Error when generating the SVA-object using package SVA in R

Question

I am trying to apply the surrogate variable analysis (sva) package to my data, but I haven't been able to even pass beyond the model construction. I'm running into an error I can't seem to fix.

My code follows the vignette (though with my own data):

pheno <- pheno.groups
edata <- counts_all.norm.log #a normalized counts table, with log2(count+1) applied
mod <- model.matrix(~group, data=pheno.groups)
mod0 <- model.matrix(~1,data=pheno)
n.sv <- 1
svobj <- sva(edata,mod=mod,mod0=mod0,n.sv=n.sv)

The latter gives an error:

Error in density.default(x, adjust = adj) : 'x' contains missing values

The traceback is as follows:

7. stop("'x' contains missing values")
6. density.default(x, adjust = adj)
5. density(x, adjust = adj)
4. density(x, adjust = adj)
3. edge.lfdr(ptmp)
2. irwsva.build(dat = dat, mod = mod, mod0 = mod0, n.sv = n.sv, B = B)
1. sva(edata, mod = mod, mod0 = mod0, n.sv = n.sv)

Here's my session info:

Session info -------------------------------------------------------------------------------------------------------------------------------------------
 setting  value                       
 version  R version 3.3.1 (2016-06-21)
 system   x86_64, darwin13.4.0        
 ui       RStudio (1.0.136)           
 language (EN)                        
 collate  en_US.UTF-8                 
 tz       America/Indiana/Indianapolis
 date     2017-03-29                  

Packages -----------------------------------------------------------------------------------------------------------------------------------------------
 package              * version  date       source        
 acepack                1.4.1    2016-10-29 CRAN (R 3.3.0)
 annotate               1.50.1   2016-10-09 Bioconductor  
 AnnotationDbi          1.34.4   2016-07-08 Bioconductor  
 assertthat             0.1      2013-12-06 CRAN (R 3.3.0)
 backports              1.0.5    2017-01-18 CRAN (R 3.3.2)
 base64enc              0.1-3    2015-07-28 CRAN (R 3.3.0)
 Biobase              * 2.32.0   2016-05-04 Bioconductor  
 BiocGenerics         * 0.18.0   2016-05-04 Bioconductor  
 BiocInstaller        * 1.22.3   2016-06-26 Bioconductor  
 BiocParallel           1.6.6    2016-08-15 Bioconductor  
 bitops                 1.0-6    2013-08-17 CRAN (R 3.3.0)
 bladderbatch         * 1.10.0   2017-03-29 Bioconductor  
 checkmate              1.8.2    2016-11-02 CRAN (R 3.3.0)
 cluster              * 2.0.6    2017-03-16 CRAN (R 3.3.2)
 colorspace             1.3-2    2016-12-14 CRAN (R 3.3.2)
 data.table             1.10.4   2017-02-01 CRAN (R 3.3.1)
 DBI                    0.6      2017-03-09 CRAN (R 3.3.2)
 DESeq2               * 1.12.4   2016-08-08 Bioconductor  
 devtools               1.12.0   2016-06-24 CRAN (R 3.3.0)
 digest                 0.6.12   2017-01-27 CRAN (R 3.3.2)
 foreign                0.8-67   2016-09-13 CRAN (R 3.3.0)
 Formula                1.2-1    2015-04-07 CRAN (R 3.3.0)
 genefilter           * 1.54.2   2016-05-16 Bioconductor  
 geneplotter            1.50.0   2016-05-04 Bioconductor  
 GenomeInfoDb         * 1.8.7    2016-09-02 Bioconductor  
 GenomicRanges        * 1.24.3   2016-09-11 Bioconductor  
 ggplot2                2.2.1    2016-12-30 CRAN (R 3.3.2)
 gridExtra              2.2.1    2016-02-29 CRAN (R 3.3.0)
 gtable                 0.2.0    2016-02-26 CRAN (R 3.3.0)
 Hmisc                  4.0-2    2016-12-31 CRAN (R 3.3.2)
 htmlTable              1.9      2017-01-26 CRAN (R 3.3.2)
 htmltools              0.3.5    2016-03-21 CRAN (R 3.3.0)
 htmlwidgets            0.8      2016-11-09 CRAN (R 3.3.2)
 IRanges              * 2.6.1    2016-06-19 Bioconductor  
 knitr                  1.15.1   2016-11-22 CRAN (R 3.3.2)
 lattice                0.20-35  2017-03-25 CRAN (R 3.3.2)
 latticeExtra           0.6-28   2016-02-09 CRAN (R 3.3.0)
 lazyeval               0.2.0    2016-06-12 CRAN (R 3.3.0)
 limma                * 3.28.21  2016-09-05 Bioconductor  
 locfit                 1.5-9.1  2013-04-20 CRAN (R 3.3.0)
 magrittr               1.5      2014-11-22 CRAN (R 3.3.0)
 Matrix                 1.2-8    2017-01-20 CRAN (R 3.3.2)
 memoise                1.0.0    2016-01-29 CRAN (R 3.3.0)
 mgcv                 * 1.8-17   2017-02-08 CRAN (R 3.3.2)
 munsell                0.4.3    2016-02-13 CRAN (R 3.3.0)
 nlme                 * 3.1-131  2017-02-06 CRAN (R 3.3.2)
 nnet                   7.3-12   2016-02-02 CRAN (R 3.3.1)
 pamr                 * 1.55     2014-08-27 CRAN (R 3.3.0)
 pheatmap             * 1.0.8    2015-12-11 CRAN (R 3.3.0)
 plyr                   1.8.4    2016-06-08 CRAN (R 3.3.0)
 RColorBrewer           1.1-2    2014-12-07 CRAN (R 3.3.0)
 Rcpp                   0.12.10  2017-03-19 CRAN (R 3.3.2)
 RCurl                  1.95-4.8 2016-03-01 CRAN (R 3.3.0)
 rpart                  4.1-10   2015-06-29 CRAN (R 3.3.1)
 RSQLite                1.1-2    2017-01-08 CRAN (R 3.3.2)
 rstudioapi             0.6      2016-06-27 CRAN (R 3.3.0)
 S4Vectors            * 0.10.3   2016-08-16 Bioconductor  
 scales                 0.4.1    2016-11-09 CRAN (R 3.3.2)
 stringi                1.1.3    2017-03-21 CRAN (R 3.3.1)
 stringr                1.2.0    2017-02-18 CRAN (R 3.3.2)
 SummarizedExperiment * 1.2.3    2016-06-10 Bioconductor  
 survival             * 2.41-2   2017-03-16 CRAN (R 3.3.2)
 sva                  * 3.20.0   2016-05-04 Bioconductor  
 tibble                 1.2      2016-08-26 CRAN (R 3.3.0)
 withr                  1.0.2    2016-06-20 CRAN (R 3.3.0)
 XML                    3.98-1.5 2016-11-10 CRAN (R 3.3.2)
 xtable                 1.8-2    2016-02-05 CRAN (R 3.3.0)
 XVector                0.12.1   2016-07-22 Bioconductor  
 zlibbioc               1.18.0   2016-05-04 Bioconductor  

Any help, or even hints on where to go from here, would be greatly appreciated!

Answer 1

I had a similar problem. I found that my factor variables read in as characters (which doesn't matter for some packages but it does for this one). Once I changed all my variables labeled as characters to factors the function worked.

Answer 2

I have meanwhile figured out the problem: while my test dataset did not contain NAs or +/- infinite numbers, there were several genes with very low read counts in there. Once these were removed, the package worked!