Error in the SCDC_ENSEMBL function

[iaradsouza1]

Hi there!

I'm testing the SCDC package to use in one of my analysis. I'm following the code from the vignette for bulk RNA analysis, however, I'm not being able to follow the code provided on the vignette. Bellow is the reprex formatted output and the session info.

The error is the following:

Error in switch(method, BR = lad.fit.BR(x, y, tol), EM = lad.fit.EM(x, : EXPR must be a vector of length 1

library(SCDC)

fadista_77 <- readRDS("/media/iaradsouza/DATA1/Github/mdd-deconvolution/data/fadista_77.rds")
qc.baron <- readRDS("/media/iaradsouza/DATA1/Github/mdd-deconvolution/data/qc_baron.rds")
qc.seger <- readRDS("/media/iaradsouza/DATA1/Github/mdd-deconvolution/data/qc_segerstolpe.rds")

fadista.healthy.ens <- SCDC_ENSEMBLE(bulk.eset = fadista_77[,fadista_77$hba1c_class2 == "Normal"], sc.eset.list = list(baronh = qc.baron$sc.eset.qc, segerh = qc.seger$sc.eset.qc), ct.varname = "cluster",
                                   sample = "sample", truep = NULL, ct.sub =  c("alpha","beta","delta","gamma","acinar","ductal"), search.length = 0.01, grid.search = T)  
#> Creating Basis Matrix adjusted for maximal variance weight
#> Used 16150 common genes...
#> Used 6 cell types in deconvolution...
#> Sub1 has common genes 15400 ...
#> WNNLS Converged at iteration 10
#> Sub3 has common genes 15499 ...
#> WNNLS Converged at iteration 41
#> Sub6 has common genes 15249 ...
#> WNNLS Converged at iteration 19
#> Sub8 has common genes 15522 ...
#> WNNLS Converged at iteration 160
#> Sub13 has common genes 15564 ...
#> WNNLS Converged at iteration 138
#> Sub14 has common genes 15299 ...
#> WNNLS Converged at iteration 16
#> Sub15 has common genes 15252 ...
#> WNNLS Converged at iteration 61
#> Sub16 has common genes 15605 ...
#> WNNLS Converged at iteration 134
#> Sub18 has common genes 15704 ...
#> WNNLS Converged at iteration 94
#> Sub19 has common genes 15549 ...
#> WNNLS Converged at iteration 28
#> Sub21 has common genes 15358 ...
#> WNNLS Converged at iteration 40
#> Sub23 has common genes 15553 ...
#> WNNLS Converged at iteration 80
#> Sub24 has common genes 15639 ...
#> WNNLS Converged at iteration 121
#> Sub26 has common genes 15063 ...
#> WNNLS Converged at iteration 48
#> Sub28 has common genes 15318 ...
#> WNNLS Converged at iteration 27
#> Sub30 has common genes 15197 ...
#> WNNLS Converged at iteration 50
#> Sub31 has common genes 15075 ...
#> WNNLS Converged at iteration 14
#> Sub33 has common genes 15548 ...
#> WNNLS Converged at iteration 63
#> Sub34 has common genes 15564 ...
#> WNNLS Converged at iteration 88
#> Sub36 has common genes 15452 ...
#> WNNLS Converged at iteration 84
#> Sub37 has common genes 15386 ...
#> WNNLS Converged at iteration 91
#> Sub39 has common genes 15450 ...
#> WNNLS Converged at iteration 128
#> Sub40 has common genes 15345 ...
#> WNNLS Converged at iteration 64
#> Sub44 has common genes 15613 ...
#> WNNLS Converged at iteration 74
