I met an error when running "locateVariants" function in "VariantAnnotation" package. Before running "locateVariants" function, I need to first libarary "tidyverse", but when I library "tidyverse" package before "VariantAnnotation" and run "locateVariants" function, an error happens ("Error in as.vector(x) : no method for coercing this S4 class to a vector"). But it works when library "VariantAnnotation" and run "locateVariants" function first. Could anyone please explain to me why it happens and how could I do to make it work when library "tidyverse" first? Here is the code that can reproduce the error.

The "rd_test.rds" file can be downloaded here https://drive.google.com/open?id=0BwtKdDxl2iyQaUc5ZW9rM2FPVnc, the "Homo_sapiens.GRCh38.90.sqlite" file can be downloaded here https://drive.google.com/open?id=0BwtKdDxl2iyQQTZJZlVJS2NzWjA

## Start a new R session

rd_test <- readRDS("rd_test.rds")

library(GenomicFeatures)

txdb <- loadDb("Homo_sapiens.GRCh38.90.sqlite")

library(VariantAnnotation)

allvar <- locateVariants(rd_test, txdb, AllVariants())

library(tidyverse)

allvar <- locateVariants(rd_test, txdb, AllVariants())

## "locateVariants" function works when library "VariantAnnotation" and run "locateVariants" function then library "tidyverse"

sessionInfo()

# R version 3.4.1 (2017-06-30)
# Platform: x86_64-pc-linux-gnu (64-bit)
# Running under: Ubuntu 16.04.1 LTS
#
# Matrix products: default
# BLAS: /usr/lib/atlas-base/atlas/libblas.so.3.0
# LAPACK: /usr/lib/atlas-base/atlas/liblapack.so.3.0
#
# locale:
#   [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C               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    LC_PAPER=en_US.UTF-8       LC_NAME=C                 
# [9] LC_ADDRESS=C               LC_TELEPHONE=C             LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
#
# attached base packages:
#   [1] parallel  stats4    stats     graphics  utils     datasets  grDevices methods   base     
#
# other attached packages:
#   [1] dplyr_0.7.2                purrr_0.2.3                readr_1.1.1                tidyr_0.7.0               
# [5] tibble_1.3.4               ggplot2_2.2.1              tidyverse_1.1.1            VariantAnnotation_1.20.3  
# [9] Rsamtools_1.26.2           Biostrings_2.42.1          XVector_0.14.1             SummarizedExperiment_1.4.0
# [13] GenomicFeatures_1.26.4     AnnotationDbi_1.36.2       Biobase_2.34.0             GenomicRanges_1.26.4      
# [17] GenomeInfoDb_1.10.3        IRanges_2.8.2              S4Vectors_0.12.2           BiocGenerics_0.20.0       
# [21] setwidth_1.0-4             colorout_1.1-2            
#
# loaded via a namespace (and not attached):
#   [1] Rcpp_0.12.12             lubridate_1.6.0          lattice_0.20-35          assertthat_0.2.0        
# [5] digest_0.6.12            psych_1.7.5              cellranger_1.1.0         R6_2.2.2                
# [9] plyr_1.8.4               RSQLite_2.0              httr_1.3.1               zlibbioc_1.20.0         
# [13] rlang_0.1.2              readxl_1.0.0             lazyeval_0.2.0           blob_1.1.0              
# [17] Matrix_1.2-11            BiocParallel_1.8.2       stringr_1.2.0            foreign_0.8-69          
# [21] RCurl_1.95-4.8           bit_1.1-12               biomaRt_2.30.0           munsell_0.4.3           
# [25] broom_0.4.2              modelr_0.1.1             compiler_3.4.1           rtracklayer_1.34.2      
# [29] pkgconfig_2.0.1          mnormt_1.5-5             XML_3.98-1.9             GenomicAlignments_1.10.1
# [33] bitops_1.0-6             grid_3.4.1               nlme_3.1-131             jsonlite_1.5            
# [37] gtable_0.2.0             DBI_0.7                  magrittr_1.5             scales_0.4.1            
# [41] stringi_1.1.5            reshape2_1.4.2           bindrcpp_0.2             xml2_1.1.1              
# [45] tools_3.4.1              forcats_0.2.0            bit64_0.9-7              BSgenome_1.42.0         
# [49] glue_1.1.1               hms_0.3                  yaml_2.1.14              colorspace_1.3-2        
# [53] rvest_0.3.2              memoise_1.1.0            bindr_0.1                haven_1.1.0  

## Start a new R session

rd_test <- readRDS("rd_test.rds")

library(GenomicFeatures)

txdb <- loadDb("Homo_sapiens.GRCh38.90.sqlite")

library(tidyverse)

library(VariantAnnotation)

allvar <- locateVariants(rd_test, txdb, AllVariants())
# 'select()' returned 1:1 mapping between keys and columns
# Error in as.vector(x) : no method for coercing this S4 class to a vector

traceback()

