Last updated: 2023-01-24
Checks: 5 2
Knit directory: Serreze-T1D_Workflow/
This reproducible R Markdown analysis was created with workflowr (version 1.7.0). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.
The R Markdown is untracked by Git. To know which version of the R
Markdown file created these results, you’ll want to first commit it to
the Git repo. If you’re still working on the analysis, you can ignore
this warning. When you’re finished, you can run
wflow_publish to commit the R Markdown file and build the
HTML.
Great job! The global environment was empty. Objects defined in the global environment can affect the analysis in your R Markdown file in unknown ways. For reproduciblity it’s best to always run the code in an empty environment.
The command set.seed(20220210) was run prior to running
the code in the R Markdown file. Setting a seed ensures that any results
that rely on randomness, e.g. subsampling or permutations, are
reproducible.
Great job! Recording the operating system, R version, and package versions is critical for reproducibility.
Nice! There were no cached chunks for this analysis, so you can be confident that you successfully produced the results during this run.
Using absolute paths to the files within your workflowr project makes it difficult for you and others to run your code on a different machine. Change the absolute path(s) below to the suggested relative path(s) to make your code more reproducible.
| absolute | relative |
|---|---|
| /Users/corneb/Documents/MyJax/CS/Projects/Serreze/qc/workflowr/Serreze-T1D_Workflow | . |
Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility.
The results in this page were generated with repository version c9fc66b. See the Past versions tab to see a history of the changes made to the R Markdown and HTML files.
Note that you need to be careful to ensure that all relevant files for
the analysis have been committed to Git prior to generating the results
(you can use wflow_publish or
wflow_git_commit). workflowr only checks the R Markdown
file, but you know if there are other scripts or data files that it
depends on. Below is the status of the Git repository when the results
were generated:
Ignored files:
Ignored: .DS_Store
Ignored: analysis/.DS_Store
Untracked files:
Untracked: analysis/0.1.1_preparing.data_bqc_4.batches_myo.Rmd
Untracked: analysis/0.1.1_preparing.data_bqc_4.batches_myo.Rmd.R
Untracked: analysis/0.1_samples_batch_20220729.Rmd
Untracked: analysis/0.1_samples_batch_20220729.Rmd.R
Untracked: analysis/0.1_samples_batch_20220826.Rmd
Untracked: analysis/0.1_samples_batch_20220826.Rmd.R
Untracked: analysis/0.1_samples_batch_20221006.Rmd
Untracked: analysis/0.1_samples_batch_20221006.Rmd.R
Untracked: analysis/0.1_samples_batch_20221116.Rmd
Untracked: analysis/0.1_samples_batch_20221116.Rmd.R
Untracked: analysis/0.2_haplotype_comparison_bqc_4.batches_myo_minprob.Rmd
Untracked: analysis/0.2_haplotype_comparison_bqc_4.batches_myo_minprob.Rmd.R
Untracked: analysis/2.1_sample_bqc_4.batches_myo.Rmd
Untracked: analysis/2.1_sample_bqc_4.batches_myo.Rmd.R
Untracked: analysis/2.2.1_snp_qc_4.batches_myo.Rmd
Untracked: analysis/2.2.1_snp_qc_4.batches_myo.Rmd.R
Untracked: analysis/2.2.1_snp_qc_4.batches_myo_mis.Rmd
Untracked: analysis/2.2.1_snp_qc_4.batches_myo_mis.Rmd.R
Untracked: analysis/2.4_preparing.data_aqc_4.batches_myo.Rmd
Untracked: analysis/2.4_preparing.data_aqc_4.batches_myo.Rmd.R
Untracked: analysis/2.4_preparing.data_aqc_4.batches_myo_mis.Rmd
Untracked: analysis/2.4_preparing.data_aqc_4.batches_myo_mis.Rmd.R
Untracked: analysis/3.1_phenotype.qc_corrected_4.batches_myo.Rmd
Untracked: analysis/3.1_phenotype.qc_corrected_4.batches_myo.Rmd.R
Untracked: analysis/3.1_phenotype.qc_corrected_4.batches_myo_mis.Rmd
Untracked: analysis/3.1_phenotype.qc_corrected_4.batches_myo_mis.Rmd.R
Untracked: analysis/4.1.1_qtl.analysis_binary_het-ici-myo-yes.vs.het-ici-myo-no_snpsqc_dis_no-x_updated_4.batches_myo.Rmd
Untracked: analysis/4.1.1_qtl.analysis_binary_het-ici-myo-yes.vs.het-ici-myo-no_snpsqc_dis_no-x_updated_4.batches_myo.Rmd.R
Untracked: analysis/4.1.1_qtl.analysis_binary_het-ici-myo-yes.vs.het-ici-myo-no_snpsqc_dis_no-x_updated_4.batches_myo_mis.Rmd
Untracked: analysis/4.1.1_qtl.analysis_binary_het-ici.vs.het-pbs_snpsqc_dis_no-x_updated_4.batches_myo.Rmd
Untracked: analysis/4.1.1_qtl.analysis_binary_het-ici.vs.het-pbs_snpsqc_dis_no-x_updated_4.batches_myo.Rmd.R
Untracked: analysis/4.1.1_qtl.analysis_binary_het-ici.vs.het-pbs_snpsqc_dis_no-x_updated_4.batches_myo_mis.Rmd
Untracked: analysis/4.1.1_qtl.analysis_binary_ici-myo-yes.vs.ici-myo-no_snpsqc_dis_no-x_updated_4.batches_myo.Rmd
Untracked: analysis/4.1.1_qtl.analysis_binary_ici-myo-yes.vs.ici-myo-no_snpsqc_dis_no-x_updated_4.batches_myo.Rmd.R
Untracked: analysis/4.1.1_qtl.analysis_binary_ici-myo-yes.vs.ici-myo-no_snpsqc_dis_no-x_updated_4.batches_myo_mis.Rmd
Untracked: analysis/4.1.1_qtl.analysis_binary_ici-sick.vs.ici-eoi_snpsqc_dis_no-x_updated_4.batches_myo.Rmd
Untracked: analysis/4.1.1_qtl.analysis_binary_ici-sick.vs.ici-eoi_snpsqc_dis_no-x_updated_4.batches_myo.Rmd.R
Untracked: analysis/4.1.1_qtl.analysis_binary_ici-sick.vs.ici-eoi_snpsqc_dis_no-x_updated_4.batches_myo_mis.Rmd
Untracked: analysis/4.1.1_qtl.analysis_binary_ici.vs.pbs_snpsqc_dis_no-x_updated_4.batches_myo.Rmd
Untracked: analysis/4.1.1_qtl.analysis_binary_ici.vs.pbs_snpsqc_dis_no-x_updated_4.batches_myo.Rmd.R
Untracked: analysis/4.1.1_qtl.analysis_binary_ici.vs.pbs_snpsqc_dis_no-x_updated_4.batches_myo_mis.Rmd
Untracked: analysis/4.1.1_qtl.analysis_binary_ici.vs.pbs_snpsqc_dis_no-x_updated_4.batches_myo_mis.Rmd.R
Untracked: analysis/4.1.1_qtl.analysis_binary_ici.vs.pbs_snpsqc_dis_no-x_updated_4.batches_myo_mis1.Rmd
Untracked: analysis/4.1.1_qtl.analysis_binary_myo-yes.vs.myo-no_snpsqc_dis_no-x_updated_4.batches_myo.Rmd
Untracked: analysis/4.1.1_qtl.analysis_binary_myo-yes.vs.myo-no_snpsqc_dis_no-x_updated_4.batches_myo.Rmd.R
Untracked: analysis/4.1.1_qtl.analysis_binary_myo-yes.vs.myo-no_snpsqc_dis_no-x_updated_4.batches_myo_mis.Rmd
Untracked: analysis/4.1.1_qtl.analysis_binary_pbs-myo-yes.vs.pbs-myo-no_snpsqc_dis_no-x_updated_4.batches_myo.Rmd
Untracked: analysis/4.1.1_qtl.analysis_binary_pbs-myo-yes.vs.pbs-myo-no_snpsqc_dis_no-x_updated_4.batches_myo.Rmd.R
Untracked: analysis/4.1.1_qtl.analysis_binary_pbs-myo-yes.vs.pbs-myo-no_snpsqc_dis_no-x_updated_4.batches_myo_mis.Rmd
Untracked: analysis/4.1.1_qtl.analysis_binary_pbs-myo-yes.vs.pbs-myo-no_snpsqc_dis_no-x_updated_4.batches_myo_misRmd.Rmd
Untracked: analysis/genotype.frequencies_het-ici-myo-yes.vs.het-ici-myo-no_4.batches_myo.Rmd
Untracked: analysis/genotype.frequencies_het-ici-myo-yes.vs.het-ici-myo-no_4.batches_myo.Rmd.R
Untracked: analysis/genotype.frequencies_het-ici-myo-yes.vs.het-ici-myo-no_4.batches_myo_mis.Rmd
Untracked: analysis/genotype.frequencies_het-ici-myo-yes.vs.het-ici-myo-no_4.batches_myo_mis.Rmd.R
Untracked: analysis/genotype.frequencies_het-ici.vs.het-pbs_4.batches_myo.Rmd
Untracked: analysis/genotype.frequencies_het-ici.vs.het-pbs_4.batches_myo.Rmd.R
Untracked: analysis/genotype.frequencies_het-ici.vs.het-pbs_4.batches_myo_mis.Rmd
Untracked: analysis/genotype.frequencies_het-ici.vs.het-pbs_4.batches_myo_mis.Rmd.R
Untracked: analysis/genotype.frequencies_ici-myo-yes.vs.ici-myo-no_4.batches_myo.Rmd
Untracked: analysis/genotype.frequencies_ici-myo-yes.vs.ici-myo-no_4.batches_myo.Rmd.R
