Dear bioconductor support,

I am trying use barcodeplot to visualize gene set enrichment using limma's function barcode plot. I am feeding the function a vector of the t-statistics from the fit2 object with the column indicating the contrast of interest, and the index is a vector of the indices that correspond to the genes in the set.

 tstats <- fit2$t[,1]
 index <- c(7,22,38,49,205,...)

The following is my barcode plot call

barcodeplot(tstats,index,worm=TRUE)

I then get the following error:

Error in (function (classes, fdef, mtable)  : 
  unable to find an inherited method for function ‘filter’ for signature ‘"numeric", "numeric"’​

I believe this error is arising in the tricubeMovingAverage function because if I call barcode plot with worm=FALSE, I do not get this error. Is this a bug in the function or could there be a something incorrect about of my input?

Thank you.

R version 3.1.3 (2015-03-09)
Platform: x86_64-apple-darwin10.8.0 (64-bit)
Running under: OS X 10.8.5 (Mountain Lion)

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] compiler  grid      stats4    parallel  stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] BiocInstaller_1.16.5      ggbiplot_0.55             scales_0.2.4              plyr_1.8.2                seqLogo_1.32.1            motifStack_1.10.2        
 [7] ade4_1.7-2                MotIV_1.22.0              grImport_0.9-0            MotifDb_1.8.0             Biostrings_2.34.1         XVector_0.6.0            
[13] Gviz_1.10.11              DEXSeq_1.12.2             BiocParallel_1.0.3        DESeq2_1.6.3              RcppArmadillo_0.5.100.1.0 Rcpp_0.11.6              
[19] pheatmap_1.0.2            Heatplus_2.12.0           CellMix_1.6.2             stringr_1.0.0             csSAM_1.2.4               NMF_0.20.5               
[25] rngtools_1.2.4            pkgmaker_0.22             registry_0.2              sva_3.12.0                genefilter_1.48.1         mgcv_1.8-6               
[31] proto_0.3-10              statmod_1.4.21            RSvgDevice_0.6.4.4        doMC_1.3.3                iterators_1.0.7           foreach_1.4.2            
[37] caret_6.0-47              TPAM_1.0                  Matrix_1.2-0              MASS_7.3-40               pamr_1.55                 survival_2.38-1          
[43] cluster_2.0.1             gtable_0.1.2              ggdendro_0.1-15           reshape_0.8.5             venneuler_1.1-0           rJava_0.9-6              
[49] RColorBrewer_1.1-2        gridBase_0.4-7            VennDiagram_1.6.9         GenomicFeatures_1.18.7    GenomicRanges_1.18.4      org.Hs.eg.db_3.0.0       
[55] RSQLite_1.0.0             DBI_0.3.1                 GSEABase_1.28.0           graph_1.44.1              GSVA_1.14.1               matrixStats_0.14.0       
[61] gplots_2.17.0             nlme_3.1-120              ggplot2_1.0.1             R2HTML_2.3.1              annotate_1.44.0           XML_3.98-1.1             
[67] AnnotationDbi_1.28.2      GenomeInfoDb_1.2.5        IRanges_2.0.1             S4Vectors_0.4.0           biomaRt_2.22.0            edgeR_3.8.6              
[73] limma_3.22.7              DESeq_1.18.0              lattice_0.20-31           locfit_1.5-9.1            Biobase_2.26.0            BiocGenerics_0.12.1      

loaded via a namespace (and not attached):
 [1] acepack_1.3-3.3          base64enc_0.1-2          BatchJobs_1.6            BBmisc_1.9               beeswarm_0.2.0           bibtex_0.4.0            
 [7] biovizBase_1.14.1        bitops_1.0-6             BradleyTerry2_1.0-6      brew_1.0-6               brglm_0.5-9              BSgenome_1.34.1         
[13] car_2.0-25               caTools_1.17.1           checkmate_1.5.3          codetools_0.2-11         colorspace_1.2-6         corpcor_1.6.7           
[19] dichromat_2.0-0          digest_0.6.8             doParallel_1.0.8         fail_1.2                 foreign_0.8-63           Formula_1.2-1           
[25] gdata_2.16.1             geneplotter_1.44.0       GenomicAlignments_1.2.2  gridExtra_0.9.1          gtools_3.4.2             Hmisc_3.16-0            
[31] hwriter_1.3.2            KernSmooth_2.23-14       latticeExtra_0.6-26      limSolve_1.5.5.1         lme4_1.1-7               lpSolve_5.6.11          
[37] magrittr_1.5             minqa_1.2.4              munsell_0.4.2            nloptr_1.0.4             nnet_7.3-9               pbkrtest_0.4-2          
[43] preprocessCore_1.28.0    quadprog_1.5-5           quantreg_5.11            RCurl_1.95-4.6           reshape2_1.4.1           rGADEM_2.14.0           
[49] rpart_4.1-9              Rsamtools_1.18.3         rtracklayer_1.26.3       sendmailR_1.2-1          SparseM_1.6              splines_3.1.3           
[55] stringi_0.4-1            tools_3.1.3              VariantAnnotation_1.12.9 xtable_1.7-4             zlibbioc_1.12.0 

Your input looks ok and, according to my testing, this code runs fine in both the current release of limma and in the older version of limma that you are using.

From the error message, my guess is that one of other R packages you have loaded has decided to redefine the filter() function and has done so in such as way that the original filter() function defined in the core stats package no longer works. To confirm this, try loading limma by itself, without all the other packages you have loaded, and try running the code again. 

You should of course upgrade to the current release of Bioconductor, although this might not solve the problem.