Hello,

I've been trying to use biomaRt to query ensembl's Biomart and extract genomic and functional information about a list of SNPs. Here's an example of the kind of query I'm doing and the results.

snpMart <- useMart("ENSEMBL_MART_SNP", dataset="hsapiens_snp")
snpList <- c("rs7349186", "rs3927683",  "rs1697421",    "rs12041233", "rs112751018", "rs2819336")
snp_annot <- getBM(attributes = c('refsnp_id', "consequence_type_tv", 'chr_name', 'chrom_start', 'chrom_end'),
                    filters = "snp_filter",
                    values = snpList,
                    mart = snpMart) %>%
  arrange(chr_name, chrom_start) %>%
  relocate(consequence_type_tv, .before = chr_name) 

snp_annot
    refsnp_id consequence_type_tv chr_name chrom_start chrom_end
1   rs7349186    missense_variant        1    20644627  20644627
2   rs3927683                            1    20796024  20796024
3   rs1697421                            1    21496799  21496799
4  rs12041233                            1    37287106  37287106
5 rs112751018                            1    39622232  39622232
6   rs2819336      intron_variant        1    43550138  43550138

The issue I'm having, is related to the consequence_type_tv, on the attributes to extract from the query. In fact, many SNPs return no consequence_type_tv. I've assumed these would be because these were intergenic variants, which is the case for many variants. So, my first issue is that these variants are not labelled as "intergenic variants".

However, when checking a few variants manually in the ensembl site, I've noticed that many that are not annotated by biomaRt, are actually annotated as other consequences, besides intergenic. Take for example rs12041233: in my biomaRt query, there's no annotated functional consequence. In contrast, in the ensembl website, the variant is reported as an intronic variant (for an ensembl lncRNA).

Not only that, I found also some incoherences between what's on the variant page in ensembl, and the information retrieved using biomaRt. Namely, on allelic frequencies reported for minor alleles being different between the two sources (which I thought were the same.)

Am I doing something wrong? Am I missing something?

Thank you very much for your help!

sessioninfo()

R version 4.2.2 (2022-10-31)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.1 LTS

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0

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] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] RColorBrewer_1.1-3 pheatmap_1.0.12    qqman_0.1.8        gprofiler2_0.2.2   UpSetR_1.4.0       eulerr_7.0.0      
 [7] DT_0.28            gwasrapidd_0.99.15 rsnps_0.5.0.0      biomaRt_2.54.1     lubridate_1.9.2    forcats_1.0.0     
[13] stringr_1.5.0      dplyr_1.1.2        purrr_1.0.1        readr_2.1.4        tidyr_1.3.0        tibble_3.2.1      
[19] ggplot2_3.4.2      tidyverse_2.0.0    data.table_1.14.8 

loaded via a namespace (and not attached):
 [1] bitops_1.0-7           bit64_4.0.5            filelock_1.0.2         progress_1.2.2         httr_1.4.6            
 [6] GenomeInfoDb_1.34.9    tools_4.2.2            bslib_0.5.0            utf8_1.2.3             R6_2.5.1              
[11] lazyeval_0.2.2         DBI_1.1.3              BiocGenerics_0.44.0    colorspace_2.1-0       withr_2.5.0           
[16] tidyselect_1.2.0       gridExtra_2.3          prettyunits_1.1.1      bit_4.0.5              curl_5.0.1            
[21] compiler_4.2.2         cli_3.6.1              Biobase_2.58.0         xml2_1.3.5             plotly_4.10.2         
[26] labeling_0.4.2         triebeard_0.4.1        sass_0.4.7             scales_1.2.1           rappdirs_0.3.3        
[31] digest_0.6.33          rmarkdown_2.23         XVector_0.38.0         pkgconfig_2.0.3        htmltools_0.5.5       
[36] dbplyr_2.3.3           fastmap_1.1.1          htmlwidgets_1.6.2      rlang_1.1.1            rstudioapi_0.15.0     
[41] httpcode_0.3.0         RSQLite_2.3.1          shiny_1.7.4.1          farver_2.1.1           jquerylib_0.1.4       
[46] generics_0.1.3         jsonlite_1.8.7         crosstalk_1.2.0        RCurl_1.98-1.12        magrittr_2.0.3        
[51] GenomeInfoDbData_1.2.9 Rcpp_1.0.11            munsell_0.5.0          S4Vectors_0.36.2       fansi_1.0.4           
[56] lifecycle_1.0.3        stringi_1.7.12         yaml_2.3.7             MASS_7.3-60            zlibbioc_1.44.0       
[61] plyr_1.8.8             BiocFileCache_2.6.1    grid_4.2.2             blob_1.2.4             promises_1.2.0.1      
[66] ggrepel_0.9.3          crayon_1.5.2           Biostrings_2.66.0      hms_1.1.3              KEGGREST_1.38.0       
[71] polylabelr_0.2.0       knitr_1.43             pillar_1.9.0           stats4_4.2.2           crul_1.4.0            
[76] XML_3.99-0.14          glue_1.6.2             evaluate_0.21          calibrate_1.7.7        httpuv_1.6.11         
[81] urltools_1.7.3         png_0.1-8              vctrs_0.6.3            tzdb_0.4.0             polyclip_1.10-4       
[86] gtable_0.3.3           assertthat_0.2.1       cachem_1.0.8           xfun_0.39              mime_0.12             
[91] xtable_1.8-4           later_1.3.1            viridisLite_0.4.2      AnnotationDbi_1.60.2   memoise_2.0.1         
[96] IRanges_2.32.0         timechange_0.2.0       ellipsis_0.3.2

The biomaRt package doesn't query Ensembl - it queries the Biomart server at Ensembl. If you do your query by hand using the Biomart server, you get the same results. There might be an argument that what you get from Biomart should 100% match what you get from a directed search of the Ensembl site, but that's an issue for the folks at Ensembl.