Untracked: analysis/genotype.frequencies_ici-myo-yes.vs.ici-myo-no_4.batches_myo_mis.Rmd
Untracked: analysis/genotype.frequencies_ici-myo-yes.vs.ici-myo-no_4.batches_myo_mis.Rmd.R
Untracked: analysis/genotype.frequencies_ici-sick.vs.ici-eoi_4.batches_myo.Rmd
Untracked: analysis/genotype.frequencies_ici-sick.vs.ici-eoi_4.batches_myo.Rmd.R
Untracked: analysis/genotype.frequencies_ici-sick.vs.ici-eoi_4.batches_myo_mis.Rmd
Untracked: analysis/genotype.frequencies_ici-sick.vs.ici-eoi_4.batches_myo_mis.Rmd.R
Untracked: analysis/genotype.frequencies_ici.vs.pbs_4.batches_myo.Rmd
Untracked: analysis/genotype.frequencies_ici.vs.pbs_4.batches_myo.Rmd.R
Untracked: analysis/genotype.frequencies_ici.vs.pbs_4.batches_myo_mis.Rmd
Untracked: analysis/genotype.frequencies_ici.vs.pbs_4.batches_myo_mis.Rmd.R
Untracked: analysis/genotype.frequencies_myo-yes.vs.myo-no_4.batches_myo.Rmd
Untracked: analysis/genotype.frequencies_myo-yes.vs.myo-no_4.batches_myo.Rmd.R
Untracked: analysis/genotype.frequencies_myo-yes.vs.myo-no_4.batches_myo_mis.Rmd
Untracked: analysis/genotype.frequencies_myo-yes.vs.myo-no_4.batches_myo_mis.Rmd.R
Untracked: analysis/genotype.frequencies_pbs-myo-yes.vs.pbs-myo-no_4.batches_myo.Rmd
Untracked: analysis/genotype.frequencies_pbs-myo-yes.vs.pbs-myo-no_4.batches_myo.Rmd.R
Untracked: analysis/genotype.frequencies_pbs-myo-yes.vs.pbs-myo-no_4.batches_myo_mis.Rmd
Untracked: analysis/genotype.frequencies_pbs-myo-yes.vs.pbs-myo-no_4.batches_myo_mis.Rmd.R
Untracked: analysis/index_4.batches_myo.Rmd
Untracked: analysis/index_4.batches_myo.Rmd.R
Untracked: analysis/power.analysis_het-ici-myo-yes.vs.het-ici-myo-no_4.batches_myo.Rmd
Untracked: analysis/power.analysis_het-ici-myo-yes.vs.het-ici-myo-no_4.batches_myo.Rmd.R
Untracked: analysis/power.analysis_het-ici-myo-yes.vs.het-ici-myo-no_4.batches_myo_mis.Rmd
Untracked: analysis/power.analysis_het-ici-myo-yes.vs.het-ici-myo-no_4.batches_myo_mis.Rmd.R
Untracked: analysis/power.analysis_het-ici.vs.het-pbs_4.batches_myo.Rmd
Untracked: analysis/power.analysis_het-ici.vs.het-pbs_4.batches_myo.Rmd.R
Untracked: analysis/power.analysis_het-ici.vs.het-pbs_4.batches_myo_mis.Rmd
Untracked: analysis/power.analysis_het-ici.vs.het-pbs_4.batches_myo_mis.Rmd.R
Untracked: analysis/power.analysis_ici-myo-yes.vs.ici-myo-no_4.batches_myo.Rmd
Untracked: analysis/power.analysis_ici-myo-yes.vs.ici-myo-no_4.batches_myo.Rmd.R
Untracked: analysis/power.analysis_ici-myo-yes.vs.ici-myo-no_4.batches_myo_mis.Rmd
Untracked: analysis/power.analysis_ici-myo-yes.vs.ici-myo-no_4.batches_myo_mis.Rmd.R
Untracked: analysis/power.analysis_ici-sick.vs.ici-eoi_4.batches_myo.Rmd
Untracked: analysis/power.analysis_ici-sick.vs.ici-eoi_4.batches_myo.Rmd.R
Untracked: analysis/power.analysis_ici-sick.vs.ici-eoi_4.batches_myo_mis.Rmd
Untracked: analysis/power.analysis_ici-sick.vs.ici-eoi_4.batches_myo_mis.Rmd.R
Untracked: analysis/power.analysis_ici.vs.pbs_4.batches_myo.R
Untracked: analysis/power.analysis_ici.vs.pbs_4.batches_myo.Rmd
Untracked: analysis/power.analysis_ici.vs.pbs_4.batches_myo.Rmd.R
Untracked: analysis/power.analysis_ici.vs.pbs_4.batches_myo_mis.Rmd
Untracked: analysis/power.analysis_ici.vs.pbs_4.batches_myo_mis.Rmd.R
Untracked: analysis/power.analysis_myo-yes.vs.myo-no_4.batches_myo.Rmd
Untracked: analysis/power.analysis_myo-yes.vs.myo-no_4.batches_myo.Rmd.R
Untracked: analysis/power.analysis_myo-yes.vs.myo-no_4.batches_myo_mis.Rmd
Untracked: analysis/power.analysis_myo-yes.vs.myo-no_4.batches_myo_mis.Rmd.R
Untracked: analysis/power.analysis_pbs-myo-yes.vs.pbs-myo-no_4.batches_myo copy.Rmd.R
Untracked: analysis/power.analysis_pbs-myo-yes.vs.pbs-myo-no_4.batches_myo.Rmd
Untracked: analysis/power.analysis_pbs-myo-yes.vs.pbs-myo-no_4.batches_myo.Rmd.R
Untracked: analysis/power.analysis_pbs-myo-yes.vs.pbs-myo-no_4.batches_myo_mis.Rmd
Untracked: analysis/power.analysis_pbs-myo-yes.vs.pbs-myo-no_4.batches_myo_mis.Rmd.R
Untracked: data copy/
Untracked: data/GM_covar_4.batches_myo.csv
Untracked: data/bad_markers_all_4.batches_myo.RData
Untracked: data/covar_corrected.cleaned_het-ici-myo-yes.vs.het-ici-myo-no_4.batches_myo.csv
Untracked: data/covar_corrected.cleaned_het-ici-myo-yes.vs.het-ici-myo-no_4.batches_myo_mis.csv
Untracked: data/covar_corrected.cleaned_het-ici.vs.het-pbs_4.batches_myo.csv
Untracked: data/covar_corrected.cleaned_het-ici.vs.het-pbs_4.batches_myo_mis.csv
Untracked: data/covar_corrected.cleaned_ici-myo-yes.vs.ici-myo-no_4.batches_myo.csv
Untracked: data/covar_corrected.cleaned_ici-myo-yes.vs.ici-myo-no_4.batches_myo_mis.csv
Untracked: data/covar_corrected.cleaned_ici-sick.vs.ici-eoi_4.batches_myo.csv
Untracked: data/covar_corrected.cleaned_ici-sick.vs.ici-eoi_4.batches_myo_mis.csv
Untracked: data/covar_corrected.cleaned_ici.vs.pbs_4.batches_myo.csv
Untracked: data/covar_corrected.cleaned_ici.vs.pbs_4.batches_myo_mis.csv
Untracked: data/covar_corrected.cleaned_myo-yes.vs.myo-no_4.batches_myo.csv
Untracked: data/covar_corrected.cleaned_myo-yes.vs.myo-no_4.batches_myo_mis.csv
Untracked: data/covar_corrected.cleaned_pbs-myo-yes.vs.pbs-myo-no_4.batches_myo.csv
Untracked: data/covar_corrected.cleaned_pbs-myo-yes.vs.pbs-myo-no_4.batches_myo_mis.csv
Untracked: data/covar_corrected_het-ici-myo-yes.vs.het-ici-myo-no_4.batches_myo.csv
Untracked: data/covar_corrected_het-ici-myo-yes.vs.het-ici-myo-no_4.batches_myo_mis.csv
Untracked: data/covar_corrected_het-ici.vs.het-pbs_4.batches_myo.csv
Untracked: data/covar_corrected_het-ici.vs.het-pbs_4.batches_myo_mis.csv
Untracked: data/covar_corrected_ici-myo-yes.vs.ici-myo-no_4.batches_myo.csv
Untracked: data/covar_corrected_ici-myo-yes.vs.ici-myo-no_4.batches_myo_mis.csv
Untracked: data/covar_corrected_ici-sick.vs.ici-eoi_4.batches_myo.csv
Untracked: data/covar_corrected_ici-sick.vs.ici-eoi_4.batches_myo_mis.csv
Untracked: data/covar_corrected_ici.vs.pbs_4.batches_myo.csv
Untracked: data/covar_corrected_ici.vs.pbs_4.batches_myo_mis.csv
Untracked: data/covar_corrected_myo-yes.vs.myo-no_4.batches_myo.csv
Untracked: data/covar_corrected_myo-yes.vs.myo-no_4.batches_myo_mis.csv
Untracked: data/covar_corrected_pbs-myo-yes.vs.pbs-myo-no_4.batches_myo.csv
Untracked: data/covar_corrected_pbs-myo-yes.vs.pbs-myo-no_4.batches_myo_mis.csv
Untracked: data/e_4.batches_myo.RData
Untracked: data/e_snpg_samqc_4.batches_myo.RData
Untracked: data/errors_ind_4.batches_myo.RData
Untracked: data/genetic_map_4.batches_myo.csv
Untracked: data/genotype_errors_marker_4.batches_myo.RData
Untracked: data/genotype_freq_marker_4.batches_myo.RData
Untracked: data/gm_allqc_4.batches_myo.RData
Untracked: data/gm_allqc_4.batches_myo_mis.RData
Untracked: data/gm_samqc_4.batches_myo.RData
Untracked: data/gm_serreze.BC312.RData
Untracked: data/het-ici-myo-yes.vs.het-ici-myo-no_marker.freq_low.geno.freq.removed_geno.ratio_4.batches_myo.csv
Untracked: data/het-ici-myo-yes.vs.het-ici-myo-no_marker.freq_low.geno.freq.removed_geno.ratio_4.batches_myo_mis.csv
Untracked: data/het-ici-myo-yes.vs.het-ici-myo-no_marker.freq_low.geno.freq.removed_sample.outliers.removed_geno.ratio_4.batches_myo.csv
Untracked: data/het-ici-myo-yes.vs.het-ici-myo-no_marker.freq_low.geno.freq.removed_sample.outliers.removed_geno.ratio_4.batches_myo_mis.csv
Untracked: data/het-ici-myo-yes.vs.het-ici-myo-no_marker.freq_low.geno.freq.removed_sample.outliers.removed_geno.ratiov_4.batches_myo.csv
Untracked: data/het-ici-myo-yes.vs.het-ici-myo-no_marker.freq_low.geno.freq.removed_sample.outliers.removed_geno.ratiov_4.batches_myo_mis.csv