#> Sub45 has common genes 15578 ...
#> WNNLS Converged at iteration 73
#> Sub47 has common genes 15479 ...
#> WNNLS Converged at iteration 98
#> Sub50 has common genes 15300 ...
#> WNNLS Converged at iteration 15
#> Sub52 has common genes 15548 ...
#> WNNLS Converged at iteration 28
#> Sub57 has common genes 15438 ...
#> WNNLS Converged at iteration 20
#> Sub58 has common genes 15494 ...
#> WNNLS Converged at iteration 160
#> Sub59 has common genes 15532 ...
#> WNNLS Converged at iteration 24
#> Sub60 has common genes 15657 ...
#> WNNLS Converged at iteration 70
#> Sub62 has common genes 15104 ...
#> WNNLS Converged at iteration 51
#> Sub63 has common genes 15160 ...
#> WNNLS Converged at iteration 43
#> Sub64 has common genes 15281 ...
#> WNNLS Converged at iteration 17
#> Sub66 has common genes 15585 ...
#> WNNLS Converged at iteration 122
#> Sub67 has common genes 15380 ...
#> WNNLS Converged at iteration 103
#> Sub68 has common genes 15572 ...
#> WNNLS Converged at iteration 69
#> Sub69 has common genes 15415 ...
#> WNNLS Converged at iteration 29
#> Sub70 has common genes 15544 ...
#> WNNLS Converged at iteration 10
#> Sub71 has common genes 15249 ...
#> WNNLS Converged at iteration 51
#> Sub72 has common genes 15185 ...
#> WNNLS Converged at iteration 47
#> Sub73 has common genes 15319 ...
#> WNNLS Converged at iteration 64
#> Sub74 has common genes 15291 ...
#> WNNLS Converged at iteration 58
#> Sub75 has common genes 15471 ...
#> WNNLS Converged at iteration 75
#> Sub80 has common genes 15410 ...
#> WNNLS Converged at iteration 12
#> Sub81 has common genes 15417 ...
#> WNNLS Converged at iteration 50
#> Sub85 has common genes 15302 ...
#> WNNLS Converged at iteration 33
#> Sub86 has common genes 15186 ...
#> WNNLS Converged at iteration 58
#> Sub88 has common genes 15360 ...
#> WNNLS Converged at iteration 55
#> Sub89 has common genes 15266 ...
#> WNNLS Converged at iteration 47
#> Creating Basis Matrix adjusted for maximal variance weight
#> Used 18249 common genes...
#> Used 6 cell types in deconvolution...
#> Sub1 has common genes 16850 ...
#> WNNLS Converged at iteration 128
#> Sub3 has common genes 16956 ...
#> WNNLS Converged at iteration 352
#> Sub6 has common genes 16563 ...
#> WNNLS Converged at iteration 244
#> Sub8 has common genes 17003 ...
#> WNNLS Converged at iteration 130
#> Sub13 has common genes 17037 ...
#> WNNLS Converged at iteration 217
#> Sub14 has common genes 16703 ...
#> WNNLS Converged at iteration 135
#> Sub15 has common genes 16690 ...
#> WNNLS Converged at iteration 76
#> Sub16 has common genes 17129 ...
#> WNNLS Converged at iteration 230
#> Sub18 has common genes 17300 ...
#> WNNLS Converged at iteration 192
#> Sub19 has common genes 17016 ...
#> WNNLS Converged at iteration 292
#> Sub21 has common genes 16787 ...
#> WNNLS Converged at iteration 228
#> Sub23 has common genes 17074 ...
#> WNNLS Converged at iteration 212
#> Sub24 has common genes 17188 ...
#> WNNLS Converged at iteration 268
