This R package provides methods for genetic finemapping in inbred mice by taking advantage of their very high homozygosity rate (>95%).
Method fetch
allows to download homozygous genotypes of 37 inbred mouse strains for a given genetic region.
if(!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("MouseFM")
library(MouseFM)
Fetch genotypes for region chr1:5000000-6000000.
df = fetch("chr1", start=5000000, end=6000000)
#> Query chr1:5,000,000-6,000,000
df[1:10,]
#> chr pos rsid ref alt most_severe_consequence
#> 1 1 5000016 rs47088541 A T intron_variant
#> 2 1 5000029 rs48827827 G A intron_variant
#> 3 1 5000057 rs48099867 C T intron_variant
#> 4 1 5000062 rs246021564 G C intron_variant
#> 5 1 5000067 rs265132353 C T intron_variant
#> 6 1 5000068 rs51419610 A G intron_variant
#> 7 1 5000101 rs253320650 C G intron_variant
#> 8 1 5000156 <NA> C T intron_variant
#> 9 1 5000157 rs216747169 G A intron_variant
#> 10 1 5000240 <NA> T G intron_variant
#> consequences C57BL_6J
#> 1 non_coding_transcript_variant,intron_variant,NMD_transcript_variant 0
#> 2 non_coding_transcript_variant,intron_variant,NMD_transcript_variant 0
#> 3 non_coding_transcript_variant,intron_variant,NMD_transcript_variant 0
#> 4 non_coding_transcript_variant,intron_variant,NMD_transcript_variant 0
#> 5 non_coding_transcript_variant,intron_variant,NMD_transcript_variant 0
#> 6 non_coding_transcript_variant,intron_variant,NMD_transcript_variant 0
#> 7 non_coding_transcript_variant,intron_variant,NMD_transcript_variant 0
#> 8 non_coding_transcript_variant,intron_variant,NMD_transcript_variant 0
#> 9 non_coding_transcript_variant,intron_variant,NMD_transcript_variant 0
#> 10 non_coding_transcript_variant,intron_variant,NMD_transcript_variant 0
#> 129P2_OlaHsd 129S1_SvImJ 129S5SvEvBrd AKR_J A_J BALB_cJ BTBR BUB_BnJ C3H_HeH
#> 1 0 0 0 0 0 0 0 0 1
#> 2 0 0 0 0 0 0 0 0 1
#> 3 0 0 0 0 0 0 0 0 1
#> 4 0 0 0 0 0 0 0 0 1
#> 5 0 0 0 0 0 0 0 0 1
#> 6 0 0 0 0 0 0 0 0 1
#> 7 0 0 0 0 0 0 0 0 1
#> 8 0 0 0 0 0 0 0 0 0
#> 9 0 0 0 0 0 0 0 0 1
#> 10 0 0 0 0 0 0 0 0 0
#> C3H_HeJ C57BL_10J C57BL_6NJ C57BR_cdJ C57L_J C58_J CAST_EiJ CBA_J DBA_1J
#> 1 1 0 0 0 0 0 1 1 1
#> 2 1 0 0 0 0 0 0 1 1
#> 3 1 0 0 0 0 0 0 1 1
#> 4 1 0 0 0 0 0 0 1 1
#> 5 1 0 0 0 0 0 0 1 1
#> 6 1 0 0 0 0 0 0 1 1
#> 7 1 0 0 0 0 0 0 1 1
#> 8 0 0 0 0 0 0 0 0 0
#> 9 1 0 0 0 0 0 0 1 0
#> 10 0 0 0 0 0 0 0 0 0
#> DBA_2J FVB_NJ I_LnJ KK_HiJ LEWES_EiJ LP_J MOLF_EiJ NOD_ShiLtJ NZB_B1NJ
#> 1 1 0 0 0 1 0 0 0 1
#> 2 1 0 0 0 1 0 0 0 0
#> 3 1 0 0 0 1 0 0 0 0
#> 4 1 0 0 0 1 0 0 0 0
#> 5 1 0 0 0 1 0 0 0 0
#> 6 1 0 0 0 1 0 0 0 0
#> 7 1 0 0 0 1 0 0 0 0