Untracked: data/het-ici-myo-yes.vs.het-ici-myo-no_marker.freq_low.probs.freq.removed_geno.ratio_4.batches_myo.csv
Untracked: data/het-ici-myo-yes.vs.het-ici-myo-no_marker.freq_low.probs.freq.removed_geno.ratio_4.batches_myo_mis.csv
Untracked: data/het-ici-myo-yes.vs.het-ici-myo-no_marker.freq_low.probs.freq.removed_sample.outliers.removed_geno.ratio_4.batches_myo.csv
Untracked: data/het-ici-myo-yes.vs.het-ici-myo-no_marker.freq_low.probs.freq.removed_sample.outliers.removed_geno.ratio_4.batches_myo_mis.csv
Untracked: data/het-ici-myo-yes.vs.het-ici-myo-no_sample.genos_marker.freq_low.geno.freq.4.batches_myo.csv
Untracked: data/het-ici-myo-yes.vs.het-ici-myo-no_sample.genos_marker.freq_low.geno.freq.4.batches_myo_mis.csv
Untracked: data/het-ici-myo-yes.vs.het-ici-myo-no_sample.genos_marker.freq_low.geno.freq.removed.csv
Untracked: data/het-ici-myo-yes.vs.het-ici-myo-no_sample.genos_marker.freq_low.geno.freq.removed_4.batches_myo.csv
Untracked: data/het-ici-myo-yes.vs.het-ici-myo-no_sample.genos_marker.freq_low.geno.freq.removed_4.batches_myo_mis.csv
Untracked: data/het-ici-myo-yes.vs.het-ici-myo-no_sample.genos_marker.freq_low.geno.freq.removed_sample.outliers.4.batches_myo.csv
Untracked: data/het-ici-myo-yes.vs.het-ici-myo-no_sample.genos_marker.freq_low.geno.freq.removed_sample.outliers.4.batches_myo_mis.csv
Untracked: data/het-ici-myo-yes.vs.het-ici-myo-no_sample.genos_marker.freq_low.geno.freq.removed_sample.outliers.removed.csv
Untracked: data/het-ici-myo-yes.vs.het-ici-myo-no_sample.genos_marker.freq_low.geno.freq.removed_sample.outliers.removed_4.batches_myo.csv
Untracked: data/het-ici-myo-yes.vs.het-ici-myo-no_sample.genos_marker.freq_low.geno.freq.removed_sample.outliers.removed_4.batches_myo_mis.csv
Untracked: data/het-ici-myo-yes.vs.het-ici-myo-no_sample.genos_marker.freq_low.probs.freq.4.batches_myo.csv
Untracked: data/het-ici-myo-yes.vs.het-ici-myo-no_sample.genos_marker.freq_low.probs.freq.4.batches_myo_mis.csv
Untracked: data/het-ici-myo-yes.vs.het-ici-myo-no_sample.genos_marker.freq_low.probs.freq.removed.csv
Untracked: data/het-ici-myo-yes.vs.het-ici-myo-no_sample.genos_marker.freq_low.probs.freq.removed_4.batches_myo.csv
Untracked: data/het-ici-myo-yes.vs.het-ici-myo-no_sample.genos_marker.freq_low.probs.freq.removed_4.batches_myo_mis.csv
Untracked: data/het-ici-myo-yes.vs.het-ici-myo-no_sample.genos_marker.freq_low.probs.freq.removed_sample.outliers.4.batches_myo.csv
Untracked: data/het-ici-myo-yes.vs.het-ici-myo-no_sample.genos_marker.freq_low.probs.freq.removed_sample.outliers.4.batches_myo_mis.csv
Untracked: data/het-ici-myo-yes.vs.het-ici-myo-no_sample.genos_marker.freq_low.probs.freq.removed_sample.outliers.removed.csv
Untracked: data/het-ici-myo-yes.vs.het-ici-myo-no_sample.genos_marker.freq_low.probs.freq.removed_sample.outliers.removed_4.batches_myo.csv
Untracked: data/het-ici-myo-yes.vs.het-ici-myo-no_sample.genos_marker.freq_low.probs.freq.removed_sample.outliers.removed_4.batches_myo_mis.csv
Untracked: data/het-ici.vs.het-pbs_marker.freq_low.geno.freq.removed_geno.ratio_4.batches_myo.csv
Untracked: data/het-ici.vs.het-pbs_marker.freq_low.geno.freq.removed_geno.ratio_4.batches_myo_mis.csv
Untracked: data/het-ici.vs.het-pbs_marker.freq_low.geno.freq.removed_sample.outliers.removed_geno.ratio_4.batches_myo.csv
Untracked: data/het-ici.vs.het-pbs_marker.freq_low.geno.freq.removed_sample.outliers.removed_geno.ratio_4.batches_myo_mis.csv
Untracked: data/het-ici.vs.het-pbs_marker.freq_low.geno.freq.removed_sample.outliers.removed_geno.ratiov_4.batches_myo.csv
Untracked: data/het-ici.vs.het-pbs_marker.freq_low.geno.freq.removed_sample.outliers.removed_geno.ratiov_4.batches_myo_mis.csv
Untracked: data/het-ici.vs.het-pbs_marker.freq_low.probs.freq.removed_geno.ratio_4.batches_myo.csv
Untracked: data/het-ici.vs.het-pbs_marker.freq_low.probs.freq.removed_geno.ratio_4.batches_myo_mis.csv
Untracked: data/het-ici.vs.het-pbs_marker.freq_low.probs.freq.removed_sample.outliers.removed_geno.ratio_4.batches_myo.csv
Untracked: data/het-ici.vs.het-pbs_marker.freq_low.probs.freq.removed_sample.outliers.removed_geno.ratio_4.batches_myo_mis.csv
Untracked: data/het-ici.vs.het-pbs_sample.genos_marker.freq_low.geno.freq.4.batches_myo.csv
Untracked: data/het-ici.vs.het-pbs_sample.genos_marker.freq_low.geno.freq.4.batches_myo_mis.csv
Untracked: data/het-ici.vs.het-pbs_sample.genos_marker.freq_low.geno.freq.removed.csv
Untracked: data/het-ici.vs.het-pbs_sample.genos_marker.freq_low.geno.freq.removed_4.batches_myo.csv
Untracked: data/het-ici.vs.het-pbs_sample.genos_marker.freq_low.geno.freq.removed_4.batches_myo_mis.csv
Untracked: data/het-ici.vs.het-pbs_sample.genos_marker.freq_low.geno.freq.removed_sample.outliers.4.batches_myo.csv
Untracked: data/het-ici.vs.het-pbs_sample.genos_marker.freq_low.geno.freq.removed_sample.outliers.4.batches_myo_mis.csv
Untracked: data/het-ici.vs.het-pbs_sample.genos_marker.freq_low.geno.freq.removed_sample.outliers.removed.csv
Untracked: data/het-ici.vs.het-pbs_sample.genos_marker.freq_low.geno.freq.removed_sample.outliers.removed_4.batches_myo.csv
Untracked: data/het-ici.vs.het-pbs_sample.genos_marker.freq_low.geno.freq.removed_sample.outliers.removed_4.batches_myo_mis.csv
Untracked: data/het-ici.vs.het-pbs_sample.genos_marker.freq_low.probs.freq.4.batches_myo.csv
Untracked: data/het-ici.vs.het-pbs_sample.genos_marker.freq_low.probs.freq.4.batches_myo_mis.csv
Untracked: data/het-ici.vs.het-pbs_sample.genos_marker.freq_low.probs.freq.removed.csv
Untracked: data/het-ici.vs.het-pbs_sample.genos_marker.freq_low.probs.freq.removed_4.batches_myo.csv
Untracked: data/het-ici.vs.het-pbs_sample.genos_marker.freq_low.probs.freq.removed_4.batches_myo_mis.csv
Untracked: data/het-ici.vs.het-pbs_sample.genos_marker.freq_low.probs.freq.removed_sample.outliers.4.batches_myo.csv
Untracked: data/het-ici.vs.het-pbs_sample.genos_marker.freq_low.probs.freq.removed_sample.outliers.4.batches_myo_mis.csv
Untracked: data/het-ici.vs.het-pbs_sample.genos_marker.freq_low.probs.freq.removed_sample.outliers.removed.csv
Untracked: data/het-ici.vs.het-pbs_sample.genos_marker.freq_low.probs.freq.removed_sample.outliers.removed_4.batches_myo.csv
Untracked: data/het-ici.vs.het-pbs_sample.genos_marker.freq_low.probs.freq.removed_sample.outliers.removed_4.batches_myo_mis.csv
Untracked: data/ici-myo-yes.vs.ici-myo-no_marker.freq_low.geno.freq.removed_geno.ratio_4.batches_myo.csv
Untracked: data/ici-myo-yes.vs.ici-myo-no_marker.freq_low.geno.freq.removed_geno.ratio_4.batches_myo_mis.csv
Untracked: data/ici-myo-yes.vs.ici-myo-no_marker.freq_low.geno.freq.removed_sample.outliers.removed_geno.ratio_4.batches_myo_mis.csv
Untracked: data/ici-myo-yes.vs.ici-myo-no_marker.freq_low.geno.freq.removed_sample.outliers.removed_geno.ratiov_4.batches_myo.csv
Untracked: data/ici-myo-yes.vs.ici-myo-no_marker.freq_low.geno.freq.removed_sample.outliers.removed_geno.ratiov_4.batches_myo_mis.csv
Untracked: data/ici-myo-yes.vs.ici-myo-no_marker.freq_low.probs.freq.removed_geno.ratio_4.batches_myo.csv
Untracked: data/ici-myo-yes.vs.ici-myo-no_marker.freq_low.probs.freq.removed_geno.ratio_4.batches_myo_mis.csv
Untracked: data/ici-myo-yes.vs.ici-myo-no_marker.freq_low.probs.freq.removed_sample.outliers.removed_geno.ratio_4.batches_myo.csv
Untracked: data/ici-myo-yes.vs.ici-myo-no_marker.freq_low.probs.freq.removed_sample.outliers.removed_geno.ratio_4.batches_myo_mis.csv
