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xuranw / MuSiC

Multi-subject Single Cell Deconvolution
https://github.com/xuranw/MuSiC
GNU General Public License v3.0
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music_prop 'negative entry appears' error #65

Open jk86754 opened 3 years ago

jk86754 commented 3 years ago

Hi,

I am trying to run the code below and get an error. Help would be appreciated.

Code: library(BisqueRNA) library(xbioc) library(MuSiC) library(Biobase)

gse132771_all_eset <- SeuratToExpressionSet(ipf_allcombined, delimiter = "", position = 1, version = 'v3') gse47460_gse132771_music <- music_prop(bulk.eset = gse47460_eset, sc.eset = gse132771_all_eset, clusters = 'cellType', samples = 'SubjectName', verbose = T)

error:

gse47460_gse132771_music <- music_prop(bulk.eset = gse47460_eset, sc.eset = gse132771_all_eset, clusters = 'cellType', samples = 'SubjectName', verbose = T) Creating Relative Abudance Matrix... Creating Variance Matrix... Creating Library Size Matrix... Used 12154 common genes... Error in relative.ab(exprs(bulk.eset)[m.bulk, ]) : Negative entry appears!

sessionInfo() R version 3.6.0 (2019-04-26) Platform: x86_64-redhat-linux-gnu (64-bit) Running under: CentOS Linux 7 (Core)

Matrix products: default BLAS/LAPACK: /usr/lib64/R/lib/libRblas.so

Random number generation: RNG: Mersenne-Twister Normal: Inversion Sample: Rounding

locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C

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

other attached packages: [1] destiny_2.14.0 biomaRt_2.40.5 limma_3.40.6 BisqueRNA_1.0.4 Seurat_3.1.1 xbioc_0.1.19 AnnotationDbi_1.46.1 IRanges_2.18.3
[9] S4Vectors_0.22.1 Biobase_2.44.0 BiocGenerics_0.32.0 MuSiC_0.1.1 ggplot2_3.3.3 nnls_1.4