sessionInfo()
# R version 3.4.1 (2017-06-30)
# Platform: x86_64-pc-linux-gnu (64-bit)
# Running under: Ubuntu 16.04.1 LTS
#
# Matrix products: default
# BLAS: /usr/lib/atlas-base/atlas/libblas.so.3.0
# LAPACK: /usr/lib/atlas-base/atlas/liblapack.so.3.0
#
# locale:
#   [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C               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    LC_PAPER=en_US.UTF-8       LC_NAME=C                 
# [9] LC_ADDRESS=C               LC_TELEPHONE=C             LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
#
# attached base packages:
#   [1] parallel  stats4    stats     graphics  utils     datasets  grDevices methods   base     
#
# other attached packages:
#   [1] VariantAnnotation_1.20.3   Rsamtools_1.26.2           Biostrings_2.42.1          XVector_0.14.1            
# [5] SummarizedExperiment_1.4.0 dplyr_0.7.2                purrr_0.2.3                readr_1.1.1               
# [9] tidyr_0.7.0                tibble_1.3.4               ggplot2_2.2.1              tidyverse_1.1.1           
# [13] GenomicFeatures_1.26.4     AnnotationDbi_1.36.2       Biobase_2.34.0             GenomicRanges_1.26.4      
# [17] GenomeInfoDb_1.10.3        IRanges_2.8.2              S4Vectors_0.12.2           BiocGenerics_0.20.0       
# [21] setwidth_1.0-4             colorout_1.1-2            
#
# loaded via a namespace (and not attached):
#   [1] Rcpp_0.12.12             lubridate_1.6.0          lattice_0.20-35          assertthat_0.2.0        
# [5] digest_0.6.12            psych_1.7.5              cellranger_1.1.0         R6_2.2.2                
# [9] plyr_1.8.4               RSQLite_2.0              httr_1.3.1               zlibbioc_1.20.0         
# [13] rlang_0.1.2              readxl_1.0.0             lazyeval_0.2.0           blob_1.1.0              
# [17] Matrix_1.2-11            BiocParallel_1.8.2       stringr_1.2.0            foreign_0.8-69          
# [21] RCurl_1.95-4.8           bit_1.1-12               biomaRt_2.30.0           munsell_0.4.3           
# [25] broom_0.4.2              compiler_3.4.1           modelr_0.1.1             rtracklayer_1.34.2      
# [29] pkgconfig_2.0.1          mnormt_1.5-5             XML_3.98-1.9             GenomicAlignments_1.10.1
# [33] bitops_1.0-6             grid_3.4.1               nlme_3.1-131             jsonlite_1.5            
# [37] gtable_0.2.0             DBI_0.7                  magrittr_1.5             scales_0.4.1            
# [41] stringi_1.1.5            reshape2_1.4.2           bindrcpp_0.2             xml2_1.1.1              
# [45] tools_3.4.1              forcats_0.2.0            bit64_0.9-7              BSgenome_1.42.0         
# [49] glue_1.1.1               hms_0.3                  yaml_2.1.14              colorspace_1.3-2        
# [53] rvest_0.3.2              memoise_1.1.0            bindr_0.1                haven_1.1.0 

## "locateVariants" function doesn't work when library "tidyverse" first and then library "VariantAnnotation" and run "locateVariants" function

I need to library "tidyverse" before running "locateVariants" function, I am looking forward to some one can help me with it. Thanks!

Yuzhu

Hi,

After more investigation on this, it seems to be an S4 problem only. What's causing it is that both the lubridate (which tidyverse depends on) and S4Vectors packages define a "union" S4 generic. So after loading the 2 packages, 2 "union" S4 generics end up in the cache. Because of some issues in the methods package, this confuses getGeneric(), standardGeneric(), callNextMethod(), and maybe a few other things.

I committed a workaround in S4Vectors that addresses the original issue you reported. It's just a workaround though. Hopefully the methods package will be fixed in the next release of R to handle homonymic generics properly. The workaround is in S4Vectors 0.14.4 (release) and 0.15.7 (devel). Both versions should become available via biocLite() in the next 48 hours or so.

Cheers,

H.

There are several select() functions to subset by columns. One is defined by tidyverse, but in your case select() you need the ones defined by the AnnotationDbi and biomaRt packages. You can check which select() function is first recognized in your environment by calling it without arguments:

## Before importing tidyverse
> select
standardGeneric for "select" defined from package "AnnotationDbi"

function (x, keys, columns, keytype, ...) 
standardGeneric("select")
<environment: 0x7c1c000>
Methods may be defined for arguments: x
Use  showMethods("select")  for currently available ones.
>

When you load the tidyverse package you will see a list of conflicts. Here many tidyverse functions can take preference over Bioconductor:

## Messages from importing tidyverse
Conflicts with tidy packages ---------------------------------------------------
collapse(): dplyr, Biostrings, IRanges
combine():  dplyr, Biobase, BiocGenerics
compact():  purrr, XVector
count():    dplyr, matrixStats
desc():     dplyr, IRanges
expand():   tidyr, VariantAnnotation, S4Vectors
filter():   dplyr, stats
first():    dplyr, S4Vectors
lag():      dplyr, stats
Position(): ggplot2, BiocGenerics, base
reduce():   purrr, GenomicRanges, IRanges
rename():   dplyr, S4Vectors
select():   dplyr, VariantAnnotation, AnnotationDbi
slice():    dplyr, XVector, IRanges
>

It's not just select(); many other Bioconductor functions are also masked in the list above: collapse(), combine(), compact(), desc(), expand(), first(), reduce(), rename(), and slice().

After importing tidyverse we can see that the dplyr select() takes preference by again calling it without arguments:

## After importing tidyverse
> select
function (.data, ...) 
{
    UseMethod("select")
}
<environment: namespace:dplyr>
>

You can work around this by importing tidyverse first, then all your bioconductor packages:

## Start a new R session
library(tidyverse)
library(GenomicFeatures)
library(VariantAnnotation)

rd_test <- readRDS("rd_test.rds")
txdb <- loadDb("Homo_sapiens.GRCh38.90.sqlite")
allvar <- locateVariants(rd_test, txdb, AllVariants())

Now when you load the GenomicFeatures you will see:

The following object is masked from ‘package:dplyr’:

    select

If you ever need to use the dplyr select or some of the other masked tidyverse functions, you should call them explicitly with the double semi-colon notation:

dplyr::select()