Untracked: data/ici-myo-yes.vs.ici-myo-no_sample.genos_marker.freq_low.geno.freq.4.batches_myo.csv
Untracked: data/ici-myo-yes.vs.ici-myo-no_sample.genos_marker.freq_low.geno.freq.4.batches_myo_mis.csv
Untracked: data/ici-myo-yes.vs.ici-myo-no_sample.genos_marker.freq_low.geno.freq.removed.csv
Untracked: data/ici-myo-yes.vs.ici-myo-no_sample.genos_marker.freq_low.geno.freq.removed_4.batches_myo_mis.csv
Untracked: data/ici-myo-yes.vs.ici-myo-no_sample.genos_marker.freq_low.geno.freq.removed_sample.outliers.4.batches_myo.csv
Untracked: data/ici-myo-yes.vs.ici-myo-no_sample.genos_marker.freq_low.geno.freq.removed_sample.outliers.4.batches_myo_mis.csv
Untracked: data/ici-myo-yes.vs.ici-myo-no_sample.genos_marker.freq_low.geno.freq.removed_sample.outliers.removed.csv
Untracked: data/ici-myo-yes.vs.ici-myo-no_sample.genos_marker.freq_low.geno.freq.removed_sample.outliers.removed_4.batches_myo_mis.csv
Untracked: data/ici-myo-yes.vs.ici-myo-no_sample.genos_marker.freq_low.probs.freq.4.batches_myo.csv
Untracked: data/ici-myo-yes.vs.ici-myo-no_sample.genos_marker.freq_low.probs.freq.4.batches_myo_mis.csv
Untracked: data/ici-myo-yes.vs.ici-myo-no_sample.genos_marker.freq_low.probs.freq.removed.csv
Untracked: data/ici-myo-yes.vs.ici-myo-no_sample.genos_marker.freq_low.probs.freq.removed_4.batches_myo_mis.csv
Untracked: data/ici-myo-yes.vs.ici-myo-no_sample.genos_marker.freq_low.probs.freq.removed_sample.outliers.4.batches_myo.csv
Untracked: data/ici-myo-yes.vs.ici-myo-no_sample.genos_marker.freq_low.probs.freq.removed_sample.outliers.4.batches_myo_mis.csv
Untracked: data/ici-myo-yes.vs.ici-myo-no_sample.genos_marker.freq_low.probs.freq.removed_sample.outliers.removed.csv
Untracked: data/ici-myo-yes.vs.ici-myo-no_sample.genos_marker.freq_low.probs.freq.removed_sample.outliers.removed_4.batches_myo_mis.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-10_peak.marker-UNC18805053_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-10_peak.marker-UNCHS029427_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-11_peak.marker-UNCHS031753_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-11_peak.marker-UNCHS031802_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-12_peak.marker-JAX00326005_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-12_peak.marker-UNC21995304_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-13_peak.marker-JAX00370189_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-13_peak.marker-UNCHS035661_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-14_peak.marker-UNC24597582_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-14_peak.marker-UNCHS039096_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-15_peak.marker-UNC25489755_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-15_peak.marker-UNCHS040614_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-16_peak.marker-UNCHS042686_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-17_peak.marker-UNCHS043777_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-17_peak.marker-UNCHS043880_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-18_peak.marker-UNC29296831_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-18_peak.marker-UNC29297751_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-19_peak.marker-UNC30069852_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-19_peak.marker-UNC30386742_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-1_peak.marker-UNCHS001121_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-1_peak.marker-UNCHS002308_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-2_peak.marker-UNC3990359_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-2_peak.marker-UNCHS006135_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-3_peak.marker-JAX00105915_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-3_peak.marker-UNC6020011_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-4_peak.marker-UNC8099452_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-4_peak.marker-UNC8161950_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-5_peak.marker-UNC9678100_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-5_peak.marker-UNC9678931_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-6_peak.marker-UNC12162881_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-6_peak.marker-backupUNC060363218_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-7_peak.marker-UNC12719038_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-7_peak.marker-UNCHS022024_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-8_peak.marker-UNC14948439_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-8_peak.marker-UNCHS023592_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-9_peak.marker-UNC16009822_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-9_peak.marker-UNC17271730_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-X_peak.marker-UNC31358512_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_blup_sub_chr-X_peak.marker-UNCHS049472_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-10_peak.marker-UNC18805053_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-10_peak.marker-UNCHS029427_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-11_peak.marker-UNCHS031753_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-11_peak.marker-UNCHS031802_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-12_peak.marker-JAX00326005_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-12_peak.marker-UNC21995304_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-13_peak.marker-JAX00370189_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-13_peak.marker-UNCHS035661_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-14_peak.marker-UNC24597582_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-14_peak.marker-UNCHS039096_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-15_peak.marker-UNC25489755_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-15_peak.marker-UNCHS040614_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-16_peak.marker-UNCHS042686_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-17_peak.marker-UNCHS043777_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-17_peak.marker-UNCHS043880_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-18_peak.marker-UNC29296831_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-18_peak.marker-UNC29297751_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-19_peak.marker-UNC30069852_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-19_peak.marker-UNC30386742_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-1_peak.marker-UNCHS001121_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-1_peak.marker-UNCHS002308_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-2_peak.marker-UNC3990359_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-2_peak.marker-UNCHS006135_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-3_peak.marker-JAX00105915_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-3_peak.marker-UNC6020011_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-4_peak.marker-UNC8099452_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-4_peak.marker-UNC8161950_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-5_peak.marker-UNC9678100_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-5_peak.marker-UNC9678931_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-6_peak.marker-UNC12162881_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-6_peak.marker-backupUNC060363218_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-7_peak.marker-UNC12719038_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-7_peak.marker-UNCHS022024_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-8_peak.marker-UNC14948439_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-8_peak.marker-UNCHS023592_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-9_peak.marker-UNC16009822_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-9_peak.marker-UNC17271730_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-X_peak.marker-UNC31358512_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_genes_chr-X_peak.marker-UNCHS049472_lod.drop-1.5_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_gm_qtl_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_marker.freq_low.geno.freq.removed_geno.ratio_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_marker.freq_low.geno.freq.removed_geno.ratio_4.batches_myo_mis.csv
