ezbake error when fnr_maxiter = 0
allonw opened this issue · 0 comments
allonw commented
The following code generates the following error in simple_FNR_params. Slightly different configurations of the parameters (still with fnr_maxiter = 0 and no HK list given) give the error in the else clause of the same if statement ("User must provide at least 2 positive control genes.")
rm(list=ls())
set.seed(101)
mat <- matrix(rpois(1000, lambda = 5), ncol=10)
colnames(mat) <- paste("X", 1:ncol(mat), sep="")
qc = data.frame(NREADS = colSums(mat), RALIGN = 100 * colMeans(mat > 5),
row.names = colnames(mat))
library(scone)
scone_easybake(expr = mat, qc = qc, fnr_maxiter = 0, negcon = NULL, eval_negcon = FALSE)
sessionInfo()
> scone_easybake(expr = mat, qc = qc, fnr_maxiter = 0, negcon = NULL, eval_negcon = FALSE)
Error in simple_FNR_params(expr = nexpr, pos_controls = pos_controls) :
If pos_controls is logical, it should have one element per gene.
>
> sessionInfo()
R version 3.4.0 (2017-04-21)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Sierra 10.12.5
Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRlapack.dylib
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] parallel stats4 stats graphics grDevices utils datasets methods
[9] base
other attached packages:
[1] scone_0.99.7 SummarizedExperiment_1.6.3 DelayedArray_0.2.7
[4] matrixStats_0.52.2 Biobase_2.36.2 GenomicRanges_1.28.3
[7] GenomeInfoDb_1.12.2 IRanges_2.10.2 S4Vectors_0.14.3
[10] BiocGenerics_0.22.0
loaded via a namespace (and not attached):
[1] aroma.light_3.6.0 NMF_0.20.6 plyr_1.8.4
[4] igraph_1.0.1 lazyeval_0.2.0 shinydashboard_0.6.1
[7] splines_3.4.0 BiocParallel_1.10.1 ggplot2_2.2.1
[10] gridBase_0.4-7 scater_1.4.0 digest_0.6.12
[13] foreach_1.4.3 htmltools_0.3.6 viridis_0.4.0
[16] gdata_2.18.0 magrittr_1.5 memoise_1.1.0
[19] cluster_2.0.6 doParallel_1.0.10 mixtools_1.1.0
[22] limma_3.32.2 Biostrings_2.44.1 annotate_1.54.0
[25] bayesm_3.0-2 R.utils_2.5.0 rARPACK_0.11-0
[28] colorspace_1.3-2 dplyr_0.7.0 tximport_1.4.0
[31] RCurl_1.95-4.8 jsonlite_1.5 hexbin_1.27.1
[34] genefilter_1.58.1 survival_2.41-3 zoo_1.8-0
[37] iterators_1.0.8 glue_1.1.0 registry_0.3
[40] gtable_0.2.0 zlibbioc_1.22.0 XVector_0.16.0
[43] compositions_1.40-1 kernlab_0.9-25 prabclus_2.2-6
[46] DEoptimR_1.0-8 scales_0.4.1 DESeq_1.28.0
[49] mvtnorm_1.0-6 DBI_0.6-1 edgeR_3.18.1
[52] rngtools_1.2.4 miniUI_0.1.1 Rcpp_0.12.11
[55] viridisLite_0.2.0 xtable_1.8-2 mclust_5.3
[58] DT_0.2 htmlwidgets_0.8 httr_1.2.1
[61] FNN_1.1 gplots_3.0.1 RColorBrewer_1.1-2
[64] fpc_2.1-10 modeltools_0.2-21 XML_3.98-1.8
[67] R.methodsS3_1.7.1 flexmix_2.3-14 nnet_7.3-12
[70] locfit_1.5-9.1 dynamicTreeCut_1.63-1 rlang_0.1.1
[73] reshape2_1.4.2 AnnotationDbi_1.38.1 munsell_0.4.3
[76] tools_3.4.0 visNetwork_1.0.3 RSQLite_1.1-2
[79] stringr_1.2.0 robustbase_0.92-7 caTools_1.17.1
[82] purrr_0.2.2.2 EDASeq_2.10.0 mime_0.5
[85] scran_1.4.4 R.oo_1.21.0 biomaRt_2.32.1
[88] compiler_3.4.0 beeswarm_0.2.3 plotly_4.7.0
[91] tibble_1.3.3 statmod_1.4.29 geneplotter_1.54.0
[94] stringi_1.1.5 GenomicFeatures_1.28.3 RSpectra_0.12-0
[97] lattice_0.20-35 trimcluster_0.1-2 Matrix_1.2-10
[100] tensorA_0.36 data.table_1.10.4 bitops_1.0-6
[103] httpuv_1.3.3 rtracklayer_1.36.3 R6_2.2.1
[106] latticeExtra_0.6-28 hwriter_1.3.2 ShortRead_1.34.0
[109] KernSmooth_2.23-15 gridExtra_2.2.1 vipor_0.4.5
[112] codetools_0.2-15 boot_1.3-19 energy_1.7-0
[115] MASS_7.3-47 gtools_3.5.0 assertthat_0.2.0
[118] rhdf5_2.20.0 rjson_0.2.15 pkgmaker_0.22
[121] RUVSeq_1.10.0 GenomicAlignments_1.12.1 Rsamtools_1.28.0
[124] GenomeInfoDbData_0.99.0 diptest_0.75-7 grid_3.4.0
[127] tidyr_0.6.3 class_7.3-14 segmented_0.5-2.1
[130] shiny_1.0.3 ggbeeswarm_0.5.3