Splicing QTLs for NYGC ALS Consortium Paper

The files below contain nominal and permuted quantitative trait loci (QTL) associations between common genetic variants derived from whole genome sequencing and Leafcutter splice junction phenotypes generated from RNA-seq of post-mortem tissue sections. All QTLs were mapped with TensorQTL.

Top association files are gzip-compressed tab-separated variable files - *cis_qtl.txt.gz

Nominal association files are stored as Parquet files to save space. These can be converted to text files using the following code snippet:

pip install pandas pyarrow
conda install -c bioconda htslib # provides bgzip

python3 -c "
import pandas as pd
df = pd.read_parquet('your_file.parquet')
df.to_csv('your_file.tsv.gz', sep='\t', index=False)
" | bgzip > your_file.tsv.gz

NYGC_all_common_variants_alleles.tsv.gz - Allele information for all SNPs tested in the sQTL analysis

NYGC_gene_junction_annotation_GENCODE_v46.txt.gz - Gene annotation for each junction (GENCODE v46 Ensembl IDs and gene names). TSV format. Junctions mapping to multiple genes have all genes assigned, split by comma.

Table columns are formatted as follows:

Nominal QTL results include all SNP-gene pairs tested using a 1Mb window from each side of the transcription start site (TSS) of the gene. 

phenotype_id - splice junction coordinations in hg38.

variant_id - SNP tested for association (rsid or chr:position:ref:alt)

tss_distance - distance of the SNP to the gene transcription start site (TSS)

maf - minor allele frequency in cohort

ma_samples - number of samples carrying the minor allele

ma_count - total number of minor alleles across individuals

pval_nominal - nominal P-value from linear regression

slope - slope of the linear regression

slope_se - standard error of the slope

Top association results include only the top SNP-gene association for each gene. Table columns are formatted as follows:

phenotype_id - ensembl ID of the gene tested (GENCODE v30

num_var - total number of variants tested in cis

beta_shape1 - first parameter value of the fitted beta distribution

beta_shape2 - second parameter value of the fitted beta distribution

true_df - effective degrees of freedom the beta distribution approximation

pval_true_df - empirical P-value for the beta distribution approximation

variant_id - ID of the top variant (rsid or chr:position:ref:alt)

tss_distance - distance of the SNP to the gene transcription start site (TSS)

ma_samples - number of samples carrying the minor allele

ma_count - total number of minor alleles across individuals

maf -minor allele frequency in MiGA cohort

ref_factor - flag indicating if the alternative allele is the minor allele in the cohort (1 if AF <= 0.5, -1 if not)

pval_nominal - nominal P-value from linear regression

slope - slope of the linear regression

slope_se - standard error of the slope

pval_perm - first permutation P-value directly obtained from the permutations with the direct method

pval_beta - second permutation P-value obtained via beta approximation. This is the one to use for downstream analysis

qval - Storey q-value derived from pval_beta (FDR adjusted)

pval_nominal_threshold - nominal P-value threshold for calling a variant-gene pair significant for the gene

Allele Information for each variant:

CHROM - chromosome position of the variant

POS - position of the variant in the chromosome

REF - reference allele (GRCh38)

ALT - alternative allele (this is the effect allele in the eQTL analysis)

ID - variant id (rsid or chr:position:ref:alt)