Untracked: data/ici-sick.vs.ici-eoi_marker.freq_low.geno.freq.removed_sample.outliers.removed_geno.ratio_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_marker.freq_low.geno.freq.removed_sample.outliers.removed_geno.ratio_4.batches_myo_mis.csv
Untracked: data/ici-sick.vs.ici-eoi_marker.freq_low.geno.freq.removed_sample.outliers.removed_geno.ratiov_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_marker.freq_low.geno.freq.removed_sample.outliers.removed_geno.ratiov_4.batches_myo_mis.csv
Untracked: data/ici-sick.vs.ici-eoi_marker.freq_low.probs.freq.removed_geno.ratio_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_marker.freq_low.probs.freq.removed_geno.ratio_4.batches_myo_mis.csv
Untracked: data/ici-sick.vs.ici-eoi_marker.freq_low.probs.freq.removed_sample.outliers.removed_geno.ratio_4.batches_myo.csv
Untracked: data/ici-sick.vs.ici-eoi_marker.freq_low.probs.freq.removed_sample.outliers.removed_geno.ratio_4.batches_myo_mis.csv
Untracked: data/ici-sick.vs.ici-eoi_sample.genos_marker.freq_low.geno.freq.4.batches_myo_mis.csv
Untracked: data/ici-sick.vs.ici-eoi_sample.genos_marker.freq_low.geno.freq.removed.csv
Untracked: data/ici-sick.vs.ici-eoi_sample.genos_marker.freq_low.geno.freq.removed_4.batches_myo_mis.csv
Untracked: data/ici-sick.vs.ici-eoi_sample.genos_marker.freq_low.geno.freq.removed_sample.outliers.4.batches_myo_mis.csv
Untracked: data/ici-sick.vs.ici-eoi_sample.genos_marker.freq_low.geno.freq.removed_sample.outliers.removed.csv
Untracked: data/ici-sick.vs.ici-eoi_sample.genos_marker.freq_low.geno.freq.removed_sample.outliers.removed_4.batches_myo_mis.csv
Untracked: data/ici-sick.vs.ici-eoi_sample.genos_marker.freq_low.probs.freq.4.batches_myo_mis.csv
Untracked: data/ici-sick.vs.ici-eoi_sample.genos_marker.freq_low.probs.freq.removed.csv
Untracked: data/ici-sick.vs.ici-eoi_sample.genos_marker.freq_low.probs.freq.removed_4.batches_myo_mis.csv
Untracked: data/ici-sick.vs.ici-eoi_sample.genos_marker.freq_low.probs.freq.removed_sample.outliers.4.batches_myo_mis.csv
Untracked: data/ici-sick.vs.ici-eoi_sample.genos_marker.freq_low.probs.freq.removed_sample.outliers.removed.csv
Untracked: data/ici-sick.vs.ici-eoi_sample.genos_marker.freq_low.probs.freq.removed_sample.outliers.removed_4.batches_myo_mis.csv
Untracked: data/ici.vs.pbs_gm_qtl_snpsqc_dis_no-x_updated_4.batches_myo.csv
Untracked: data/ici.vs.pbs_marker.freq_low.geno.freq.removed_geno.ratio_4.batches_myo.csv
Untracked: data/ici.vs.pbs_marker.freq_low.geno.freq.removed_geno.ratio_4.batches_myo_mis.csv
Untracked: data/ici.vs.pbs_marker.freq_low.geno.freq.removed_sample.outliers.removed_geno.ratio_4.batches_myo.csv
Untracked: data/ici.vs.pbs_marker.freq_low.geno.freq.removed_sample.outliers.removed_geno.ratio_4.batches_myo_mis.csv
Untracked: data/ici.vs.pbs_marker.freq_low.geno.freq.removed_sample.outliers.removed_geno.ratiov_4.batches_myo.csv
Untracked: data/ici.vs.pbs_marker.freq_low.geno.freq.removed_sample.outliers.removed_geno.ratiov_4.batches_myo_mis.csv
Untracked: data/ici.vs.pbs_marker.freq_low.probs.freq.removed_geno.ratio_4.batches_myo.csv
Untracked: data/ici.vs.pbs_marker.freq_low.probs.freq.removed_geno.ratio_4.batches_myo_mis.csv
Untracked: data/ici.vs.pbs_marker.freq_low.probs.freq.removed_sample.outliers.removed_geno.ratio_4.batches_myo.csv
Untracked: data/ici.vs.pbs_marker.freq_low.probs.freq.removed_sample.outliers.removed_geno.ratio_4.batches_myo_mis.csv
Untracked: data/ici.vs.pbs_sample.genos_marker.freq_low.geno.freq.4.batches_myo.csv
Untracked: data/ici.vs.pbs_sample.genos_marker.freq_low.geno.freq.4.batches_myo_mis.csv
Untracked: data/ici.vs.pbs_sample.genos_marker.freq_low.geno.freq.removed.csv
Untracked: data/ici.vs.pbs_sample.genos_marker.freq_low.geno.freq.removed_4.batches_myo_mis.csv
Untracked: data/ici.vs.pbs_sample.genos_marker.freq_low.geno.freq.removed_sample.outliers.4.batches_myo.csv
Untracked: data/ici.vs.pbs_sample.genos_marker.freq_low.geno.freq.removed_sample.outliers.4.batches_myo_mis.csv
Untracked: data/ici.vs.pbs_sample.genos_marker.freq_low.geno.freq.removed_sample.outliers.removed.csv
Untracked: data/ici.vs.pbs_sample.genos_marker.freq_low.geno.freq.removed_sample.outliers.removed_4.batches_myo_mis.csv
Untracked: data/ici.vs.pbs_sample.genos_marker.freq_low.probs.freq.4.batches_myo.csv
Untracked: data/ici.vs.pbs_sample.genos_marker.freq_low.probs.freq.4.batches_myo_mis.csv
Untracked: data/ici.vs.pbs_sample.genos_marker.freq_low.probs.freq.removed.csv
Untracked: data/ici.vs.pbs_sample.genos_marker.freq_low.probs.freq.removed_4.batches_myo_mis.csv
Untracked: data/ici.vs.pbs_sample.genos_marker.freq_low.probs.freq.removed_sample.outliers.4.batches_myo.csv
Untracked: data/ici.vs.pbs_sample.genos_marker.freq_low.probs.freq.removed_sample.outliers.4.batches_myo_mis.csv
Untracked: data/ici.vs.pbs_sample.genos_marker.freq_low.probs.freq.removed_sample.outliers.removed.csv
Untracked: data/ici.vs.pbs_sample.genos_marker.freq_low.probs.freq.removed_sample.outliers.removed_4.batches_myo_mis.csv
Untracked: data/myo-yes.vs.myo-no_marker.freq_low.geno.freq.removed_geno.ratio_4.batches_myo.csv
Untracked: data/myo-yes.vs.myo-no_marker.freq_low.geno.freq.removed_geno.ratio_4.batches_myo_mis.csv
Untracked: data/myo-yes.vs.myo-no_marker.freq_low.geno.freq.removed_sample.outliers.removed_geno.ratio_4.batches_myo.csv
Untracked: data/myo-yes.vs.myo-no_marker.freq_low.geno.freq.removed_sample.outliers.removed_geno.ratio_4.batches_myo_mis.csv
Untracked: data/myo-yes.vs.myo-no_marker.freq_low.geno.freq.removed_sample.outliers.removed_geno.ratiov_4.batches_myo.csv
Untracked: data/myo-yes.vs.myo-no_marker.freq_low.geno.freq.removed_sample.outliers.removed_geno.ratiov_4.batches_myo_mis.csv
Untracked: data/myo-yes.vs.myo-no_marker.freq_low.probs.freq.removed_geno.ratio_4.batches_myo.csv
Untracked: data/myo-yes.vs.myo-no_marker.freq_low.probs.freq.removed_geno.ratio_4.batches_myo_mis.csv
Untracked: data/myo-yes.vs.myo-no_marker.freq_low.probs.freq.removed_sample.outliers.removed_geno.ratio_4.batches_myo.csv
Untracked: data/myo-yes.vs.myo-no_marker.freq_low.probs.freq.removed_sample.outliers.removed_geno.ratio_4.batches_myo_mis.csv
Untracked: data/myo-yes.vs.myo-no_sample.genos_marker.freq_low.geno.freq.4.batches_myo.csv
Untracked: data/myo-yes.vs.myo-no_sample.genos_marker.freq_low.geno.freq.4.batches_myo_mis.csv