#> 8 0 0 0 0 0 0 0 0 1
#> 9 0 0 0 0 1 0 0 0 0
#> 10 0 0 0 0 0 0 0 0 1
#> NZO_HlLtJ NZW_LacJ PWK_PhJ RF_J SEA_GnJ SPRET_EiJ ST_bJ WSB_EiJ ZALENDE_EiJ
#> 1 0 0 1 1 0 1 0 1 1
#> 2 0 0 1 1 0 1 0 1 1
#> 3 0 0 1 1 0 1 0 1 1
#> 4 0 0 1 1 0 1 0 1 1
#> 5 0 0 1 1 0 0 0 1 1
#> 6 0 0 1 1 0 1 0 1 1
#> 7 0 0 1 1 0 1 0 1 1
#> 8 0 0 0 0 0 0 0 0 0
#> 9 0 0 0 1 0 0 0 1 1
#> 10 0 0 0 0 0 0 0 0 0
View meta information
comment(df)
#> [1] "#Alleles of strain C57BL_6J represent the reference (ref) alleles"
#> [2] "#reference_version=GRCm38"
The output of sessionInfo()
on the system
on which this document was compiled:
sessionInfo()
#> R version 4.1.2 (2021-11-01)
#> Platform: x86_64-apple-darwin17.0 (64-bit)
#> Running under: macOS Mojave 10.14.6
#>
#> Matrix products: default
#> BLAS: /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRblas.0.dylib
#> LAPACK: /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRlapack.dylib
#>
#> locale:
#> [1] C/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
#>
#> attached base packages:
#> [1] stats graphics grDevices utils datasets methods base
#>
#> other attached packages:
#> [1] MouseFM_1.4.1 BiocStyle_2.22.0
#>
#> loaded via a namespace (and not attached):
#> [1] Biobase_2.54.0 httr_1.4.2 tidyr_1.1.4
#> [4] sass_0.4.0 bit64_4.0.5 jsonlite_1.7.2
#> [7] gtools_3.9.2 bslib_0.3.1 assertthat_0.2.1
#> [10] BiocManager_1.30.16 stats4_4.1.2 BiocFileCache_2.2.0
#> [13] blob_1.2.2 GenomeInfoDbData_1.2.7 yaml_2.2.1
#> [16] progress_1.2.2 pillar_1.6.4 RSQLite_2.2.8
#> [19] rlist_0.4.6.2 glue_1.5.0 digest_0.6.28
#> [22] GenomicRanges_1.46.0 XVector_0.34.0 colorspace_2.0-2
#> [25] plyr_1.8.6 htmltools_0.5.2 XML_3.99-0.8
#> [28] pkgconfig_2.0.3 biomaRt_2.50.0 bookdown_0.24
#> [31] zlibbioc_1.40.0 purrr_0.3.4 scales_1.1.1
#> [34] tibble_3.1.6 KEGGREST_1.34.0 generics_0.1.1
#> [37] IRanges_2.28.0 ggplot2_3.3.5 ellipsis_0.3.2
#> [40] cachem_1.0.6 BiocGenerics_0.40.0 magrittr_2.0.1
#> [43] crayon_1.4.2 memoise_2.0.0 evaluate_0.14
#> [46] fansi_0.5.0 xml2_1.3.2 tools_4.1.2
#> [49] data.table_1.14.2 prettyunits_1.1.1 hms_1.1.1
#> [52] lifecycle_1.0.1 stringr_1.4.0 S4Vectors_0.32.2
#> [55] munsell_0.5.0 AnnotationDbi_1.56.2 Biostrings_2.62.0
#> [58] compiler_4.1.2 jquerylib_0.1.4 GenomeInfoDb_1.30.0
#> [61] rlang_0.4.12 grid_4.1.2 RCurl_1.98-1.5
#> [64] rappdirs_0.3.3 bitops_1.0-7 rmarkdown_2.11
#> [67] gtable_0.3.0 DBI_1.1.1 curl_4.3.2
#> [70] reshape2_1.4.4 R6_2.5.1 knitr_1.36
#> [73] dplyr_1.0.7 fastmap_1.1.0 bit_4.0.4
#> [76] utf8_1.2.2 filelock_1.0.2 stringi_1.7.5
#> [79] Rcpp_1.0.7 vctrs_0.3.8 png_0.1-7
#> [82] dbplyr_2.1.1 tidyselect_1.1.1 xfun_0.28