FunGen-xQTL Resources

Knight ADRC brain proteomics QTL

Charles F. And Joanne Knight Alzheimer’s Disease Research Center (Knight-ADRC)

Please refer to this document for an overview of the Knight project.

Cohort
Knight-ADRCKnight Alzheimer Disease Research Center
Modality
pQTLQTL results
Tissue or cell type
parietal cortex
Sample size
412 samples
Release status
Stagednot yet verified
Access
ControlledData use certificate
Lead analysts
Zining QiSelect a name to email them
Source data
Knight ADRC brain Proteomics
Open syn69670592 in Synapse ↗ Query associations in the xQTL Atlas ↗

Access

Controlled access. Request data access for Knight-ADRC on the AD Knowledge Portal; you need a Synapse account. See How to get the data.

WhereIDAccessWhat you get
Synapsesyn69670592ControlledResults described below

Other Synapse IDs on this page syn69670600 syn69670611 syn69670597 syn69865816 syn69670630

shell
pip install synapseclient
synapse login
synapse get -r syn69670592

Contact

Zining Qi(zq2209@cumc.columbia.edu)

Study Overview

  • Study name : Knight ADRC brain proteomics QTL
  • Study Description : Charles F. And Joanne Knight Alzheimer’s Disease Research Center (Knight-ADRC) brain proteomics QTL analysis summary statistics using the FGC xQTL pipeline.

Samples’ phenotype information (sex, age, race etc.) can be found in Knight metadata, see “Other information” section in this document

Analysis Status

TransQTL association: Need to be updated with new covariate files.

Analysis Details

Sample size tracking through the analysis workflow

StepSample Size
Raw data442
After overlapping with Knight covariates418
After overlapping with Knight genotype412

QC and Normalization Details for Phenotype Data

For QCs performed on data please refer to descriptor/omics/proteomics/proteomics/Knight_ADRC_brain_proteomics.md

Genotype parameters

  • Kinship coefficient for related individuals: 0.0625
  • Minor allele count cutoff for single variant analysis: 5
  • Variant level missingness threshold: 0.1
  • Sample level missingness threshold: 0.1

Covariate parameters

PCA analysis:

  • MAF for PCA: 0.05
  • LD pruning via PLINK for PCA analysis: window 50, shift 10, r2 0.1
  • Tolerance of missingness in covariates: 0.3
  • number of pc that captured more than 70% PVE were kept

Hidden Factor analysis - PCA

  • Use Marchenko-Pastur limit to choose PCs

Final covariates: Sex, Age at death, PMI, PCs(12), hidden factors(18)

TensorQTL association scan parameters

  • cis/trans window for the up and downstream radius to analyze around the region of interest, in units of bp: 1000000
  • Minor allele count cutoff: 5
  • Minor allele frequency cutoff: 5/(2N), where N is the number of samples in the analysis. The pipeline computes N from the covariate file, so the cutoff differs between datasets.

See notebooks in:

The notebooks in this folder contain the commands and data wrangling codes for analysis of the proteomics data in ROSMAP. (data wrangling exist because not all data are processed using the xqtl-pipeline from the begnning and need to be reformated to fit one intermediate step of the pipeline).

Association data preprocessing

phenotype preprocessing can be run in parallel but covariate preprocessing need to be done last since it requires both phenotype data and PCs from PCA in genotype preprocessing.

  • genotype_preprocessing.ipynb shows the commands used for genotype processing and preparation steps.
    • Includes QC, PCA, and PCA result figures.
  • phenotype_preprocessing.ipynb shows the commands used for the phenotype data processing and preparation steps.
    • This notebook strated from some already cleaned data and covert them to bed format inputs taken by tensorQTL.
  • covariate_preprocessing.ipynb shows the commands used for the covariate data processing and preparation steps.
    • This includes PCA hidden factor analysis steps and merging the PCA hidden factors to covariates and PCA.

