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Hi,
I followed the steps outlined in the Readme and utilized the run_ldsc_reg.sh script to compute the disease heritability enrichment signal for each cell type, categorized by annotation type (e.g., based on eQTL or PC Hi-C, etc.). My aim is to combine different annotation types to determine the total disease heritability enrichments for each cell type. To achieve this, I utilized either the ldsc_postprocess_combined_taustar.R or ldsc_postprocess_joint_taustar.R script. However, I am perplexed by the code that the test for tau in the script (meta.summaries) is derived from the results (df) calculated across multiple traits. How does this calculation translate into the disease heritability enrichment of cell types? I would appreciate it if someone could point out where I may be misunderstanding the process.
It's worth mentioning that my resulting directory distribution is:
Hi,
I followed the steps outlined in the Readme and utilized the run_ldsc_reg.sh script to compute the disease heritability enrichment signal for each cell type, categorized by annotation type (e.g., based on eQTL or PC Hi-C, etc.). My aim is to combine different annotation types to determine the total disease heritability enrichments for each cell type. To achieve this, I utilized either the ldsc_postprocess_combined_taustar.R or ldsc_postprocess_joint_taustar.R script. However, I am perplexed by the code that the test for tau in the script (meta.summaries) is derived from the results (df) calculated across multiple traits. How does this calculation translate into the disease heritability enrichment of cell types? I would appreciate it if someone could point out where I may be misunderstanding the process.
It's worth mentioning that my resulting directory distribution is:
cell type1:
trait1.results
trait1.delete
trait1.log
trait1.part_delete
trait2.results
trait2.delete
trait2.log
trait2.part_delete
cell type2:
trait1.results
trait1.delete
trait1.log
trait1.part_delete
...
cell type1:
...
cell type2:
...
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