loaded via a namespace (and not attached): [1] rappdirs_0.3.1 SparseM_1.78 ggthemes_4.2.4 R.methodsS3_1.8.1 coda_0.19-4 pkgmaker_0.32.2
[7] tidyr_1.1.2 bit64_4.0.5 irlba_2.3.3 multcomp_1.4-11 DelayedArray_0.10.0 R.utils_2.10.1
[13] data.table_1.12.8 RCurl_1.98-1.2 generics_0.1.0 metap_1.4 cowplot_1.1.1 TH.data_1.0-10
[19] RSQLite_2.2.3 RANN_2.6.1 europepmc_0.4 proxy_0.4-24 future_1.21.0 bit_4.0.4
[25] enrichplot_1.4.0 mutoss_0.1-12 xml2_1.3.2 SummarizedExperiment_1.14.1 assertthat_0.2.1 viridis_0.5.1
[31] hms_1.0.0 DEoptimR_1.0-8 progress_1.2.2 readxl_1.3.1 igraph_1.2.6 DBI_1.1.1
[37] tmvnsim_1.0-2 htmlwidgets_1.5.3 mcmc_0.9-7 purrr_0.3.4 ellipsis_0.3.1 dplyr_1.0.3
[43] backports_1.2.1 MCMCpack_1.5-0 gbRd_0.4-11 vctrs_0.3.6 quantreg_5.83 TTR_0.24.2
[49] ROCR_1.0-11 abind_1.4-5 cachem_1.0.1 RcppEigen_0.3.3.9.1 withr_2.4.1 ggforce_0.3.2
[55] triebeard_0.3.0 robustbase_0.93-7 checkmate_2.0.0 vroom_1.3.2 vcd_1.4-8 sctransform_0.3.2
[61] xts_0.12.1 prettyunits_1.1.1 mnormt_2.0.2 cluster_2.1.0 DOSE_3.10.2 ape_5.4-1
[67] lazyeval_0.2.2 laeken_0.5.1 crayon_1.3.4 pkgconfig_2.0.3 tweenr_1.0.1 GenomeInfoDb_1.20.0
[73] nlme_3.1-141 nnet_7.3-15 rlang_0.4.10 globals_0.14.0 lifecycle_0.2.0 MatrixModels_0.4-1
[79] sandwich_2.5-1 registry_0.5-1 mathjaxr_1.0-1 rsvd_1.0.3 cellranger_1.1.0 polyclip_1.10-0
[85] matrixStats_0.57.0 lmtest_0.9-38 graph_1.62.0 Matrix_1.3-2 urltools_1.7.3 carData_3.0-4
[91] boot_1.3-26 zoo_1.8-8 ggridges_0.5.3 png_0.1-7 viridisLite_0.3.0 bitops_1.0-6
[97] R.oo_1.24.0 KernSmooth_2.23-18 blob_1.2.1 stringr_1.4.0 qvalue_2.16.0 parallelly_1.23.0
[103] gridGraphics_0.5-1 reactome.db_1.68.0 scales_1.1.1 memoise_2.0.0 graphite_1.30.0 magrittr_2.0.1
[109] plyr_1.8.6 ica_1.0-2 zlibbioc_1.30.0 compiler_3.6.0 RColorBrewer_1.1-2 plotrix_3.7-7
[115] fitdistrplus_1.1-3 XVector_0.24.0 listenv_0.8.0 pbapply_1.4-3 MASS_7.3-53 tidyselect_1.1.0
[121] stringi_1.5.3 forcats_0.5.0 GOSemSim_2.10.0 ggrepel_0.9.0 grid_3.6.0 fastmatch_1.1-0
[127] tools_3.6.0 future.apply_1.7.0 rio_0.5.16 rstudioapi_0.13 foreign_0.8-76 gridExtra_2.3
[133] smoother_1.1 scatterplot3d_0.3-41 farver_2.0.3 Rtsne_0.15 ggraph_2.0.4 digest_0.6.27
[139] rvcheck_0.1.8 BiocManager_1.30.10 Rcpp_1.0.6 GenomicRanges_1.36.1 car_3.0-10 SDMTools_1.1-221.2
[145] RcppAnnoy_0.0.18 httr_1.4.2 Rdpack_2.1 colorspace_2.0-0 XML_3.99-0.3 ranger_0.12.1
[151] reticulate_1.18 splines_3.6.0 uwot_0.1.10 sn_1.6-2 conquer_1.0.2 graphlayouts_0.7.1
[157] sp_1.4-5 multtest_2.40.0 ggplotify_0.0.5 plotly_4.9.3 xtable_1.8-4 jsonlite_1.7.2
[163] tidygraph_1.2.0 UpSetR_1.4.0 R6_2.5.0 TFisher_0.2.0 pillar_1.4.7 htmltools_0.5.1.1
[169] glue_1.4.2 fastmap_1.1.0 VIM_6.1.0 DT_0.17 BiocParallel_1.18.1 class_7.3-18
[175] codetools_0.2-18 fgsea_1.10.1 tsne_0.1-3 mvtnorm_1.1-1 lattice_0.20-41 tibble_3.0.5
[181] numDeriv_2016.8-1.1 curl_4.3 leiden_0.3.1 ReactomePA_1.28.0 zip_2.1.1 GO.db_3.8.2
[187] openxlsx_4.2.3 survival_3.2-7 munsell_0.5.0 e1071_1.7-4 DO.db_2.9 GenomeInfoDbData_1.2.1
[193] haven_2.3.1 reshape2_1.4.4 gtable_0.3.0 rbibutils_2.0

jk86754 commented 3 years ago

Quick update: I am using RMA-normalized microarray data for bulk gene expression, NOT RNA-seq.

LacquerHed commented 1 month ago

Did you ever get this figured out? Im having a similar issue. Thanks.