Hi,

I'm using plotSignatures to plot signatures as follows:

I have mutational signatures data in table format, i read the table in R to get object of mode list in the following format 

               T1     T2  T3   T4

C>A ACA     1      0    2    1

C>A ACC     1      2      2      1    

C>A ACG     1     0      0      0     

C>A ACT     5      0      0      0   

C>A CCA     10      0      1      1  

C>A CCC     2      1      1      0    

C>A CCG     2      1      4      0      

C>A CCT     1      1      1      1    

C>A GCA     1      0      1      1 

#=================

I used data.matrix to convert list to matrix as in case if not conversion i got tis error

Error in validObject(.Object) : 
  invalid class “MutationalSignatures” object: invalid object for slot "observed" in class "MutationalSignatures": got class "data.frame", should be or extend class "matrix"

#===========

n_sig=4

Sig = identifySignatures(data.matrix(Data), n_sigs, nmfDecomposition)

plotSignatures(Sig) + ggtitle("Somatic Signatures of Sig: NMF - Barchart")

The output  plot is just pain grid with no signature information

In addition, I got this warning message

Warning message:
In RColorBrewer::brewer.pal(n, pal) :
  n too large, allowed maximum for palette Set3 is 12
Returning the palette you asked for with that many colors

Any idea?

#==========

 sessionInfo()
R version 3.2.1 (2015-06-18)
Platform: x86_64-apple-darwin10.8.0 (64-bit)
Running under: OS X 10.8.5 (Mountain Lion)

locale:
[1] ja_JP.UTF-8/ja_JP.UTF-8/ja_JP.UTF-8/C/ja_JP.UTF-8/ja_JP.UTF-8

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

other attached packages:
 [1] stringr_1.0.0            h5vc_2.2.0               ggplot2_1.0.1           
 [4] gridExtra_2.0.0          SomaticSignatures_2.4.5  Biobase_2.28.0          
 [7] VariantAnnotation_1.14.6 Rsamtools_1.20.4         Biostrings_2.36.1       
[10] XVector_0.8.0            GenomicRanges_1.20.5     GenomeInfoDb_1.4.1      
[13] IRanges_2.2.5            S4Vectors_0.6.2          BiocGenerics_0.14.0     

loaded via a namespace (and not attached):
 [1] splines_3.2.1           foreach_1.4.2           Formula_1.2-1          
 [4] latticeExtra_0.6-26     RBGL_1.44.0             BSgenome_1.36.3        
 [7] RSQLite_1.0.0           lattice_0.20-33         biovizBase_1.16.0      
[10] digest_0.6.8            RColorBrewer_1.1-2      checkmate_1.6.2        
[13] colorspace_1.2-6        ggbio_1.16.1            plyr_1.8.3             
[16] OrganismDbi_1.10.0      XML_3.98-1.3            biomaRt_2.24.0         
[19] zlibbioc_1.14.0         xtable_1.7-4            scales_0.2.5           
[22] brew_1.0-6              BiocParallel_1.2.11     proxy_0.4-15           
[25] pkgmaker_0.22           GenomicFeatures_1.20.1  nnet_7.3-10            
[28] proto_0.3-10            survival_2.38-3         magrittr_1.5           
[31] GGally_0.5.0            fail_1.2                doParallel_1.0.8       
[34] MASS_7.3-43             NMF_0.20.6              foreign_0.8-65         
[37] graph_1.46.0            tools_3.2.1             registry_0.3           
[40] BBmisc_1.9              gridBase_0.4-7          sendmailR_1.2-1        
[43] munsell_0.4.2           cluster_2.0.3           rngtools_1.2.4         
[46] AnnotationDbi_1.30.1    lambda.r_1.1.7          pcaMethods_1.58.0      
[49] rhdf5_2.12.0            futile.logger_1.4.1     RCurl_1.95-4.7         
[52] dichromat_2.0-0         iterators_1.0.7         labeling_0.3           
[55] h5vcData_1.102.0        base64enc_0.1-3         bitops_1.0-6           
[58] gtable_0.1.2            codetools_0.2-14        abind_1.4-3            
[61] DBI_0.3.1               reshape_0.8.5           reshape2_1.4.1         
[64] GenomicAlignments_1.4.1 rtracklayer_1.28.6      Hmisc_3.16-0           
[67] futile.options_1.0.0    stringi_0.5-5           BatchJobs_1.6          
[70] Rcpp_0.12.0             rpart_4.1-10            acepack_1.3-3.3 

#===========

Thank you

Regarding your original questions, your input table representing the motif counts per sample seems correctly formatted. You will need to adjust the representation of the motifs itself, to match the way they are expressed in the SomaticSignatures package internally. If you have a look at the example data of the package, e.g. with data(sca_mm, package = "SomaticSignatures"). The rownames of the matrix represent the somatic motifs, and will need to be reformatted from C>A ACA to CA A.A, C>G ACT to CG A.T, and so on. Please note that all this assumes that your perl script generating the input matrix works properly, which is something I can't comment on. You may further want to consider normalizing the counts by the total number of events observed in each sample, i.e. dividing by the column sums.

For your follow-up questions on how to start with a table of mutation events, please read through the vignette of package which covers this use case in detail.