Association scan using TensorQTL and summary statistics standardization

Dataset Description

Path(s) to genotype matrix

text
-rw-r--r-- 1 zq2209 zq2209  48M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.10.bed
-rw-r--r-- 1 zq2209 zq2209  17M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.10.bim
-rw-r--r-- 1 zq2209 zq2209 9.4K Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.10.fam
-rw-r--r-- 1 zq2209 zq2209  47M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.11.bed
-rw-r--r-- 1 zq2209 zq2209  16M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.11.bim
-rw-r--r-- 1 zq2209 zq2209 9.4K Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.11.fam
-rw-r--r-- 1 zq2209 zq2209  45M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.12.bed
-rw-r--r-- 1 zq2209 zq2209  16M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.12.bim
-rw-r--r-- 1 zq2209 zq2209 9.4K Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.12.fam
-rw-r--r-- 1 zq2209 zq2209  35M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.13.bed
-rw-r--r-- 1 zq2209 zq2209  12M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.13.bim
-rw-r--r-- 1 zq2209 zq2209 9.4K Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.13.fam
-rw-r--r-- 1 zq2209 zq2209  30M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.14.bed
-rw-r--r-- 1 zq2209 zq2209  11M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.14.bim
-rw-r--r-- 1 zq2209 zq2209 9.4K Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.14.fam
-rw-r--r-- 1 zq2209 zq2209  26M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.15.bed
-rw-r--r-- 1 zq2209 zq2209 8.9M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.15.bim
-rw-r--r-- 1 zq2209 zq2209 9.4K Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.15.fam
-rw-r--r-- 1 zq2209 zq2209  29M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.16.bed
-rw-r--r-- 1 zq2209 zq2209 9.6M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.16.bim
-rw-r--r-- 1 zq2209 zq2209 9.4K Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.16.fam
-rw-r--r-- 1 zq2209 zq2209  25M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.17.bed
-rw-r--r-- 1 zq2209 zq2209 8.3M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.17.bim
-rw-r--r-- 1 zq2209 zq2209 9.4K Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.17.fam
-rw-r--r-- 1 zq2209 zq2209  27M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.18.bed
-rw-r--r-- 1 zq2209 zq2209 9.1M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.18.bim
-rw-r--r-- 1 zq2209 zq2209 9.4K Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.18.fam
-rw-r--r-- 1 zq2209 zq2209  21M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.19.bed
-rw-r--r-- 1 zq2209 zq2209 7.0M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.19.bim
-rw-r--r-- 1 zq2209 zq2209 9.4K Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.19.fam
-rw-r--r-- 1 zq2209 zq2209  72M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.1.bed
-rw-r--r-- 1 zq2209 zq2209  24M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.1.bim
-rw-r--r-- 1 zq2209 zq2209 9.4K Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.1.fam
-rw-r--r-- 1 zq2209 zq2209  21M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.20.bed
-rw-r--r-- 1 zq2209 zq2209 7.0M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.20.bim
-rw-r--r-- 1 zq2209 zq2209 9.4K Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.20.fam
-rw-r--r-- 1 zq2209 zq2209  13M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.21.bed
-rw-r--r-- 1 zq2209 zq2209 4.3M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.21.bim
-rw-r--r-- 1 zq2209 zq2209 9.4K Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.21.fam
-rw-r--r-- 1 zq2209 zq2209  13M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.22.bed
-rw-r--r-- 1 zq2209 zq2209 4.3M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.22.bim
-rw-r--r-- 1 zq2209 zq2209 9.4K Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.22.fam
-rw-r--r-- 1 zq2209 zq2209  77M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.2.bed
-rw-r--r-- 1 zq2209 zq2209  26M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.2.bim
-rw-r--r-- 1 zq2209 zq2209 9.4K Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.2.fam
-rw-r--r-- 1 zq2209 zq2209  66M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.3.bed
-rw-r--r-- 1 zq2209 zq2209  22M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.3.bim
-rw-r--r-- 1 zq2209 zq2209 9.4K Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.3.fam
-rw-r--r-- 1 zq2209 zq2209  68M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.4.bed
-rw-r--r-- 1 zq2209 zq2209  23M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.4.bim
-rw-r--r-- 1 zq2209 zq2209 9.4K Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.4.fam
-rw-r--r-- 1 zq2209 zq2209  61M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.5.bed
-rw-r--r-- 1 zq2209 zq2209  20M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.5.bim
-rw-r--r-- 1 zq2209 zq2209 9.4K Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.5.fam
-rw-r--r-- 1 zq2209 zq2209  62M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.6.bed
-rw-r--r-- 1 zq2209 zq2209  21M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.6.bim
-rw-r--r-- 1 zq2209 zq2209 9.4K Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.6.fam
-rw-r--r-- 1 zq2209 zq2209  55M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.7.bed
-rw-r--r-- 1 zq2209 zq2209  18M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.7.bim
-rw-r--r-- 1 zq2209 zq2209 9.4K Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.7.fam
-rw-r--r-- 1 zq2209 zq2209  51M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.8.bed
-rw-r--r-- 1 zq2209 zq2209  17M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.8.bim
-rw-r--r-- 1 zq2209 zq2209 9.4K Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.8.fam
-rw-r--r-- 1 zq2209 zq2209  41M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.9.bed
-rw-r--r-- 1 zq2209 zq2209  14M Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.9.bim
-rw-r--r-- 1 zq2209 zq2209 9.4K Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.9.fam
-rw-r--r-- 1 zq2209 zq2209 922M Feb 14 10:37 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.bed
-rw-r--r-- 1 zq2209 zq2209 309M Feb 14 10:37 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.bim
-rw-r--r-- 1 zq2209 zq2209 9.4K Feb 14 17:30 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.fam
-rw-r--r-- 1 zq2209 zq2209  19K Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.X.bed
-rw-r--r-- 1 zq2209 zq2209 6.2K Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.X.bim
-rw-r--r-- 1 zq2209 zq2209 9.4K Feb 14 17:36 MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.X.fam

