EBcoexpress missing value where TRUE/FALSE needed
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Ed Siefker ▴ 230
@ed-siefker-5136
Last seen 5 months ago
United States

I have a normalized count table output from DESeq.  I ran it through varFilter(), extracted the exprs(), and converted it to a matrix with numeric values. 

> head(count.matrix)
        S154 BE36 BA44 BI50 BE88 BE8
Sox17     27   39   56   34   57  33
Mrpl15   271  450  565  297  540 572
Lypla1   139  295  240  225  364 282
Tcea1    211  396  376  273  460 451
Atp6v1h   52  196  173  146  150 186
Rb1cc1   100  189  160  130  166 184
> class(count.matrix[[1,1]])
[1] "numeric"
> class(count.matrix)
[1] "matrix"

I created a conditions array, the same length as the number of samples.

> cond
S154 BE36 BA44 BI50 BE88  BE8
   1    1    1    2    2    2
> class(cond)
[1] "array"
> length(cond)
[1] 6

According to the EBcoexpress, I should be able to create a D matrix with:

> D <- makeMyD(count.matrix, cond, useBWMC=TRUE)
Error in if (sum(D[, j] == Inf) > 0) stop(paste("Infinite BWMC values detected in condition ",  :
  missing value where TRUE/FALSE needed

I don't understand this error or how to troubleshoot further.  Any ideas?
software error • 772 views
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> sessionInfo()
R version 3.4.2 (2017-09-28)
Platform: amd64-portbld-freebsd10.3 (64-bit)
Running under: FreeBSD bio 10.3-STABLE FreeBSD 10.3-STABLE #0 r295946=5327704(9.10-STABLE): Wed Aug  3 12:13:26 PDT 2016     root@build.ixsystems.com:/tank/home/nightlies/build-freenas9/_BE/objs/tank/home/nightlies/build-freenas9/_BE/os/sys/FreeNAS.amd64  amd64

Matrix products: default
LAPACK: /usr/local/lib/R/lib/libRlapack.so

locale:
[1] C

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

other attached packages:
[1] EBcoexpress_1.20.0    minqa_1.2.4           mclust_5.3
[4] EBarrays_2.40.0       lattice_0.20-35       Biobase_2.36.2
[7] BiocGenerics_0.22.1   DGCA_1.0.1            WGCNA_1.61
[10] fastcluster_1.1.24    dynamicTreeCut_1.63-1

loaded via a namespace (and not attached):
[1] bit64_0.9-7           splines_3.4.2         foreach_1.4.3
[4] Formula_1.2-2         stats4_3.4.2          latticeExtra_0.6-28
[7] blob_1.1.0            fit.models_0.5-14     robustbase_0.92-7
[10] impute_1.50.1         RSQLite_2.0           backports_1.1.1
[13] digest_0.6.12         RColorBrewer_1.1-2    checkmate_1.8.4
[16] colorspace_1.3-2      htmltools_0.3.6       preprocessCore_1.38.1
[19] Matrix_1.2-11         plyr_1.8.4            pcaPP_1.9-72
[22] XML_3.98-1.9          pkgconfig_2.0.1       genefilter_1.58.1
[25] xtable_1.8-2          GO.db_3.4.1           mvtnorm_1.0-6
[28] scales_0.5.0          htmlTable_1.9         tibble_1.3.4
[31] annotate_1.54.0       IRanges_2.10.5        ggplot2_2.2.1
[34] nnet_7.3-12           lazyeval_0.2.0        survival_2.41-3
[37] magrittr_1.5          memoise_1.1.0         doParallel_1.0.11
[40] MASS_7.3-47           foreign_0.8-69        tools_3.4.2
[43] data.table_1.10.4-2   matrixStats_0.52.2    stringr_1.2.0
[46] S4Vectors_0.14.7      munsell_0.4.3         cluster_2.0.6
[49] AnnotationDbi_1.38.2  compiler_3.4.2        DESeq_1.28.0
[52] rlang_0.1.2           grid_3.4.2            RCurl_1.95-4.8
[55] iterators_1.0.8       htmlwidgets_0.9       robust_0.4-18
[58] bitops_1.0-6          base64enc_0.1-3       gtable_0.2.0
[61] codetools_0.2-15      DBI_0.7               rrcov_1.4-3
[64] gridExtra_2.3         knitr_1.17            bit_1.1-12
[67] Hmisc_4.0-3           stringi_1.1.5         Rcpp_0.12.13
[70] geneplotter_1.54.0    rpart_4.1-11          acepack_1.4.1
[73] DEoptimR_1.0-8
>

 

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