Last updated: 2025-02-18
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Knit directory: muse/
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File | Version | Author | Date | Message |
---|---|---|---|---|
Rmd | 4aeedcb | Dave Tang | 2025-02-18 | CD4 and CD8 markers |
html | 102d48a | Dave Tang | 2025-02-18 | Build site. |
Rmd | 8edc91c | Dave Tang | 2025-02-18 | Convert rat gene symbols to mouse |
html | 1080430 | Dave Tang | 2025-02-18 | Build site. |
Rmd | 6edbb51 | Dave Tang | 2025-02-18 | Use homologene |
html | 576dac1 | Dave Tang | 2025-02-18 | Build site. |
Rmd | 1500177 | Dave Tang | 2025-02-18 | Convert gene symbols across species |
To begin, install the {biomaRt} package.
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("biomaRt")
Load package.
suppressPackageStartupMessages(library(biomaRt))
packageVersion("biomaRt")
[1] '2.62.1'
Adapted from https://www.biostars.org/p/446641/.
getLDS()
retrieves information from two linked datasets;
this function is the main {biomaRt} query function that links 2 datasets
and retrieves information from these linked BioMart datasets. In Ensembl
this translates to homology mapping.
human_us_mart <- useEnsembl(
biomart = "ensembl",
mirror = "useast",
dataset = "hsapiens_gene_ensembl"
)
rat_us_mart <- useEnsembl(
biomart = "ensembl",
mirror = "useast",
dataset = "rnorvegicus_gene_ensembl"
)
rat_genes <- c("Tll1", "Tlx3")
rat_to_human <- getLDS(
attributes = c("rgd_symbol"),
filters = "rgd_symbol",
values = rat_genes,
mart = rat_us_mart,
attributesL = c("hgnc_symbol"),
martL = human_us_mart,
uniqueRows = TRUE
)
Error in `httr2::req_perform()`:
! HTTP 502 Bad Gateway.
rat_to_human
Error: object 'rat_to_human' not found
Expected output:
#> RGD.symbol HGNC.symbol
#> 1 Tll1 TLL1
#> 2 Tlx3 TLX3
Install package.
install.packages("homologene")
NCBI Taxonomy IDs:
Convert from rat to human.
suppressPackageStartupMessages(library(homologene))
# Convert human genes to rat genes
# 9606 = human
# 10116 = rat
human_genes <- homologene(
rat_genes,
inTax = 10116,
outTax = 9606
)
human_genes
10116 9606 10116_ID 9606_ID
1 Tll1 TLL1 678743 7092
2 Tlx3 TLX3 497881 30012
Convert from rat to mouse.
homologene(
rat_genes,
inTax = 10116,
outTax = 10090
)
10116 10090 10116_ID 10090_ID
1 Tll1 Tll1 678743 21892
2 Tlx3 Tlx3 497881 27140
Human CD4+ T cell markers.
cd4_markers <- c("IL7R", "MAL", "LTB", "CD4", "LDHB", "TPT1", "TRAC", "TMSB10", "CD3D", "CD3G")
homologene(
cd4_markers,
outTax = 10116,
inTax = 9606
)
9606 10116 9606_ID 10116_ID
1 IL7R Il7r 3575 294797
2 MAL Mal 4118 25263
3 LTB Ltb 4050 361795
4 CD4 Cd4 920 24932
5 LDHB Ldhb 3945 24534
6 TPT1 Tpt1 7178 116646
7 CD3D Cd3d 915 25710
8 CD3G Cd3g 917 300678
Human CD8+ T cell markers.
cd8_markers <- c("CD8B", "CD8A", "CD3D", "TMSB10", "HCST", "CD3G", "LINC02446", "CTSW", "CD3E", "TRAC")
homologene(
cd8_markers,
outTax = 10116,
inTax = 9606
)
9606 10116 9606_ID 10116_ID
1 CD8B Cd8b 926 24931
2 CD8A Cd8a 925 24930
3 CD3D Cd3d 915 25710
4 HCST Hcst 10870 474146
5 CD3G Cd3g 917 300678
6 CTSW Ctsw 1521 293676
7 CD3E Cd3e 916 315609
sessionInfo()
R version 4.4.1 (2024-06-14)
Platform: x86_64-pc-linux-gnu
Running under: Ubuntu 22.04.5 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so; LAPACK version 3.10.0
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] 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
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
time zone: Etc/UTC
tzcode source: system (glibc)
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] homologene_1.4.68.19.3.27 biomaRt_2.62.1
[3] workflowr_1.7.1
loaded via a namespace (and not attached):
[1] KEGGREST_1.46.0 xfun_0.48 bslib_0.8.0
[4] httr2_1.0.5 processx_3.8.4 Biobase_2.66.0
[7] callr_3.7.6 generics_0.1.3 vctrs_0.6.5
[10] tools_4.4.1 ps_1.8.1 curl_5.2.3
[13] stats4_4.4.1 tibble_3.2.1 fansi_1.0.6
[16] AnnotationDbi_1.68.0 RSQLite_2.3.7 blob_1.2.4
[19] pkgconfig_2.0.3 dbplyr_2.5.0 S4Vectors_0.44.0
[22] lifecycle_1.0.4 GenomeInfoDbData_1.2.13 compiler_4.4.1
[25] stringr_1.5.1 git2r_0.35.0 Biostrings_2.74.1
[28] progress_1.2.3 getPass_0.2-4 httpuv_1.6.15
[31] GenomeInfoDb_1.42.3 htmltools_0.5.8.1 sass_0.4.9
[34] yaml_2.3.10 later_1.3.2 pillar_1.9.0
[37] crayon_1.5.3 jquerylib_0.1.4 whisker_0.4.1
[40] cachem_1.1.0 tidyselect_1.2.1 digest_0.6.37
[43] stringi_1.8.4 purrr_1.0.2 dplyr_1.1.4
[46] rprojroot_2.0.4 fastmap_1.2.0 cli_3.6.3
[49] magrittr_2.0.3 utf8_1.2.4 withr_3.0.2
[52] filelock_1.0.3 prettyunits_1.2.0 UCSC.utils_1.2.0
[55] promises_1.3.0 rappdirs_0.3.3 bit64_4.5.2
[58] rmarkdown_2.28 XVector_0.46.0 httr_1.4.7
[61] bit_4.5.0 png_0.1-8 hms_1.1.3
[64] memoise_2.0.1 evaluate_1.0.1 knitr_1.48
[67] IRanges_2.40.1 BiocFileCache_2.14.0 rlang_1.1.4
[70] Rcpp_1.0.13 glue_1.8.0 DBI_1.2.3
[73] xml2_1.3.6 BiocGenerics_0.52.0 rstudioapi_0.17.1
[76] jsonlite_1.8.9 R6_2.5.1 fs_1.6.4
[79] zlibbioc_1.52.0