Untracked: data/myo-yes.vs.myo-no_sample.genos_marker.freq_low.geno.freq.removed.csv
Untracked: data/myo-yes.vs.myo-no_sample.genos_marker.freq_low.geno.freq.removed_4.batches_myo.csv
Untracked: data/myo-yes.vs.myo-no_sample.genos_marker.freq_low.geno.freq.removed_4.batches_myo_mis.csv
Untracked: data/myo-yes.vs.myo-no_sample.genos_marker.freq_low.geno.freq.removed_sample.outliers.4.batches_myo.csv
Untracked: data/myo-yes.vs.myo-no_sample.genos_marker.freq_low.geno.freq.removed_sample.outliers.4.batches_myo_mis.csv
Untracked: data/myo-yes.vs.myo-no_sample.genos_marker.freq_low.geno.freq.removed_sample.outliers.removed.csv
Untracked: data/myo-yes.vs.myo-no_sample.genos_marker.freq_low.geno.freq.removed_sample.outliers.removed_4.batches_myo.csv
Untracked: data/myo-yes.vs.myo-no_sample.genos_marker.freq_low.geno.freq.removed_sample.outliers.removed_4.batches_myo_mis.csv
Untracked: data/myo-yes.vs.myo-no_sample.genos_marker.freq_low.probs.freq.4.batches_myo.csv
Untracked: data/myo-yes.vs.myo-no_sample.genos_marker.freq_low.probs.freq.4.batches_myo_mis.csv
Untracked: data/myo-yes.vs.myo-no_sample.genos_marker.freq_low.probs.freq.removed.csv
Untracked: data/myo-yes.vs.myo-no_sample.genos_marker.freq_low.probs.freq.removed_4.batches_myo.csv
Untracked: data/myo-yes.vs.myo-no_sample.genos_marker.freq_low.probs.freq.removed_4.batches_myo_mis.csv
Untracked: data/myo-yes.vs.myo-no_sample.genos_marker.freq_low.probs.freq.removed_sample.outliers.4.batches_myo.csv
Untracked: data/myo-yes.vs.myo-no_sample.genos_marker.freq_low.probs.freq.removed_sample.outliers.4.batches_myo_mis.csv
Untracked: data/myo-yes.vs.myo-no_sample.genos_marker.freq_low.probs.freq.removed_sample.outliers.removed.csv
Untracked: data/myo-yes.vs.myo-no_sample.genos_marker.freq_low.probs.freq.removed_sample.outliers.removed_4.batches_myo.csv
Untracked: data/myo-yes.vs.myo-no_sample.genos_marker.freq_low.probs.freq.removed_sample.outliers.removed_4.batches_myo_mis.csv
Untracked: data/pbs-myo-yes.vs.pbs-myo-no_marker.freq_low.geno.freq.removed_geno.ratio_4.batches_myo.csv
Untracked: data/pbs-myo-yes.vs.pbs-myo-no_marker.freq_low.geno.freq.removed_geno.ratio_4.batches_myo_mis.csv
Untracked: data/pbs-myo-yes.vs.pbs-myo-no_marker.freq_low.geno.freq.removed_sample.outliers.removed_geno.ratio_4.batches_myo.csv
Untracked: data/pbs-myo-yes.vs.pbs-myo-no_marker.freq_low.geno.freq.removed_sample.outliers.removed_geno.ratio_4.batches_myo1.csv
Untracked: data/pbs-myo-yes.vs.pbs-myo-no_marker.freq_low.geno.freq.removed_sample.outliers.removed_geno.ratio_4.batches_myo_mis.csv
Untracked: data/pbs-myo-yes.vs.pbs-myo-no_marker.freq_low.geno.freq.removed_sample.outliers.removed_geno.ratio_4.batches_myo_mis1.csv
Untracked: data/pbs-myo-yes.vs.pbs-myo-no_marker.freq_low.probs.freq.removed_geno.ratio_4.batches_myo.csv
Untracked: data/pbs-myo-yes.vs.pbs-myo-no_marker.freq_low.probs.freq.removed_geno.ratio_4.batches_myo_mis.csv
Untracked: data/pbs-myo-yes.vs.pbs-myo-no_marker.freq_low.probs.freq.removed_sample.outliers.removed_geno.ratio_4.batches_myo.csv
Untracked: data/pbs-myo-yes.vs.pbs-myo-no_marker.freq_low.probs.freq.removed_sample.outliers.removed_geno.ratio_4.batches_myo_mis.csv
Untracked: data/pbs-myo-yes.vs.pbs-myo-no_sample.genos_marker.freq_low.geno.freq.4.batches_myo.csv
Untracked: data/pbs-myo-yes.vs.pbs-myo-no_sample.genos_marker.freq_low.geno.freq.4.batches_myo_mis.csv
Untracked: data/pbs-myo-yes.vs.pbs-myo-no_sample.genos_marker.freq_low.geno.freq.removed.csv
Untracked: data/pbs-myo-yes.vs.pbs-myo-no_sample.genos_marker.freq_low.geno.freq.removed_4.batches_myo_mis.csv
Untracked: data/pbs-myo-yes.vs.pbs-myo-no_sample.genos_marker.freq_low.geno.freq.removed_sample.outliers.4.batches_myo.csv
Untracked: data/pbs-myo-yes.vs.pbs-myo-no_sample.genos_marker.freq_low.geno.freq.removed_sample.outliers.4.batches_myo_mis.csv
Untracked: data/pbs-myo-yes.vs.pbs-myo-no_sample.genos_marker.freq_low.geno.freq.removed_sample.outliers.removed.csv
Untracked: data/pbs-myo-yes.vs.pbs-myo-no_sample.genos_marker.freq_low.geno.freq.removed_sample.outliers.removed_4.batches_myo_mis.csv
Untracked: data/pbs-myo-yes.vs.pbs-myo-no_sample.genos_marker.freq_low.probs.freq.4.batches_myo.csv
Untracked: data/pbs-myo-yes.vs.pbs-myo-no_sample.genos_marker.freq_low.probs.freq.4.batches_myo_mis.csv
Untracked: data/pbs-myo-yes.vs.pbs-myo-no_sample.genos_marker.freq_low.probs.freq.removed.csv
Untracked: data/pbs-myo-yes.vs.pbs-myo-no_sample.genos_marker.freq_low.probs.freq.removed_4.batches_myo_mis.csv
Untracked: data/pbs-myo-yes.vs.pbs-myo-no_sample.genos_marker.freq_low.probs.freq.removed_sample.outliers.4.batches_myo.csv
Untracked: data/pbs-myo-yes.vs.pbs-myo-no_sample.genos_marker.freq_low.probs.freq.removed_sample.outliers.4.batches_myo_mis.csv
Untracked: data/pbs-myo-yes.vs.pbs-myo-no_sample.genos_marker.freq_low.probs.freq.removed_sample.outliers.removed.csv
Untracked: data/pbs-myo-yes.vs.pbs-myo-no_sample.genos_marker.freq_low.probs.freq.removed_sample.outliers.removed_4.batches_myo_mis.csv
Untracked: data/percent_missing_id_4.batches_myo.RData
Untracked: data/percent_missing_marker_4.batches_myo.RData
Untracked: data/pheno_4.batches_myo.csv
Untracked: data/physical_map_4.batches_myo.csv
Untracked: data/qc_info_bad_sample_4.batches_myo.RData
Untracked: data/sample_geno_AHB_4.batches_myo.csv
Untracked: data/sample_geno_bc_4.batches_myo.csv
Untracked: data/serreze_probs_4.batches_myo.rds
Untracked: data/serreze_probs_allqc_4.batches_myo.rds
Untracked: data/serreze_probs_allqc_4.batches_myo_mis.rds
Untracked: data/summary.cg_4.batches_myo.RData
Untracked: output/Percent_missing_genotype_data_4.batches_myo.pdf
Untracked: output/Percent_missing_genotype_data_per_marker_4.batches_myo.pdf
Untracked: output/Proportion_matching_genotypes_before_removal_of_bad_samples_4.batches_myo.pdf
Untracked: output/genotype_error_marker_4.batches_myo.pdf
Untracked: output/genotype_frequency_marker_4.batches_myo.pdf
Unstaged changes:
Modified: analysis/index_5.batches.Rmd
Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.
There are no past versions. Publish this analysis with
wflow_publish() to start tracking its development.
load("data/gm_allqc_4.batches_myo.RData")
#gm_allqc
gm=gm_allqc
gmObject of class cross2 (crosstype "bc")
Total individuals 208
No. genotyped individuals 208
No. phenotyped individuals 208
No. with both geno & pheno 208
No. phenotypes 1
No. covariates 11
No. phenotype covariates 0
No. chromosomes 20
Total markers 32610
No. markers by chr:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
2498 2407 1748 1770 1649 1835 1544 1515 1773 1102 1744 1214 1442 1497 1109 835
17 18 19 X
674 813 940 4501 pr <- readRDS("data/serreze_probs_allqc_4.batches_myo.rds")
#pr <- readRDS("data/serreze_probs.rds")
geno <- read.csv("/Users/corneb/Documents/MyJax/CS/Projects/Serreze/haplotype.reconstruction/output_4.batches_myo_corrected/sample_geno_bc_4.batches_myo_BC217.csv", as.is=T)
names(geno) <- gsub("^X","",names(geno))
names(geno) <- gsub("\\.","-",names(geno))
rownames(geno) <- geno$marker## extracting animals with ici and pbs group status
#miceinfo <- gm$covar[gm$covar$group == "PBS" | gm$covar$group == "ICI",]
#table(miceinfo$group)
#mice.ids <- rownames(miceinfo)
#gm <- gm[mice.ids]
#gm
#table(gm$covar$group)
covars <- read_csv("data/covar_corrected_pbs-myo-yes.vs.pbs-myo-no_4.batches_myo.csv")
# removing any missing info
#covars <- subset(covars, covars$age.of.onset!='')