#> Sub26 has common genes 16369 ...
#> WNNLS Converged at iteration 160
#> Sub28 has common genes 16795 ...
#> WNNLS Converged at iteration 60
#> Sub30 has common genes 16528 ...
#> WNNLS Converged at iteration 78
#> Sub31 has common genes 16359 ...
#> WNNLS Converged at iteration 238
#> Sub33 has common genes 17087 ...
#> WNNLS Converged at iteration 326
#> Sub34 has common genes 17123 ...
#> WNNLS Converged at iteration 272
#> Sub36 has common genes 16864 ...
#> WNNLS Converged at iteration 199
#> Sub37 has common genes 16799 ...
#> WNNLS Converged at iteration 90
#> Sub39 has common genes 16884 ...
#> WNNLS Converged at iteration 234
#> Sub40 has common genes 16767 ...
#> WNNLS Converged at iteration 214
#> Sub44 has common genes 17311 ...
#> WNNLS Converged at iteration 184
#> Sub45 has common genes 17212 ...
#> WNNLS Converged at iteration 268
#> Sub47 has common genes 16935 ...
#> WNNLS Converged at iteration 296
#> Sub50 has common genes 16645 ...
#> WNNLS Converged at iteration 220
#> Sub52 has common genes 17028 ...
#> WNNLS Converged at iteration 336
#> Sub57 has common genes 16920 ...
#> WNNLS Converged at iteration 258
#> Sub58 has common genes 16970 ...
#> WNNLS Converged at iteration 178
#> Sub59 has common genes 16999 ...
#> WNNLS Converged at iteration 364
#> Sub60 has common genes 17263 ...
#> WNNLS Converged at iteration 184
#> Sub62 has common genes 16369 ...
#> WNNLS Converged at iteration 42
#> Sub63 has common genes 16559 ...
#> WNNLS Converged at iteration 180
#> Sub64 has common genes 16740 ...
#> WNNLS Converged at iteration 226
#> Sub66 has common genes 17111 ...
#> WNNLS Converged at iteration 146
#> Sub67 has common genes 16759 ...
#> WNNLS Converged at iteration 338
#> Sub68 has common genes 17094 ...
#> WNNLS Converged at iteration 260
#> Sub69 has common genes 16897 ...
#> WNNLS Converged at iteration 264
#> Sub70 has common genes 17092 ...
#> WNNLS Converged at iteration 216
#> Sub71 has common genes 16684 ...
#> WNNLS Converged at iteration 26
#> Sub72 has common genes 16559 ...
#> WNNLS Converged at iteration 214
#> Sub73 has common genes 16784 ...
#> WNNLS Converged at iteration 54
#> Sub74 has common genes 16709 ...
#> WNNLS Converged at iteration 180
#> Sub75 has common genes 17048 ...
#> WNNLS Converged at iteration 148
#> Sub80 has common genes 16905 ...
#> WNNLS Converged at iteration 135
#> Sub81 has common genes 16942 ...
#> WNNLS Converged at iteration 196
#> Sub85 has common genes 16712 ...
#> WNNLS Converged at iteration 142
#> Sub86 has common genes 16537 ...
#> WNNLS Converged at iteration 160
#> Sub88 has common genes 16844 ...
#> WNNLS Converged at iteration 240
#> Sub89 has common genes 16677 ...
#> WNNLS Converged at iteration 200
#> Searching ENSEMBLE weight by Sum of Squared Errors or Sum of Abs Errors ......
#> Searching ENSEMBLE weight by LAD -- Minimizing mAD of Y measurement
#> Error in switch(method, BR = lad.fit.BR(x, y, tol), EM = lad.fit.EM(x, : EXPR deve ser um vetor de comprimento 1

