3. Distributions of Data and Quality Control Diagnostics
Belinda Cornes
2021-05-04
Last updated: 2021-05-04
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Knit directory: QTL_Analysis_Report-Pinkney/
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3.1 Phenotype distribution
In total we have 225 samples, among them 120 females, 105 males. We use 6 phenotypes for QTL analysis. They are:
- average right eye axial length (
R_AVG), - average left eye axial length (
L_AVG), - average axial length for both eyes (
Both_AVG), - average right eye axial length for degeneration data (
deg_avg_r), - average left eye axial length for degeneration data (
deg_avg_l), - average axial length for both eyes for degeneration data (
deg_avg_b).
Phenotypic distributions are plotted below.
QTL analysis requires variables follow normal distribution, from the above distributions, there are no “bad” candidates for QTL analysis.
However, we removed any samples that were 3 standard deviations from the mean for a particular phenotype. These were:
| Mouse.ID | R_AVG | L_AVG | Both_AVG | deg_avg_r | deg_avg_l | deg_avg_b |
|---|---|---|---|---|---|---|
| 270 | XX | |||||
| 806 | XX | XX | XX | |||
| 895 | XX |
That is, those that have a grey square were removed for that particular phenotype in the QTL mapping.
3.2 Genotyping quality assessment
The recombination fraction (RF) plot is presented below. Markers on the same chromosome that are closer to each other are assumed to be linked (yellow color); Markers that are far away from each other on the same chromosome or markers on the different chromosomes are assumed to be independent. The patterns in Figure 2 suggests that the quality of genotyping is reasonably good.
--Read the following data:
225 individuals
62 markers
6 phenotypes
--Cross type: f2 
R version 3.6.2 (2019-12-12)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Catalina 10.15.7
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib
locale:
[1] en_AU.UTF-8/en_AU.UTF-8/en_AU.UTF-8/C/en_AU.UTF-8/en_AU.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] qtl_1.46-2 qtl2_0.22 reshape2_1.4.4 ggplot2_3.3.2
[5] tibble_3.0.1 psych_2.0.7 readxl_1.3.1 cluster_2.1.0
[9] dplyr_0.8.5 optparse_1.6.6 rhdf5_2.28.1 mclust_5.4.6
[13] tidyr_1.0.2 data.table_1.12.8 knitr_1.28 kableExtra_1.1.0
[17] workflowr_1.6.2
loaded via a namespace (and not attached):
[1] httr_1.4.1 bit64_0.9-7 jsonlite_1.6.1 viridisLite_0.3.0
[5] assertthat_0.2.1 blob_1.2.1 cellranger_1.1.0 yaml_2.2.1
[9] pillar_1.4.4 RSQLite_2.2.0 backports_1.1.7 lattice_0.20-38
[13] glue_1.4.1 digest_0.6.25 promises_1.1.0 rvest_0.3.5
[17] colorspace_1.4-1 htmltools_0.4.0 httpuv_1.5.2 plyr_1.8.6
[21] pkgconfig_2.0.3 purrr_0.3.4 scales_1.1.1 webshot_0.5.2
[25] whisker_0.4 getopt_1.20.3 later_1.0.0 git2r_0.26.1
[29] farver_2.0.3 ellipsis_0.3.1 withr_2.2.0 mnormt_1.5-7
[33] magrittr_1.5 crayon_1.3.4 memoise_1.1.0 evaluate_0.14
[37] fs_1.4.1 nlme_3.1-142 xml2_1.3.1 tools_3.6.2
[41] hms_0.5.3 lifecycle_0.2.0 stringr_1.4.0 Rhdf5lib_1.6.3
[45] munsell_0.5.0 pastecs_1.3.21 compiler_3.6.2 rlang_0.4.6
[49] grid_3.6.2 rstudioapi_0.11 labeling_0.3 rmarkdown_2.1
[53] boot_1.3-23 gtable_0.3.0 DBI_1.1.0 R6_2.4.1
[57] bit_1.1-15.2 rprojroot_1.3-2 readr_1.3.1 stringi_1.4.6
[61] parallel_3.6.2 Rcpp_1.0.4.6 vctrs_0.3.1 tidyselect_1.0.0
[65] xfun_0.13