nrow(covars)[1] 58table(covars$"Myocarditis Status")
NO YES
13 45 table(covars$"Murine MHC KO Status")
HOM
58 table(covars$"Drug Treatment")
PBS
58 table(covars$"clinical pheno")
EOI SICK
39 19 # keeping only informative mice
gm <- gm[covars$Mouse.ID]
gmObject of class cross2 (crosstype "bc")
Total individuals 58
No. genotyped individuals 58
No. phenotyped individuals 58
No. with both geno & pheno 58
No. phenotypes 1
No. covariates 11
No. phenotype covariates 0
No. chromosomes 20
Total markers 32610
No. markers by chr:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
2498 2407 1748 1770 1649 1835 1544 1515 1773 1102 1744 1214 1442 1497 1109 835
17 18 19 X
674 813 940 4501 table(gm$covar$"Myocarditis Status")
NO YES
13 45 table(gm$covar$"Murine MHC KO Status")
HOM
58 table(gm$covar$"Drug Treatment")
PBS
58 table(gm$covar$"clinical pheno")
EOI SICK
39 19 pr.qc.ids <- pr
for (i in 1:20){pr.qc.ids[[i]] = pr.qc.ids[[i]][covars$Mouse.ID,,]}
geno <- geno[,covars$Mouse.ID]
geno <- geno[marker_names(gm),]
dim(geno)[1] 32610 58## calculating genotype frequencies
### from geno genotypes
g <- do.call("cbind", gm$geno)
gf_mar_geno <- t(apply(g, 2, function(a) table(factor(a, 1:2))/sum(a != 0)))
gn_mar_geno <- t(apply(g, 2, function(a) table(factor(a, 0:2))))
#gf_mar_raw<- gf_mar_raw[gf_mar_raw[,2] != "NaN",]
colnames(gf_mar_geno) <- c("freq_AA_geno_table","freq_AB_geno_table")
colnames(gn_mar_geno) <- c("count_missing_geno_table","count_AA_geno_table","count_AB_geno_table")
gfn_mar_geno <- merge(as.data.frame(gn_mar_geno), as.data.frame(gf_mar_geno), by="row.names")
rownames(gfn_mar_geno) <- gfn_mar_geno[,1]
gfn_mar_geno <- gfn_mar_geno[-1]
### from raw using table function in R
#genosl <- list()
#for(i in 1:nrow(geno)){
##for(i in 1:3){
# genoi <- geno[i,]
# freqf <- table(factor(geno[i,], c("-","AA","AB")))
# genoi$count_AA_raw_rowSums <- rowSums(genoi == "AA")
# genoi$count_AB_raw_rowSums <- rowSums(genoi == "AB")
# genoi$count_missing_raw_rowSums <- rowSums(genoi == "-")
# freqf <- t(table(factor(geno[i,], c("-","AA","AB"))))
# freqf <- as.data.frame(t(freqf[1,]))
# rownames(freqf) <- rownames(genoi)
# colnames(freqf) <- c("count_missing_raw_table","count_AA_raw_table","count_AB_raw_table")
# genoif <- cbind(freqf,genoi[c("count_AA_raw_rowSums","count_AB_raw_rowSums","count_missing_raw_rowSums")])
# genosl[[i]] = genoif
#}
#gf_mar_raw <- do.call("rbind",genosl)
#gf_mar_raw <- gf_mar_raw[,c(1:3,6,4:5)]
#gf_mar_raw$index <- 1:nrow(gf_mar_raw)
### from probabilities
gf_mar_probs.1 <- calc_geno_freq(pr.qc.ids, by = "marker", omit_x = FALSE)
#gn_mar_probs <- calc_geno_freq(probs, by = "individual", omit_x = FALSE)
gf_mar_probs <- rbind(gf_mar_probs.1$A[,1:2], gf_mar_probs.1$X[,1:2])
colnames(gf_mar_probs) <- paste0("freq_",colnames(gf_mar_probs),"_probs")
gf_mar_probs <- as.data.frame(gf_mar_probs)
gf_mar_probs$index <- 1:nrow(gf_mar_probs)
### merging all genotype frequecies for all markers
#gf_mar.1 <- merge(as.data.frame(gf_mar_raw), as.data.frame(gfn_mar_geno), by="row.names")
#rownames(gf_mar.1) <- gf_mar.1[,1]
#gf_mar.1 <- gf_mar.1[-1]
#gf_mar <- merge(gf_mar.1,as.data.frame(gf_mar_probs), by="row.names")
gf_mar <- merge(as.data.frame(gfn_mar_geno),as.data.frame(gf_mar_probs), by="row.names")
rownames(gf_mar) <- gf_mar[,1]
gf_mar <- gf_mar[-1]
gf_mar <- gf_mar[order(gf_mar$index),]
dim(gf_mar)[1] 32610 8# Calculating ratio and flagging informative marker
gf_mar$ratio = as.numeric(gf_mar$freq_AA_geno_table)/as.numeric(gf_mar$freq_AB_geno_table)
gf_mar$Include = ifelse(gf_mar$ratio >= 0.90 & gf_mar$ratio <= 1.10, TRUE,FALSE)
table(gf_mar$Include)
FALSE TRUE
27478 5132 ## filtering out <= 0.05
gf_mar$count.geno <- rowSums(gf_mar[c("freq_AA_geno_table","freq_AB_geno_table")] <=0.05)
filtered_gf_mar_geno <- gf_mar[gf_mar$count.geno != 1,]
filtered_gf_mar_geno <- filtered_gf_mar_geno[,-which(names(filtered_gf_mar_geno) %in% c("count.geno","index"))]
dim(filtered_gf_mar_geno)[1] 26753 9table(filtered_gf_mar_geno$Include)
FALSE TRUE
21621 5132 gf_mar$count.probs <- rowSums(gf_mar[c("freq_AA_probs","freq_AB_probs")] <=0.05)
filtered_gf_mar_probs <- gf_mar[gf_mar$count.probs != 1,]
filtered_gf_mar_probs <- filtered_gf_mar_probs[,-which(names(filtered_gf_mar_probs) %in% c("count.geno","count.probs","index"))]
dim(filtered_gf_mar_probs)[1] 27768 9table(filtered_gf_mar_probs$Include)
FALSE TRUE
22649 5119 ## merging with sample_genos
filtered_gf_mar_geno_sample <- merge(geno,filtered_gf_mar_geno, by="row.names", all.y=T, sort=F)
#filtered_gf_mar_geno_sample <- filtered_gf_mar_geno_sample[order(filtered_gf_mar_geno_sample$index),]
#filtered_gf_mar_geno_sample <- filtered_gf_mar_geno_sample[,-which(names(filtered_gf_mar_geno_sample) %in% c("count.geno","index"))]
names(filtered_gf_mar_geno_sample)[1] <- c("marker")
dim(filtered_gf_mar_geno_sample)[1] 26753 68filtered_gf_mar_probs_sample <- merge(geno,filtered_gf_mar_probs, by="row.names", all.y=T, sort=F)
#filtered_gf_mar_probs_sample <- filtered_gf_mar_probs_sample[order(filtered_gf_mar_probs_sample$index),]
#filtered_gf_mar_probs_sample <- filtered_gf_mar_probs_sample[,-which(names(filtered_gf_mar_probs_sample) %in% c("count.geno","count.probs","index"))]
names(filtered_gf_mar_probs_sample)[1] <- c("marker")
dim(filtered_gf_mar_probs_sample)[1] 27768 68## saving files
write.csv(filtered_gf_mar_geno_sample, "data/pbs-myo-yes.vs.pbs-myo-no_sample.genos_marker.freq_low.geno.freq.removed_4.batches_myo.csv", quote=F)
write.csv(filtered_gf_mar_probs_sample, "data/pbs-myo-yes.vs.pbs-myo-no_sample.genos_marker.freq_low.probs.freq.removed_4.batches_myo.csv", quote=F)
write.csv(filtered_gf_mar_geno, "data/pbs-myo-yes.vs.pbs-myo-no_marker.freq_low.geno.freq.removed_geno.ratio_4.batches_myo.csv", quote=F)
write.csv(filtered_gf_mar_probs, "data/pbs-myo-yes.vs.pbs-myo-no_marker.freq_low.probs.freq.removed_geno.ratio_4.batches_myo.csv", quote=F)load("data/gm_allqc_4.batches_myo.RData")
#gm_allqc
gm=gm_allqc
gmObject of class cross2 (crosstype "bc")
Total individuals 208
No. genotyped individuals 208
No. phenotyped individuals 208
No. with both geno & pheno 208
No. phenotypes 1
No. covariates 11
No. phenotype covariates 0
No. chromosomes 20
Total markers 32610
No. markers by chr:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
2498 2407 1748 1770 1649 1835 1544 1515 1773 1102 1744 1214 1442 1497 1109 835
17 18 19 X
674 813 940 4501 pr <- readRDS("data/serreze_probs_allqc_4.batches_myo.rds")
#pr <- readRDS("data/serreze_probs.rds")
geno <- read.csv("/Users/corneb/Documents/MyJax/CS/Projects/Serreze/haplotype.reconstruction/output_4.batches_myo_corrected/sample_geno_bc_4.batches_myo_BC217.csv", as.is=T)
names(geno) <- gsub("^X","",names(geno))
names(geno) <- gsub("\\.","-",names(geno))
rownames(geno) <- geno$marker## extracting animals with ici and pbs group status
#miceinfo <- gm$covar[gm$covar$group == "PBS" | gm$covar$group == "ICI",]
#table(miceinfo$group)
#mice.ids <- rownames(miceinfo)
#gm <- gm[mice.ids]
#gm
#table(gm$covar$group)
covars <- read_csv("data/covar_corrected.cleaned_pbs-myo-yes.vs.pbs-myo-no_4.batches_myo.csv")
# removing any missing info
covars <- subset(covars, covars$out.age.of.onset=='Keep' & covars$out.rz.age=='Keep')
nrow(covars)[1] 58table(covars$"Myocarditis Status")
NO YES
13 45 table(covars$"Murine MHC KO Status")
HOM
58 table(covars$"Drug Treatment")
PBS
58 table(covars$"clinical pheno")
