plot_effect_concordance_across_cohorts.R: compares effect sizes (Z-scores) calculated in each individual dataset (before the meta-analysis)
plot_celltype_overlap_upset.R : upset plot overlap of significant co-eQTLs between cell types
power_analyis_coeqtls.R : explores how the number of tests reduce the power to detect co-eQTLs, taking estimates for number of tests based on how many genes are expressed above different cutoffs for Oelen v3 dataset
Rb calculations are these files:
prepare_for_rb_calculation.py : prepare the input files for rb calculation
Rb.R : rb function
calculate_rb_for_sc_and_bios.R : execute rb functions
rb_celltypes.ipynb: examine the rb values for each cell type; also include scripts for examining different characteristics for coeQTLs compared to non-coeQTLs
Co-eQTL pipeline are these files:
all files in the betaqtl_scripts (incl. templates)
individual_networks.py: make co-expression files for each individual
prepare_genelist_and_annotation_for_betaqtl.py: prepare input files for the qtl mapping pipeline
createBatches.sh: create batches for qtl mapping pipeline
submit_process_betaqtl_results.sh: submit the jobs for concatenating qtl mapping and perform multiple testing procedures
concat_betaqtl_results.fixed.py: concat qtl mapping results
screen_permutation_p_values.py: concat permutation files
multipletesting_correction.fixed.py: perform multiple testing correction
Other co-eQTL analysis:
filtering_strategy.py: filter for gene pairs
individual_networks_cmono_ncmono.py: create co-expression files for each individual for sub cell types in monocytes
individual_networks_maxcell.py: create co-expression files for each individual with a limit of cell number
merge_coexpression_for_betaeqtl_maxcell.py: merge the co-expression files for each individual with a limit of cell number
merge_coexpression_for_betaqtl.subsampleindividuals.py: create co-expression files for each individual with a limit of sample number
BIOS replication are these files:
replication_in_bios.py: perform bios replication
select_snps_from_vcf.sh: select SNP from vcf file
examine_bios_replication.ipynb: examine the bios replication results
Annotating coeQTL results:
annotate_coeqtl_files.py: annotate the coeqtl results for nonzero ratio, mean and var of gene pair
collect_nonzeroratio.py: collect non zero ratio annotation for all genes in all datasets