Path(s) to omics-data matrix

text
$ ls -lh *.{txt,gz}
-rw-r--r-- 1 zq2209 zq2209 4.2M Jun  1 13:18  WashU_pheno.bed.gz
-rw-r--r-- 1 zq2209 zq2209 133K Jun  1 13:18  WashU_pheno_chr10.bed.gz
-rw-r--r-- 1 zq2209 zq2209 243K Jun  1 13:18  WashU_pheno_chr11.bed.gz
-rw-r--r-- 1 zq2209 zq2209 284K Jun  1 13:18  WashU_pheno_chr12.bed.gz
-rw-r--r-- 1 zq2209 zq2209  83K Jun  1 13:18  WashU_pheno_chr13.bed.gz
-rw-r--r-- 1 zq2209 zq2209 122K Jun  1 13:18  WashU_pheno_chr14.bed.gz
-rw-r--r-- 1 zq2209 zq2209 111K Jun  1 13:18  WashU_pheno_chr15.bed.gz
-rw-r--r-- 1 zq2209 zq2209 144K Jun  1 13:18  WashU_pheno_chr16.bed.gz
-rw-r--r-- 1 zq2209 zq2209 291K Jun  1 13:18  WashU_pheno_chr17.bed.gz
-rw-r--r-- 1 zq2209 zq2209  57K Jun  1 13:18  WashU_pheno_chr18.bed.gz
-rw-r--r-- 1 zq2209 zq2209 348K Jun  1 13:18  WashU_pheno_chr19.bed.gz
-rw-r--r-- 1 zq2209 zq2209 453K Jun  1 13:18  WashU_pheno_chr1.bed.gz
-rw-r--r-- 1 zq2209 zq2209 151K Jun  1 13:18  WashU_pheno_chr20.bed.gz
-rw-r--r-- 1 zq2209 zq2209  91K Jun  1 13:18  WashU_pheno_chr21.bed.gz
-rw-r--r-- 1 zq2209 zq2209 103K Jun  1 13:18  WashU_pheno_chr22.bed.gz
-rw-r--r-- 1 zq2209 zq2209 238K Jun  1 13:18  WashU_pheno_chr2.bed.gz
-rw-r--r-- 1 zq2209 zq2209 220K Jun  1 13:18  WashU_pheno_chr3.bed.gz
-rw-r--r-- 1 zq2209 zq2209 235K Jun  1 13:18  WashU_pheno_chr4.bed.gz
-rw-r--r-- 1 zq2209 zq2209 222K Jun  1 13:18  WashU_pheno_chr5.bed.gz
-rw-r--r-- 1 zq2209 zq2209 177K Jun  1 13:18  WashU_pheno_chr6.bed.gz
-rw-r--r-- 1 zq2209 zq2209 182K Jun  1 13:18  WashU_pheno_chr7.bed.gz
-rw-r--r-- 1 zq2209 zq2209 129K Jun  1 13:18  WashU_pheno_chr8.bed.gz
-rw-r--r-- 1 zq2209 zq2209 138K Jun  1 13:18  WashU_pheno_chr9.bed.gz
-rw-r--r-- 1 zq2209 zq2209 115K Jun  1 13:18  WashU_pheno_chrX.bed.gz

Path(s) to covariate data matrix

text
$ ls -lh *.gz
-rw-r--r-- 1 zq2209 zq2209 113K Jun  1 13:22 WashU_pheno.WashU_cov.MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.pQTL.related.filtered.extracted.pca.projected.resid.Marchenko_pc.gz