EOI SICK
39 19 # keeping only informative mice
gm <- gm[covars$Mouse.ID]
gmObject of class cross2 (crosstype "bc")
Total individuals 58
No. genotyped individuals 58
No. phenotyped individuals 58
No. with both geno & pheno 58
No. phenotypes 1
No. covariates 11
No. phenotype covariates 0
No. chromosomes 20
Total markers 32610
No. markers by chr:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
2498 2407 1748 1770 1649 1835 1544 1515 1773 1102 1744 1214 1442 1497 1109 835
17 18 19 X
674 813 940 4501 table(gm$covar$"Myocarditis Status")
NO YES
13 45 table(gm$covar$"Murine MHC KO Status")
HOM
58 table(gm$covar$"Drug Treatment")
PBS
58 table(gm$covar$"clinical pheno")
EOI SICK
39 19 pr.qc.ids <- pr
for (i in 1:20){pr.qc.ids[[i]] = pr.qc.ids[[i]][covars$Mouse.ID,,]}
geno <- geno[,covars$Mouse.ID]
geno <- geno[marker_names(gm),]
dim(geno)[1] 32610 58## calculating genotype frequencies
### from geno genotypes
g <- do.call("cbind", gm$geno)
gf_mar_geno <- t(apply(g, 2, function(a) table(factor(a, 1:2))/sum(a != 0)))
gn_mar_geno <- t(apply(g, 2, function(a) table(factor(a, 0:2))))
#gf_mar_raw<- gf_mar_raw[gf_mar_raw[,2] != "NaN",]
colnames(gf_mar_geno) <- c("freq_AA_geno_table","freq_AB_geno_table")
colnames(gn_mar_geno) <- c("count_missing_geno_table","count_AA_geno_table","count_AB_geno_table")
gfn_mar_geno <- merge(as.data.frame(gn_mar_geno), as.data.frame(gf_mar_geno), by="row.names")
rownames(gfn_mar_geno) <- gfn_mar_geno[,1]
gfn_mar_geno <- gfn_mar_geno[-1]
### from raw using table function in R
#genosl <- list()
#for(i in 1:nrow(geno)){
##for(i in 1:3){
# genoi <- geno[i,]
# freqf <- table(factor(geno[i,], c("-","AA","AB")))
# genoi$count_AA_raw_rowSums <- rowSums(genoi == "AA")
# genoi$count_AB_raw_rowSums <- rowSums(genoi == "AB")
# genoi$count_missing_raw_rowSums <- rowSums(genoi == "-")
# freqf <- t(table(factor(geno[i,], c("-","AA","AB"))))
# freqf <- as.data.frame(t(freqf[1,]))
# rownames(freqf) <- rownames(genoi)
# colnames(freqf) <- c("count_missing_raw_table","count_AA_raw_table","count_AB_raw_table")
# genoif <- cbind(freqf,genoi[c("count_AA_raw_rowSums","count_AB_raw_rowSums","count_missing_raw_rowSums")])
# genosl[[i]] = genoif
#}
#gf_mar_raw <- do.call("rbind",genosl)
#gf_mar_raw <- gf_mar_raw[,c(1:3,6,4:5)]
#gf_mar_raw$index <- 1:nrow(gf_mar_raw)
### from probabilities
gf_mar_probs.1 <- calc_geno_freq(pr.qc.ids, by = "marker", omit_x = FALSE)
#gn_mar_probs <- calc_geno_freq(probs, by = "individual", omit_x = FALSE)
gf_mar_probs <- rbind(gf_mar_probs.1$A[,1:2], gf_mar_probs.1$X[,1:2])
colnames(gf_mar_probs) <- paste0("freq_",colnames(gf_mar_probs),"_probs")
gf_mar_probs <- as.data.frame(gf_mar_probs)
gf_mar_probs$index <- 1:nrow(gf_mar_probs)
### merging all genotype frequecies for all markers
#gf_mar.1 <- merge(as.data.frame(gf_mar_raw), as.data.frame(gfn_mar_geno), by="row.names")
#rownames(gf_mar.1) <- gf_mar.1[,1]
#gf_mar.1 <- gf_mar.1[-1]
#gf_mar <- merge(gf_mar.1,as.data.frame(gf_mar_probs), by="row.names")
gf_mar <- merge(as.data.frame(gfn_mar_geno),as.data.frame(gf_mar_probs), by="row.names")
rownames(gf_mar) <- gf_mar[,1]
gf_mar <- gf_mar[-1]
gf_mar <- gf_mar[order(gf_mar$index),]
dim(gf_mar)[1] 32610 8# Calculating ratio and flagging informative marker
gf_mar$ratio = as.numeric(gf_mar$freq_AA_geno_table)/as.numeric(gf_mar$freq_AB_geno_table)
gf_mar$Include = ifelse(gf_mar$ratio >= 0.90 & gf_mar$ratio <= 1.10, TRUE,FALSE)
table(gf_mar$Include)
FALSE TRUE
27478 5132 ## filtering out <= 0.05
gf_mar$count.geno <- rowSums(gf_mar[c("freq_AA_geno_table","freq_AB_geno_table")] <=0.05)
filtered_gf_mar_geno <- gf_mar[gf_mar$count.geno != 1,]
filtered_gf_mar_geno <- filtered_gf_mar_geno[,-which(names(filtered_gf_mar_geno) %in% c("count.geno","index"))]
dim(filtered_gf_mar_geno)[1] 26753 9table(filtered_gf_mar_geno$Include)
FALSE TRUE
21621 5132 gf_mar$count.probs <- rowSums(gf_mar[c("freq_AA_probs","freq_AB_probs")] <=0.05)
filtered_gf_mar_probs <- gf_mar[gf_mar$count.probs != 1,]
filtered_gf_mar_probs <- filtered_gf_mar_probs[,-which(names(filtered_gf_mar_probs) %in% c("count.geno","count.probs","index"))]
dim(filtered_gf_mar_probs)[1] 27768 9table(filtered_gf_mar_probs$Include)
FALSE TRUE
22649 5119 ## merging with sample_genos
filtered_gf_mar_geno_sample <- merge(geno,filtered_gf_mar_geno, by="row.names", all.y=T, sort=F)
#filtered_gf_mar_geno_sample <- filtered_gf_mar_geno_sample[order(filtered_gf_mar_geno_sample$index),]
#filtered_gf_mar_geno_sample <- filtered_gf_mar_geno_sample[,-which(names(filtered_gf_mar_geno_sample) %in% c("count.geno","index"))]
names(filtered_gf_mar_geno_sample)[1] <- c("marker")
dim(filtered_gf_mar_geno_sample)[1] 26753 68filtered_gf_mar_probs_sample <- merge(geno,filtered_gf_mar_probs, by="row.names", all.y=T, sort=F)
#filtered_gf_mar_probs_sample <- filtered_gf_mar_probs_sample[order(filtered_gf_mar_probs_sample$index),]
#filtered_gf_mar_probs_sample <- filtered_gf_mar_probs_sample[,-which(names(filtered_gf_mar_probs_sample) %in% c("count.geno","count.probs","index"))]
names(filtered_gf_mar_probs_sample)[1] <- c("marker")
dim(filtered_gf_mar_probs_sample)[1] 27768 68## saving files
write.csv(filtered_gf_mar_geno_sample, "data/pbs-myo-yes.vs.pbs-myo-no_sample.genos_marker.freq_low.geno.freq.removed_sample.outliers.removed_4.batches_myo.csv", quote=F)
write.csv(filtered_gf_mar_probs_sample, "data/pbs-myo-yes.vs.pbs-myo-no_sample.genos_marker.freq_low.probs.freq.removed_sample.outliers.removed_4.batches_myo.csv", quote=F)
write.csv(filtered_gf_mar_geno, "data/pbs-myo-yes.vs.pbs-myo-no_marker.freq_low.geno.freq.removed_sample.outliers.removed_geno.ratio_4.batches_myo.csv", quote=F)
write.csv(filtered_gf_mar_probs, "data/pbs-myo-yes.vs.pbs-myo-no_marker.freq_low.probs.freq.removed_sample.outliers.removed_geno.ratio_4.batches_myo.csv", quote=F)
R version 4.2.2 (2022-10-31)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Big Sur ... 10.16
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRlapack.dylib
locale:
[1] en_US.UTF-8/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] abind_1.4-5 qtl2_0.30 reshape2_1.4.4 ggplot2_3.4.0
[5] tibble_3.1.8 psych_2.2.9 readxl_1.4.1 cluster_2.1.4
[9] dplyr_1.0.10 optparse_1.7.3 rhdf5_2.40.0 mclust_6.0.0
[13] tidyr_1.2.1 data.table_1.14.6 knitr_1.41 kableExtra_1.3.4
[17] workflowr_1.7.0
loaded via a namespace (and not attached):
[1] httr_1.4.4 sass_0.4.4 bit64_4.0.5 jsonlite_1.8.4
[5] viridisLite_0.4.1 bslib_0.4.1 assertthat_0.2.1 getPass_0.2-2
[9] highr_0.9 blob_1.2.3 cellranger_1.1.0 yaml_2.3.6
[13] pillar_1.8.1 RSQLite_2.2.19 lattice_0.20-45 glue_1.6.2
[17] digest_0.6.30 promises_1.2.0.1 rvest_1.0.3 colorspace_2.0-3
[21] htmltools_0.5.3 httpuv_1.6.6 plyr_1.8.8 pkgconfig_2.0.3
[25] purrr_0.3.5 scales_1.2.1 webshot_0.5.4 processx_3.8.0
[29] svglite_2.1.0 whisker_0.4.1 getopt_1.20.3 later_1.3.0
[33] git2r_0.30.1 generics_0.1.3 cachem_1.0.6 withr_2.5.0
[37] cli_3.4.1 mnormt_2.1.1 magrittr_2.0.3 memoise_2.0.1
[41] evaluate_0.18 ps_1.7.2 fs_1.5.2 fansi_1.0.3
[45] nlme_3.1-160 xml2_1.3.3 tools_4.2.2 lifecycle_1.0.3
[49] stringr_1.5.0 Rhdf5lib_1.18.2 munsell_0.5.0 callr_3.7.3
[53] compiler_4.2.2 jquerylib_0.1.4 systemfonts_1.0.4 rlang_1.0.6
[57] grid_4.2.2 rhdf5filters_1.8.0 rstudioapi_0.14 rmarkdown_2.18
[61] gtable_0.3.1 DBI_1.1.3 R6_2.5.1 bit_4.0.5
[65] fastmap_1.1.0 utf8_1.2.2 rprojroot_2.0.3 stringi_1.7.8
[69] parallel_4.2.2 Rcpp_1.0.9 vctrs_0.5.1 tidyselect_1.2.0
[73] xfun_0.35