zenodo v3

zenodo_v3

updated COLOC and eCAVIAR code

zenodo v2

zenodo_v2

Update README.md

Gene counts

• gene.noVersion.rawCounts.tsv.zip: raw gene counts, quantified by Salmon, compiled by tximport
• genes.combatseq.tsv.zip: raw gene counts, restricted to gene and sample sets used in eQTL mapping (31947 genes, 642 samples), combat-seq to correct for batch. WGCNA network analysis starts from this file, and then TMM normalize to generate a pseudo-count matrix of normalized expression

Genotypic variants

test.bim.zip: Genotypic variants for multi-ancestry xQTL mapping. A1 is the effect allele.
filtered.hg19.sorted.removeRel.bim.zip: Genotypic variants for EUR xQTL mapping. A1 is the effect allele

zenodo

Make zenodo archive

Supplementary Data for medRxiv

Supplementary Data
Data S1 (Mixed_ciseqtl_90hcp_perm_purity_filtered.txt.gz): SuSiE fine-mapping results for multi-ancestry cis-eQTL
Data S2 (Eur_ciseqtl_50hcp_perm_purity_filtered.txt.gz): SuSiE fine-mapping results for EUR cis-eQTL
Data S3 (Amr_ciseqtl_15hcp_perm_purity_filtered.txt.gz): SuSiE fine-mapping results for AMR cis-eQTL
Data S4 (Afr_ciseqtl_25hcp_perm_purity_filtered.txt.gz): SuSiE fine-mapping results for AFR cis-eQTL
Data S5 (EUR_tri1_gene_cish2.csv): heritability estimates for genes in EUR Tri1 samples
Data S6: EUR_tri2_gene_cish2.csv): heritability estimates for genes in EUR Tri2 samples
Data S7: (EUR_tri1_splicing_cish2.csv): heritability estimates for local splicing in EUR Tri1 samples
Data S8: (EUR_tri2_splicing_cish2.csv): heritability estimates for local splicing in EUR Tri2 samples
Data S9 (modeqtl_top.RData): module interaction eQTL permutation eGenes and their primary ieQTLs

Supplementary Tables for medRxiv

Table S1. Metadata and xQTL summary statistics
● README
● ST1-1-metadata: Metadata of 654 distinct, high-quality samples
● ST1-2-eGene: Sum stats of 10094 permutation eGenes and their primary cis-eQTL
● ST1-3-isoGene: Sum stats of 11845 group permutation isoGenes and their primary cis-isoQTL
● ST1-4-sGene: Sum stats of 7490 group permutation sGenes and their primary cis-sQTL
● ST1-5-torus-funcEnrich: Torus functional enrichment of cis-e/iso/sQTL
● ST1-6-conditional: Sum stats of conditional cis-eQTL mapping, for detailed descriptions of columns, see https://qtltools.github.io/qtltools/
● ST1-7-fetalOnlyeGene-CellTypeEnrich: Cell type enrichment for 2488 fetal only eGenes. "apprach" column denotes whether the cell types are defined as broad, cluster, or sub-cluster
● ST1-8-inv-eQTL: Sum stats of significant inversion eQTL

Table S2. Population specific xQTL and fine-mapping
● README
● ST2-1-EUR-eGenes: Sum stats of 5296 EUR permutation eGenes and their primary cis-eQTL
● ST2-2-AMR-eGenes: Sum stats of 3242 EUR permutation eGenes and their primary cis-eQTL
● ST2-3-AFR-eGenes: Sum stats of 1876 EUR permutation eGenes and their primary cis-eQTL
● ST2-4-EUR-isoGenes : Sum stats of 11672/6885 isoforms/isoGenes with permutation cis-isoQTL in EUR
● ST2-5-AMR-isoGenes: Sum stats of 5747/3989 isoforms/isoGenes with permutation cis-isoQTL in AMR
● ST2-6-AFR-isoGenes: Sum stats of 3719/2682 isoforms/isoGenes with permutation cis-isoQTL in AFR
● ST2-7-EUR-sGenes: Sum stats of 16277/4963 introns/sGenes with permutation cis-sQTL in EUR
● ST2-8-AMR-sGenes: Sum stats of 6324/2772 introns/sGenes with permutation cis-sQTL in AMR
● ST2-9-AFR-sGenes: Sum stats of 4337/2069 introns/sGenes with permutation cis-sQTL in AFR