Path(s) to QTL results

text
ls -lh *.txt
-rw-r--r-- 1 zq2209 zq2209 8.9K May 19 14:33 pheno_recipe_WashU_pheno.WashU_cov.MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.pQTL.related.filtered.extracted.pca.projected.resid.Marchenko_pc.10.emprical.cis_sumstats.txt
-rw-r--r-- 1 zq2209 zq2209  44M May 19 14:32 pheno_recipe_WashU_pheno.WashU_cov.MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.pQTL.related.filtered.extracted.pca.projected.resid.Marchenko_pc.10.norminal.cis_long_table.txt
-rw-r--r-- 1 zq2209 zq2209  17K May 19 14:34 pheno_recipe_WashU_pheno.WashU_cov.MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.pQTL.related.filtered.extracted.pca.projected.resid.Marchenko_pc.11.emprical.cis_sumstats.txt
-rw-r--r-- 1 zq2209 zq2209  76M May 19 14:34 pheno_recipe_WashU_pheno.WashU_cov.MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.pQTL.related.filtered.extracted.pca.projected.resid.Marchenko_pc.11.norminal.cis_long_table.txt
-rw-r--r-- 1 zq2209 zq2209  19K May 19 14:36 pheno_recipe_WashU_pheno.WashU_cov.MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.pQTL.related.filtered.extracted.pca.projected.resid.Marchenko_pc.12.emprical.cis_sumstats.txt
-rw-r--r-- 1 zq2209 zq2209  81M May 19 14:35 pheno_recipe_WashU_pheno.WashU_cov.MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.pQTL.related.filtered.extracted.pca.projected.resid.Marchenko_pc.12.norminal.cis_long_table.txt
-rw-r--r-- 1 zq2209 zq2209 5.5K May 19 14:35 pheno_recipe_WashU_pheno.WashU_cov.MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.pQTL.related.filtered.extracted.pca.projected.resid.Marchenko_pc.13.emprical.cis_sumstats.txt
-rw-r--r-- 1 zq2209 zq2209  26M May 19 14:35 pheno_recipe_WashU_pheno.WashU_cov.MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.pQTL.related.filtered.extracted.pca.projected.resid.Marchenko_pc.13.norminal.cis_long_table.txt
-rw-r--r-- 1 zq2209 zq2209 8.6K May 19 14:35 pheno_recipe_WashU_pheno.WashU_cov.MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.pQTL.related.filtered.extracted.pca.projected.resid.Marchenko_pc.14.emprical.cis_sumstats.txt
-rw-r--r-- 1 zq2209 zq2209  41M May 19 14:34 pheno_recipe_WashU_pheno.WashU_cov.MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.pQTL.related.filtered.extracted.pca.projected.resid.Marchenko_pc.14.norminal.cis_long_table.txt
-rw-r--r-- 1 zq2209 zq2209 7.2K May 19 14:35 pheno_recipe_WashU_pheno.WashU_cov.MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.pQTL.related.filtered.extracted.pca.projected.resid.Marchenko_pc.15.emprical.cis_sumstats.txt
-rw-r--r-- 1 zq2209 zq2209  29M May 19 14:35 pheno_recipe_WashU_pheno.WashU_cov.MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.pQTL.related.filtered.extracted.pca.projected.resid.Marchenko_pc.15.norminal.cis_long_table.txt
-rw-r--r-- 1 zq2209 zq2209 9.8K May 19 14:35 pheno_recipe_WashU_pheno.WashU_cov.MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.pQTL.related.filtered.extracted.pca.projected.resid.Marchenko_pc.16.emprical.cis_sumstats.txt
-rw-r--r-- 1 zq2209 zq2209  42M May 19 14:35 pheno_recipe_WashU_pheno.WashU_cov.MAP_Brain-xQTL_Gwas_geno_0.1_maf_0.0005.filtered.pQTL.related.filtered.extracted.pca.projected.resid.Marchenko_pc.16.norminal.cis_long_table.txt
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  • FTP:

Path(s) to cis-QTL association testing

output of TensorQTL.ipynb

Path(s) to fine-mapping with SuSiE RSS model

Fine-mapping model objects (SuSiE-RSS, .rds) are available in the finemapping models folder (syn69670592).

Path(s) to TWAS models

Pre-trained TWAS weight models for this context: syn69670600

Quantile TWAS (qTWAS) models: syn69670611

Path(s) to colocalization with SuSiE-coloc / ColocBoost

Multi-context colocalization models (ColocBoost): syn69670597

AD GWAS–xQTL colocalization results: syn69865816

AD GWAS–xQTL colocalization models: syn69670630

Analyses

  • cis-QTLDone
  • SuSiEDone
  • TWASDone

Read from the methods: map in this page's metadata header, the same data as the analysis coverage grid.