fadista.t2d.ens <- SCDC_ENSEMBLE(bulk.eset = fadista_77[,fadista_77$hba1c_class2 == "T2D"], sc.eset.list = list(baronh = qc.baron$sc.eset.qc, segerh = qc.seger$sc.eset.qc), ct.varname = "cluster",
                               sample = "sample", truep = NULL, ct.sub =  c("alpha","beta","delta","gamma","acinar","ductal"), search.length = 0.01, grid.search = T)
#> Creating Basis Matrix adjusted for maximal variance weight
#> Used 16150 common genes...
#> Used 6 cell types in deconvolution...
#> Sub11 has common genes 15485 ...
#> WNNLS Converged at iteration 166
#> Sub17 has common genes 15429 ...
#> WNNLS Converged at iteration 139
#> Sub25 has common genes 15498 ...
#> WNNLS Converged at iteration 24
#> Sub27 has common genes 15544 ...
#> WNNLS Converged at iteration 58
#> Sub29 has common genes 15498 ...
#> WNNLS Converged at iteration 52
#> Sub32 has common genes 15497 ...
#> WNNLS Converged at iteration 22
#> Sub35 has common genes 15717 ...
#> WNNLS Converged at iteration 108
#> Sub38 has common genes 15460 ...
#> WNNLS Converged at iteration 78
#> Sub42 has common genes 15502 ...
#> WNNLS Converged at iteration 62
#> Sub43 has common genes 15513 ...
#> WNNLS Converged at iteration 70
#> Sub46 has common genes 15421 ...
#> WNNLS Converged at iteration 124
#> Sub48 has common genes 15584 ...
#> WNNLS Converged at iteration 38
#> Sub51 has common genes 15689 ...
#> WNNLS Converged at iteration 12
#> Sub53 has common genes 15598 ...
#> WNNLS Converged at iteration 24
#> Sub54 has common genes 15610 ...
#> WNNLS Converged at iteration 38
#> Sub55 has common genes 15609 ...
#> WNNLS Converged at iteration 89
#> Sub56 has common genes 15436 ...
#> WNNLS Converged at iteration 16
#> Sub61 has common genes 15584 ...
#> WNNLS Converged at iteration 160
#> Sub65 has common genes 15650 ...
#> WNNLS Converged at iteration 23
#> Sub76 has common genes 15651 ...
#> WNNLS Converged at iteration 59
#> Sub77 has common genes 15573 ...
#> WNNLS Converged at iteration 28
#> Sub78 has common genes 15705 ...
#> WNNLS Converged at iteration 43
#> Sub82 has common genes 15541 ...
#> WNNLS Converged at iteration 120
#> Sub83 has common genes 15178 ...
#> WNNLS Converged at iteration 21
#> Sub84 has common genes 15482 ...
#> WNNLS Converged at iteration 123
#> Sub87 has common genes 15486 ...
#> WNNLS Converged at iteration 65
#> Creating Basis Matrix adjusted for maximal variance weight
#> Used 18248 common genes...
#> Used 6 cell types in deconvolution...
#> Sub11 has common genes 16894 ...
#> WNNLS Converged at iteration 201
#> Sub17 has common genes 16822 ...
#> WNNLS Converged at iteration 218
#> Sub25 has common genes 17025 ...
#> WNNLS Converged at iteration 194
#> Sub27 has common genes 17028 ...
#> WNNLS Converged at iteration 278
#> Sub29 has common genes 16997 ...
#> WNNLS Converged at iteration 238
#> Sub32 has common genes 16894 ...
#> WNNLS Converged at iteration 158
#> Sub35 has common genes 17355 ...
#> WNNLS Converged at iteration 336
#> Sub38 has common genes 16902 ...
#> WNNLS Converged at iteration 166
#> Sub42 has common genes 16924 ...
#> WNNLS Converged at iteration 162
#> Sub43 has common genes 17056 ...
#> WNNLS Converged at iteration 78
#> Sub46 has common genes 16892 ...
#> WNNLS Converged at iteration 226
#> Sub48 has common genes 17060 ...
#> WNNLS Converged at iteration 264
#> Sub51 has common genes 17348 ...
#> WNNLS Converged at iteration 296
#> Sub53 has common genes 17170 ...
#> WNNLS Converged at iteration 261
#> Sub54 has common genes 17120 ...
#> WNNLS Converged at iteration 348
#> Sub55 has common genes 17075 ...
#> WNNLS Converged at iteration 380
#> Sub56 has common genes 16939 ...
#> WNNLS Converged at iteration 242
#> Sub61 has common genes 17115 ...
#> WNNLS Converged at iteration 220
#> Sub65 has common genes 17157 ...
#> WNNLS Converged at iteration 270
#> Sub76 has common genes 17251 ...
#> WNNLS Converged at iteration 244
#> Sub77 has common genes 17128 ...
#> WNNLS Converged at iteration 260
#> Sub78 has common genes 17336 ...
#> WNNLS Converged at iteration 258
#> Sub82 has common genes 17018 ...
#> WNNLS Converged at iteration 315
#> Sub83 has common genes 16489 ...
#> WNNLS Converged at iteration 216
#> Sub84 has common genes 16981 ...
#> WNNLS Converged at iteration 228
#> Sub87 has common genes 16969 ...
#> WNNLS Converged at iteration 122
#> Searching ENSEMBLE weight by Sum of Squared Errors or Sum of Abs Errors ......
#> Searching ENSEMBLE weight by LAD -- Minimizing mAD of Y measurement
#> Error in switch(method, BR = lad.fit.BR(x, y, tol), EM = lad.fit.EM(x, : EXPR deve ser um vetor de comprimento 1