Table S3. Trimester xQTL summary statistics
● README
● ST3-1-tri1-eGene: Sum stats of 4211 permutation eGenes in Tri1
● ST3-2-tri2-eGene: Sum stats of 2220 permutation eGenes in Tri2
● ST3-3-tri1-isoGene: Sum stats of 10881/6921 isoforms/isoGenes with permutation cis-isoQTL in Tri1
● ST3-4-tri2-isoGene: Sum stats of 4179/3047 isoforms/isoGenes with permutation cis-isoQTL in Tri2
● ST3-5-tri1-sGene: Sum stats of 14193/5312 introns/sGenes with permutation cis-sQTL in Tri1
● ST3-6-tri2-sGene: Sum stats of 5348/2318 introns/sGenes with permutation cis-sQTL in Tri2
● ST3-7-triOnly-biotype: Counts of gene types of tri1 and tri2-only e/sGenes
● ST3-8-triOnly-cellTypeEnrich: Cell type enrichment of tri1 and tri2-only e/sGenes

Table S4. S-LDSC and MESC results
● README
● ST4-1-sLDSC: S-LDSC of background and various brain QTL annotations (e/iso/sQTL, GTEx brain cortex eQTL, tri e/iso/sQTL)
● ST4-2-sLDSC-e/iso/sQTL-joint: S-LDSC jointly running background annotations, and e+iso+sQTL, top enrichment 15 annotations
● ST4-3-sLDSC-e/isoQTL-joint: S-LDSC jointly running background annotations, and e+isoQTL, top enrichment 15 annotations
● ST4-4-MESC: h2med results for all expressed genes/isoforms/introns in the full dataset, and trimester specific datasets

Table S5. isoTWAS and colocalization
● README
● ST5-1a-isoTWAS-preFOCUS: isoTWAS statistics of isoforms that are permutation significant
● ST5-1b-isoTWAS-finemapped: isoTWAS statistics of isoforms that are in 90% FOCUS credible sets
● ST5-2 to ST5-29: eCAVIAR significant colocalization results for various neuropsychiatric GWAS and fetal brain QTLs
● ST5-30: MRLOCUS summary statistics

Table S6. Network analyses
● README
● ST6-1-Module-Genes: Membership of genes and transcripts to each of the modules
● ST6-2-All-Enrichment: Compiled module enrichment data from ST6-3, ST6-4, and ST6-5
● ST6-3-Cell-Enrichment: Cell type enrichment of modules using Polioudakis fetal brain marker genes
● ST6-4-Common-Enrichment: Common variation enrichment of modules using sLDSC and MAGMA
● ST6-5-Rare-Enrichment: Rare variation enrichment of modules using logistic regression
● ST6-6-Module-Overlap: Overlap of fetal modules with other fetal modules in the dataset or modules from Walker et al. (walker_), Werling et al. (werling_), and Li et al. (li_)

Table S7. CellWalker and module interacting eQTL summary statistics
● README
● ST7-1-CellWalker-single-label: CellWalker mapping of bulk eQTL SuSiE results to single cell type labels. Corresponds to Fig 7A
● ST7-2-CellWalker-ML-strict: CellWalker mapping of bulk eQTL SuSiE results to multi-level ("ML") cell type labels. Filtered for number of cell types. See methods for details

TWAS Weights

Gene-level TWAS weights:

1. PredictDB data format for PrediXcan family of methods
2. ZIP of individual gene .wgt files for TWAS / Fusion Methods