Download
| File | Description | Size |
|---|---|---|
| pcg_and_lncrna.tsv | Ensembl gene IDs for the subset of genes that are protein-coding or lncRNA. We include all genes in the Ensembl annotations in Pantry phenotyping and genetic analyses, and filter to this set of protein-coding and lncRNA genes for the Pantry and LaDDR study analyses. The aggregated results below have not been filtered, though LaDDR phenotyping and genetic analyses do only include protein-coding and lncRNA genes. | 3.0 MB |
| geuvadis.separate_kdp.assoc.tsv.gz |
Top cis-QTL associations per gene (*.cis_qtl.txt.gz),
not necessarily significant, for each of six knowledge-driven
modalities for Geuvadis.
|
7.7 MB |
| geuvadis.ddp.assoc.tsv.gz | Top cis-QTL associations per gene (not necessarily significant) for data-driven phenotypes for Geuvadis. | 2.5 MB |
| geuvadis.separate_kdp.qtls.tsv.gz |
Conditionally independent cis-QTLs
(*.cis_independent_qtl.txt.gz) mapped separately for
each of six knowledge-driven modalities for Geuvadis.
|
2.9 MB |
| geuvadis.cross_modality_kdp.qtls.tsv.gz | cis-QTLs conditionally independent across six knowledge-driven modalities for Geuvadis. | 1.6 MB |
| geuvadis.cross_modality_hybrid.qtls.tsv.gz | cis-QTLs conditionally independent across six knowledge-driven modalities plus residual data-driven phenotypes for Geuvadis. | 2.2 MB |
| geuvadis.ddp.qtls.tsv.gz | Conditionally independent cis-QTLs for data-driven phenotypes for Geuvadis. | 1.9 MB |
| geuvadis.kdp_rddp.hsq.tsv.gz | TWAS transcriptomic model summary table for six knowledge-driven modalities plus residual data-driven phenotypes for Geuvadis. | 2.4 MB |
| geuvadis.ddp.hsq.tsv.gz | TWAS transcriptomic model summary table for data-driven phenotypes for Geuvadis. | 1.3 MB |
| geuvadis.kdp_rddp.twas_hits.tsv.gz | TWAS hits for six knowledge-driven modalities plus residual data-driven phenotypes against all traits for Geuvadis. | 3.6 MB |
| geuvadis.ddp.twas_hits.tsv.gz | TWAS hits for data-driven phenotypes against all traits for Geuvadis. | 1.9 MB |
| gtex.separate_kdp.assoc.tsv.gz |
Top cis-QTL associations per gene (*.cis_qtl.txt.gz),
not necessarily significant, for six knowledge-driven modalities
for 49 GTEx tissues.
|
464 MB |
| gtex.ddp.assoc.tsv.gz | Top cis-QTL associations per gene (not necessarily significant) for data-driven phenotypes for 49 GTEx tissues. | 141 MB |
| gtex.separate_kdp.qtls.tsv.gz |
Conditionally independent cis-QTLs
(*.cis_independent_qtl.txt.gz) mapped separately for
each of six knowledge-driven modalities for 49 GTEx tissues.
|
106 MB |
| gtex.cross_modality_kdp.qtls.tsv.gz | cis-QTLs conditionally independent across six knowledge-driven modalities for 49 GTEx tissues. | 60 MB |
| gtex.cross_modality_hybrid.qtls.tsv.gz | cis-QTLs conditionally independent across six knowledge-driven modalities plus residual data-driven phenotypes for 49 GTEx tissues. | 130 MB |
| gtex.ddp.qtls.tsv.gz | Conditionally independent cis-QTLs for data-driven phenotypes for 49 GTEx tissues. | 99 MB |
| gtex.kdp_rddp.hsq.tsv.gz | TWAS transcriptomic model summary table for six knowledge-driven modalities plus residual data-driven phenotypes for 49 GTEx tissues. | 121 MB |
| gtex.ddp.hsq.tsv.gz | TWAS transcriptomic model summary table for data-driven phenotypes for 49 GTEx tissues. | 83 MB |
| gtex.kdp_rddp.twas_hits.tsv.gz | TWAS hits for six knowledge-driven modalities plus residual data-driven phenotypes against all traits for 49 GTEx tissues. | 176 MB |
| gtex.ddp.twas_hits.tsv.gz | TWAS hits for data-driven phenotypes against all traits for 49 GTEx tissues. | 100 MB |
RNA phenotypes were quantified for Geuvadis and 49 GTEx tissues. The
tables are in BED format, with the first three columns specifying the
TSS coordinate of each phenotype's gene, i.e., the input format for
tensorQTL. They have been normalized by
quantile-normalizing samples to the average empirical distribution,
followed by rank-based inverse-normal transformation per phenotype. For
GTEx tissues, we included only samples with genotypes and converted
sample IDs to individual IDs to match the genotypes.
| File | Modality |
|---|
For each tissue-modality RNA phenotype table, the covariates include the
first 20 principal components (PCs) of the phenotype table and the first
5 PCs of the genotype alternative allele count matrix. We include two
formats for each covariate table, one compatible with tensorQTL
(*.covar.tsv), and one in PLINK format for compatibility
with FUSION (*.covar.plink.tsv).
We include covariates and cis-QTL results for a concatenation of
phenotypes from six knowledge-driven modalities
(cross_modality_KDP) and for a concatenation of phenotypes
from the six knowledge-driven modalities plus residual data-driven
phenotypes (cross_modality_hybrid). Covariates for these
are computed from the
combined phenotype tables, and are not concatenations of
each modality's covariates. We used them for cross-modality mapping of
cis-QTLs, but not for xTWAS.
| File | Modality | Format |
|---|
Output files from tensorQTL run in cis mode
(*.cis_qtl.txt.gz, top association per gene, even if not
significant) and cis_independent mode
(*.cis_independent_qtl.txt.gz, all
conditionally-independent cis-QTLs). Files for
cross_modality_kdp are the result of running tensorQTL on
phenotype tables and group files containing all six knowledge-driven
modalities, so that cis-QTLs are conditionally independent across
modalities per gene (cross-modality mapping), and phenotypes used for
cross_modality_hybrid included the six knowledge-driven
modalities plus residual data-driven phenotypes.
| File | Modality |
|---|
A set of TWAS transcriptomic models was generated for each
tissue-modality pair using FUSION. The weights and summary files are
provided in compressed archives, and the outputs of the FUSION script
FUSION.profile_wgt.R, i.e. tables giving cis-heritability
and model stats per phenotype, are also included separately
(*.twas_weights.profile).
| File | Modality |
|---|
TWAS associations were calculated for each set of models against summary
stats for each of
114 GWAS traits previously harmonized to GTEx v8 variant reference. Outputs of FUSION.assoc_test.R were concatenated across
chromosomes to get one table per trait-tissue-modality combination.
Tables are provided in compressed archives per trait and include, for
each tissue, results for the six knowledge-driven modalities, residual
data-driven phenotypes, and full data-driven phenotypes. It is
recommended to analyze either the knowledge-driven and residual
data-driven phenotypes together or just the full data-driven phenotypes.