^{Created on 2023-06-01 with reprex v2.0.2}

─ Session info ───────────────────────────────────────────────────────────────────────────────────────────────────────────── setting value version R version 4.2.3 (2023-03-15) os Linux Mint 21.1 system x86_64, linux-gnu ui RStudio language pt_BR:pt:en collate pt_BR.UTF-8 ctype pt_BR.UTF-8 tz America/Recife date 2023-06-01 rstudio 2022.07.0+548 Spotted Wakerobin (desktop) pandoc 2.19.2 @ /home/iaradsouza/miniconda3/envs/r-423/bin/ (via rmarkdown)

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[1] /media/iaradsouza/DATA1/Github/mdd-deconvolution/renv/library/R-4.2/x86_64-conda-linux-gnu [2] /home/iaradsouza/.cache/R/renv/sandbox/R-4.2/x86_64-conda-linux-gnu/3ff409aa

P ── Loaded and on-disk path mismatch.

[fruce-ki]

I am also having this error, simply trying to run the examples in the vignette.

R version 4.3.1 (2023-06-16 ucrt) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows 10 x64 (build 19045)

Matrix products: default

locale: [1] LC_COLLATE=English_United States.utf8 [2] LC_CTYPE=English_United States.utf8
[3] LC_MONETARY=English_United States.utf8 [4] LC_NUMERIC=C
[5] LC_TIME=English_United States.utf8

time zone: Europe/Vienna tzcode source: internal

attached base packages: [1] stats graphics grDevices utils datasets [6] methods base

other attached packages: [1] SCDC_0.0.0.9000

loaded via a namespace (and not attached): [1] KEGGREST_1.40.0 gtable_0.3.3
[3] ggplot2_3.4.2 Biobase_2.60.0
[5] vctrs_0.6.3 tools_4.3.1
[7] bitops_1.0-7 generics_0.1.3
[9] stats4_4.3.1 tibble_3.2.1
[11] fansi_1.0.4 AnnotationDbi_1.62.2
[13] RSQLite_2.3.1 blob_1.2.4
[15] pkgconfig_2.0.3 pheatmap_1.0.12
[17] checkmate_2.2.0 RColorBrewer_1.1-3
[19] nnls_1.4 S4Vectors_0.38.1
[21] assertthat_0.2.1 lifecycle_1.0.3
[23] GenomeInfoDbData_1.2.10 farver_2.1.1
[25] compiler_4.3.1 stringr_1.5.0
[27] pkgmaker_0.32.8 Biostrings_2.68.1
[29] munsell_0.5.0 codetools_0.2-19
[31] GenomeInfoDb_1.36.1 RCurl_1.98-1.12
[33] pillar_1.9.0 crayon_1.5.2
[35] cachem_1.0.8 tidyselect_1.2.0
[37] digest_0.6.32 stringi_1.7.12
[39] dplyr_1.1.2 reshape2_1.4.4
[41] labeling_0.4.2 cowplot_1.1.1
[43] fastmap_1.1.1 grid_4.3.1
[45] colorspace_2.1-0 cli_3.6.1
[47] magrittr_2.0.3 utf8_1.2.3
[49] withr_2.5.0 backports_1.4.1
[51] scales_1.2.1 L1pack_0.41-24
[53] fastmatrix_0.5 bit64_4.0.5
[55] registry_0.5-1 XVector_0.40.0
[57] httr_1.4.6 bit_4.0.5
[59] png_0.1-8 memoise_2.0.1
[61] IRanges_2.34.1 rlang_1.1.1
[63] Rcpp_1.0.10 xtable_1.8-4
[65] glue_1.6.2 DBI_1.1.3
[67] BiocManager_1.30.21 BiocGenerics_0.46.0
[69] xbioc_0.1.19 rstudioapi_0.14
[71] plyr_1.8.8 R6_2.5.1
[73] zlibbioc_1.46.0

[lsalman34]

I am also experiencing the same error. Has anyone figured out a way around this error or a way to fix it?

[yaqiongliu]

Did anyone fix this problem? Thanks

[yaqiongliu]

w_lad <-NA dt <- data.frame(y = yv, y.list) fitlad <- L1pack::lad(y~.-1, data = dt, ) w_lad <- fitlad$coefficients w_lad[w_lad <0] <- 0 w_lad <- w_lad/sum(w_lad) Error in switch(method, BR = lad.fit.BR(x, y, tol), EM = lad.fit.EM(x, : EXPR must be a vector of length 1, the error is caused by the method = c("BR", "EM")

[nehmea]

same thing here

[LinupJ]

Hello everyone, I am having the same issue. Did anyone solve this problem? Many thanks! 🙏