillar_1.5.0 lattice_0.20-41 fastmap_1.1.0
[157] httr_1.4.2 survival_3.2-7 GO.db_3.12.1
[160] glue_1.4.2 zip_2.1.1 png_0.1-7
[163] iterators_1.0.13 bit_4.0.4 stringi_1.5.3
[166] blob_1.2.1 latticeExtra_0.6-29 memoise_2.0.0
Hi, can we have a look at your data_se object ?
Hi, would that be enough? Not sure what I should show exactly.
Yes thanks. And what is the result of
max(colData(data_se)$replicate)? You said you ran the source code separately and did it work ?It returns 3. I did not work with the source code, but I run the code chunk that returned the error in order to confirm that the range of threshold was the correct one.