Contents

1 Introduction

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.

2 Installation

if(!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("MouseFM")

3 Loading package

library(MouseFM)

4 Example function calls

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_Tplus_Itpr3tf_J
#> 1             0           0            0     0   0       0                    0
#> 2             0           0            0     0   0       0                    0
#> 3             0           0            0     0   0       0                    0
#> 4             0           0            0     0   0       0                    0
#> 5             0           0            0     0   0       0                    0
#> 6             0           0            0     0   0       0                    0
#> 7             0           0            0     0   0       0                    0
#> 8             0           0            0     0   0       0                    0
#> 9             0           0            0     0   0       0                    0
#> 10            0           0            0     0   0       0                    0
#>    BUB_BnJ C3H_HeH C3H_HeJ C57BL_10J C57BL_6NJ C57BR_cdJ C57L_J C58_J CAST_EiJ
#> 1        0       1       1         0         0         0      0     0        1
#> 2        0       1       1         0         0         0      0     0        0
#> 3        0       1       1         0         0         0      0     0        0
#> 4        0       1       1         0         0         0      0     0        0
#> 5        0       1       1         0         0         0      0     0        0
#> 6        0       1       1         0         0         0      0     0        0
#> 7        0       1       1         0         0         0      0     0        0
#> 8        0       0       0         0         0         0      0     0        0
#> 9        0       1       1         0         0         0      0     0        0
#> 10       0       0       0         0         0         0      0     0        0
#>    CBA_J DBA_1J DBA_2J FVB_NJ I_LnJ KK_HiJ LEWES_EiJ LP_J MOLF_EiJ NOD_ShiLtJ
#> 1      1      1      1      0     0      0         1    0        0          0
#> 2      1      1      1      0     0      0         1    0        0          0
#> 3      1      1      1      0     0      0         1    0        0          0
#> 4      1      1      1      0     0      0         1    0        0          0
#> 5      1      1      1      0     0      0         1    0        0          0
#> 6      1      1      1      0     0      0         1    0        0          0
#> 7      1      1      1      0     0      0         1    0        0          0
#> 8      0      0      0      0     0      0         0    0        0          0
#> 9      1      0      0      0     0      0         1    0        0          0
#> 10     0      0      0      0     0      0         0    0        0          0
#>    NZB_B1NJ NZO_HlLtJ NZW_LacJ PWK_PhJ RF_J SEA_GnJ SPRET_EiJ ST_bJ WSB_EiJ
#> 1         1         0        0       1    1       0         1     0       1
#> 2         0         0        0       1    1       0         1     0       1
#> 3         0         0        0       1    1       0         1     0       1
#> 4         0         0        0       1    1       0         1     0       1
#> 5         0         0        0       1    1       0         0     0       1
#> 6         0         0        0       1    1       0         1     0       1
#> 7         0         0        0       1    1       0         1     0       1
#> 8         1         0        0       0    0       0         0     0       0
#> 9         0         0        0       0    1       0         0     0       1
#> 10        1         0        0       0    0       0         0     0       0
#>    ZALENDE_EiJ
#> 1            1
#> 2            1
#> 3            1
#> 4            1
#> 5            1
#> 6            1
#> 7            1
#> 8            0
#> 9            1
#> 10           0

View meta information

comment(df)
#> [1] "#Alleles of strain C57BL_6J represent the reference (ref) alleles"
#> [2] "#reference_version=GRCm38"

5 Output of Session Info

The output of sessionInfo() on the system on which this document was compiled:

sessionInfo()
#> R version 4.0.3 (2020-10-10)
#> Platform: x86_64-pc-linux-gnu (64-bit)
#> Running under: Ubuntu 18.04.5 LTS
#> 
#> Matrix products: default
#> BLAS:   /home/biocbuild/bbs-3.12-bioc/R/lib/libRblas.so
#> LAPACK: /home/biocbuild/bbs-3.12-bioc/R/lib/libRlapack.so
#> 
#> locale:
#>  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
#>  [3] LC_TIME=en_US.UTF-8        LC_COLLATE=C              
#>  [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       
#> 
#> attached base packages:
#> [1] stats     graphics  grDevices utils     datasets  methods   base     
#> 
#> other attached packages:
#> [1] MouseFM_1.0.0    BiocStyle_2.18.0
#> 
#> loaded via a namespace (and not attached):
#>  [1] Rcpp_1.0.5             tidyr_1.1.2            gtools_3.8.2          
#>  [4] prettyunits_1.1.1      assertthat_0.2.1       digest_0.6.27         
#>  [7] BiocFileCache_1.14.0   plyr_1.8.6             R6_2.4.1              
#> [10] GenomeInfoDb_1.26.0    stats4_4.0.3           RSQLite_2.2.1         
#> [13] evaluate_0.14          httr_1.4.2             ggplot2_3.3.2         
#> [16] pillar_1.4.6           zlibbioc_1.36.0        rlang_0.4.8           
#> [19] progress_1.2.2         curl_4.3               data.table_1.13.2     
#> [22] blob_1.2.1             S4Vectors_0.28.0       rmarkdown_2.5         
#> [25] stringr_1.4.0          RCurl_1.98-1.2         bit_4.0.4             
#> [28] biomaRt_2.46.0         munsell_0.5.0          compiler_4.0.3        
#> [31] xfun_0.18              pkgconfig_2.0.3        askpass_1.1           
#> [34] BiocGenerics_0.36.0    htmltools_0.5.0        openssl_1.4.3         
#> [37] tidyselect_1.1.0       tibble_3.0.4           GenomeInfoDbData_1.2.4
#> [40] bookdown_0.21          IRanges_2.24.0         XML_3.99-0.5          
#> [43] crayon_1.3.4           dplyr_1.0.2            dbplyr_1.4.4          
#> [46] bitops_1.0-6           rappdirs_0.3.1         grid_4.0.3            
#> [49] jsonlite_1.7.1         gtable_0.3.0           lifecycle_0.2.0       
#> [52] DBI_1.1.0              magrittr_1.5           scales_1.1.1          
#> [55] rlist_0.4.6.1          stringi_1.5.3          reshape2_1.4.4        
#> [58] XVector_0.30.0         xml2_1.3.2             ellipsis_0.3.1        
#> [61] vctrs_0.3.4            generics_0.0.2         tools_4.0.3           
#> [64] bit64_4.0.5            Biobase_2.50.0         glue_1.4.2            
#> [67] purrr_0.3.4            hms_0.5.3              parallel_4.0.3        
#> [70] yaml_2.2.1             AnnotationDbi_1.52.0   colorspace_1.4-1      
#> [73] BiocManager_1.30.10    GenomicRanges_1.42.0   memoise_1.1.0         
#> [76] knitr_1.30