Hi everyone.

Up until this afternoon, never had a problem with biomaRT and the following code:

myMart <- useMart(biomart="ENSEMBL_MART_ENSEMBL")
mouse.anno <- useMart(biomart="ENSEMBL_MART_ENSEMBL", dataset = "mmusculus_gene_ensembl")

gene <- getBM(attributes=c("gene_biotype", "external_gene_name", "description"), filters = "external_gene_name", values=res.df$external_gene_name, mart=mouse.anno)

But now, i'm getting this eror:

Error in .processResults(postRes, mart = mart, sep = sep, fullXmlQuery = fullXmlQuery, : Query ERROR: caught BioMart::Exception::Database: Could not connect to mysql database ensembl_mart_104: DBI connect('database=ensembl_mart_104;host=127.0.0.1;port=5316','ensro',...) failed: Can't connect to MySQL server on '127.0.0.1' (111) at /nfs/public/ro/ensweb/live/mart/www_104/biomart-perl/lib/BioMart/Configuration/DBLocation.pm line 98.

Is this is a congestion issue? Is there alternative code?

Thanks.

```r sessionInfo() R version 4.0.5 (2021-03-31) Platform: x86_64-apple-darwin17.0 (64-bit) Running under: macOS Catalina 10.15.7

Matrix products: default BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib

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

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

other attached packages: [1] viridis_0.6.1 viridisLite_0.4.0 hrbrthemes_0.8.0 enrichR_3.0
[5] ggvenn_0.1.8 scales_1.1.1 pheatmap_1.0.12 enrichplot_1.10.2
[9] msigdbr_7.4.1 clusterProfiler_3.18.1 gprofiler2_0.2.0 GSVA_1.38.2
[13] GSEABase_1.52.1 graph_1.68.0 annotate_1.68.0 XML_3.99-0.6
[17] VennDiagram_1.6.20 futile.logger_1.4.3 ggrepel_0.9.1 patchwork_1.1.1
[21] IsoformSwitchAnalyzeR_1.12.0 DEXSeq_1.36.0 DESeq2_1.30.1 ggpubr_0.4.0
[25] RColorBrewer_1.1-2 org.Mm.eg.db_3.12.0 gplots_3.1.1 Glimma_2.0.0
[29] tximport_1.18.0 DT_0.18 plotly_4.9.3 EnsDb.Mmusculus.v79_2.99.0
[33] ensembldb_2.14.1 AnnotationFilter_1.14.0 GenomicFeatures_1.42.3 AnnotationDbi_1.52.0
[37] gt_0.3.0 cowplot_1.1.1 RUVSeq_1.24.0 forcats_0.5.1
[41] stringr_1.4.0 dplyr_1.0.6 purrr_0.3.4 readr_1.4.0
[45] tidyr_1.1.3 tibble_3.1.2 ggplot2_3.3.3 tidyverse_1.3.1
[49] EDASeq_2.24.0 ShortRead_1.48.0 GenomicAlignments_1.26.0 SummarizedExperiment_1.20.0 [53] MatrixGenerics_1.2.1 matrixStats_0.59.0 Rsamtools_2.6.0 GenomicRanges_1.42.0
[57] GenomeInfoDb_1.26.7 Biostrings_2.58.0 XVector_0.30.0 IRanges_2.24.1
[61] S4Vectors_0.28.1 BiocParallel_1.24.1 Biobase_2.50.0 BiocGenerics_0.36.1
[65] biomaRt_2.46.3 edgeR_3.32.1 limma_3.46.0

loaded via a namespace (and not attached): [1] rappdirs_0.3.3 rtracklayer_1.50.0 R.methodsS3_1.8.1 knitr_1.33
[5] bit64_4.0.5 aroma.light_3.20.0 DelayedArray_0.16.3 R.utils_2.10.1
[9] data.table_1.14.0 hwriter_1.3.2 RCurl_1.98-1.3 generics_0.1.0
[13] lambda.r_1.2.4 RSQLite_2.2.7 shadowtext_0.0.8 bit_4.0.4
[17] xml2_1.3.2 lubridate_1.7.10 httpuv_1.6.1 assertthat_0.2.1
[21] xfun_0.23 hms_1.1.0 evaluate_0.14 babelgene_21.4
[25] promises_1.2.0.1 fansi_0.5.0 progress_1.2.2 caTools_1.18.2
[29] dbplyr_2.1.1 readxl_1.3.1 igraph_1.2.6 DBI_1.1.1
[33] geneplotter_1.68.0 htmlwidgets_1.5.3 ellipsis_0.3.2 backports_1.2.1
