Hello,
I was attempting to run SPIA through the graphite package and ran into
an odd error when running prepareSPIA on the human Reactome pathways.
You can reproduce the error simply and quickly by:
> library(graphite)
> prepareSPIA(pathways("hsapiens", "reactome")["Insulin receptor
signalling cascade"], "test", TRUE)
Insulin receptor signalling cascade
Error in Filter(Negate(is.null), lapply(db, function(p) { :
error in evaluating the argument 'x' in selecting a method for
function 'Filter': Error in if (e[1] <= e[2]) paste(e[1], e[2], sep =
"|") else paste(e[2], :
missing value where TRUE/FALSE needed
The traceback is not particularly informative. I don't actually see the
line of code from the error message in the traceback:
> traceback()
4: Filter(Negate(is.null), lapply(db, function(p) {
if (print.names)
cat(p@title, "\n")
p <- convertIdentifiers(p, "entrez")
es <- edges(p)
if (NROW(es) == 0 || NROW(unique(es[, 1:2])) < 5)
return(NULL)
ns <- nodes(p)
es <- merge(es, spiaConv, all.x = TRUE)[c("src", "dest",
"direction", "spiaType")]
l <- sapply(spiaAttributes, simplify = FALSE, USE.NAMES = TRUE,
function(edgeType) {
est <- es[es[, 4] == edgeType, , drop = FALSE]
gnl <- buildGraphNEL(ns, est, TRUE)
t(as(gnl, "matrix"))
})
l$title <- p@title
l$nodes <- ns
l$NumberOfReactions <- 0
return(l)
}))
3: .prepareSPIA(db@entries, pathwaySetName, print.names)
2: prepareSPIA(pathways("hsapiens", "reactome")["Insulin receptor
signalling cascade"],
"test", TRUE)
1: prepareSPIA(pathways("hsapiens", "reactome")["Insulin receptor
signalling cascade"],
"test", TRUE)
I guess for now I will remove the offending pathway, but it seems
unexpected that graphite cannot handle a pathway included in its own
package.
-Ryan Thompson
> sessionInfo()
R version 3.2.0 (2015-04-16)
Platform: x86_64-unknown-linux-gnu (64-bit)
Running under: Ubuntu 14.04.2 LTS
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] grDevices datasets parallel graphics stats4 stats utils
[8] methods base
other attached packages:
[1] org.Hs.eg.db_3.1.2 GSEABase_1.30.2
[3] graph_1.46.0 annotate_1.46.0
[5] XML_3.98-1.2 graphite_1.14.0
[7] openxlsx_2.5.10 DESeq2_1.8.1
[9] RcppArmadillo_0.5.200.1.0 Rcpp_0.11.6
[11] edgeR_3.10.2 limma_3.24.10
[13] magrittr_1.5 dplyr_0.4.1
[15] biomaRt_2.24.0 functional_0.6
[17] sqldf_0.4-10 RSQLite_1.0.0
[19] DBI_0.3.1 gsubfn_0.6-6
[21] proto_0.3-10 GenomicFeatures_1.20.1
[23] AnnotationDbi_1.30.1 chipseq_1.18.0
[25] BSgenome_1.36.0 inline_0.3.14
[27] affy_1.46.1 rtracklayer_1.28.4
[29] Biobase_2.28.0 ShortRead_1.26.0
[31] GenomicAlignments_1.4.1 BiocParallel_1.3.16
[33] Rsamtools_1.20.4 Biostrings_2.36.1
[35] XVector_0.8.0 GenomicRanges_1.20.5
[37] GenomeInfoDb_1.4.0 doParallel_1.0.8
[39] iterators_1.0.7 foreach_1.4.2
[41] plyr_1.8.3 stringr_1.0.0
[43] IRanges_2.2.4 ggplot2_1.0.1
[45] S4Vectors_0.6.0 BiocGenerics_0.14.0
[47] BiocInstaller_1.18.3
loaded via a namespace (and not attached):
[1] splines_3.2.0 assertthat_0.1 Formula_1.2-1
[4] latticeExtra_0.6-26 lattice_0.20-31 chron_2.3-45
[7] digest_0.6.8 RColorBrewer_1.1-2 colorspace_1.2-6
[10] preprocessCore_1.30.0 genefilter_1.50.0 zlibbioc_1.14.0
[13] xtable_1.7-4 scales_0.2.5 affyio_1.36.0
[16] lazyeval_0.1.10 nnet_7.3-9 survival_2.38-2
[19] MASS_7.3-40 hwriter_1.3.2 foreign_0.8-63
[22] tools_3.2.0 munsell_0.4.2 locfit_1.5-9.1
[25] cluster_2.0.1 lambda.r_1.1.7 compiler_3.2.0
[28] futile.logger_1.4.1 grid_3.2.0 RCurl_1.96-0
[31] bitops_1.0-6 gtable_0.1.2 codetools_0.2-11
[34] reshape2_1.4.1 gridExtra_0.9.1 Hmisc_3.16-0
[37] futile.options_1.0.0 stringi_0.4-1 geneplotter_1.46.0
[40] rpart_4.1-9 acepack_1.3-3.3
>
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