[37] vctrs_0.3.8 abind_1.4-5 cachem_1.0.5 withr_2.4.2
[41] ggforce_0.3.3 BSgenome_1.58.0 prettyunits_1.1.1 DOSE_3.16.0
[45] lazyeval_0.2.2 crayon_1.4.1 genefilter_1.72.1 labeling_0.4.2
[49] pkgconfig_2.0.3 tweenr_1.0.2 ProtGenerics_1.22.0 rlang_0.4.11
[53] lifecycle_1.0.0 downloader_0.4 extrafontdb_1.0 BiocFileCache_1.14.0
[57] modelr_0.1.8 AnnotationHub_2.22.1 cellranger_1.1.0 polyclip_1.10-0
[61] Matrix_1.3-4 carData_3.0-4 tximeta_1.8.5 reprex_2.0.0
[65] rjson_0.2.20 png_0.1-7 bitops_1.0-7 R.oo_1.24.0
[69] KernSmooth_2.23-20 blob_1.2.1 qvalue_2.22.0 jpeg_0.1-8.1
[73] rstatix_0.7.0 ggsignif_0.6.1 memoise_2.0.0 magrittr_2.0.1
[77] plyr_1.8.6 zlibbioc_1.36.0 scatterpie_0.1.6 compiler_4.0.5
[81] cli_2.5.0 formatR_1.11 MASS_7.3-54 tidyselect_1.1.1
[85] stringi_1.6.2 yaml_2.2.1 GOSemSim_2.16.1 askpass_1.1
[89] locfit_1.5-9.4 latticeExtra_0.6-29 fastmatch_1.1-0 tools_4.0.5
[93] rio_0.5.26 rstudioapi_0.13 foreign_0.8-81 gridExtra_2.3
[97] farver_2.1.0 ggraph_2.0.5 rvcheck_0.1.8 digest_0.6.27
[101] BiocManager_1.30.15 shiny_1.6.0 Rcpp_1.0.6 car_3.0-10
[105] broom_0.7.6 BiocVersion_3.12.0 later_1.2.0 gdtools_0.2.3
[109] httr_1.4.2 colorspace_2.0-1 rvest_1.0.0 fs_1.5.0
[113] splines_4.0.5 statmod_1.4.36 graphlayouts_0.7.1 systemfonts_1.0.2
[117] xtable_1.8-4 jsonlite_1.7.2 futile.options_1.0.1 tidygraph_1.2.0
[121] R6_2.5.0 pillar_1.6.1 htmltools_0.5.1.1 mime_0.10
[125] DRIMSeq_1.18.0 glue_1.4.2 fastmap_1.1.0 interactiveDisplayBase_1.28.0 [129] fgsea_1.16.0 utf8_1.2.1 lattice_0.20-44 curl_4.3.1
[133] gtools_3.8.2 Rttf2pt1_1.3.8 zip_2.2.0 GO.db_3.12.1
[137] openxlsx_4.2.3 openssl_1.4.4 survival_3.2-11 rmarkdown_2.8
[141] munsell_0.5.0 DO.db_2.9 GenomeInfoDbData_1.2.4 haven_2.4.1
[145] reshape2_1.4.4 gtable_0.3.0 extrafont_0.17

The error you've encountered ("Query ERROR: caught BioMart::Exception::Database") comes from the Ensembl BioMart server. If that has a problem, there's nothing biomaRt can really do to help. The source of the data is broken, and you have to wait for Ensembl to fix it. However, for me the code now works so hopefully it is now resolved:

library(biomaRt)

mouse.anno <- useMart(biomart="ENSEMBL_MART_ENSEMBL", dataset = "mmusculus_gene_ensembl")

getBM(attributes=c("gene_biotype", "external_gene_name", "description"), 
      filters = "external_gene_name", 
      values = "Cdc6", 
      mart = mouse.anno)
#>     gene_biotype external_gene_name
#> 1 protein_coding               Cdc6
#>                                                 description
#> 1 cell division cycle 6 [Source:MGI Symbol;Acc:MGI:1345150]

If you encounter this again, one option is to try querying one of the Ensembl mirrors, which may be working even if the main site has a problem. You can do that by creating you Mart object with the function useEnsembl() rather than useMart()

mouse.anno <- useEnsembl(biomart = "genes", 
                         dataset = "mmusculus_gene_ensembl", 
                         mirror = "asia")

Values for the mirror argument are: www, useast, uswest, asia.