Loading required namespace: GenomicFiles Using local VCF. File already tabix-indexed. Finding empty VCF columns based on first 10,000 rows. Dropping 1 duplicate column(s). 1 sample detected: eqtl-a-ENSG00000064989 Constructing ScanVcfParam object. VCF contains: 18,019 variant(s) x 1 sample(s) Processing will be more efficient in single-threaded mode when nrows<100000. Temporarily setting nThread=1. Reading VCF file: single-threaded Converting VCF to data.table. Expanding VCF first, so number of rows may increase. Dropping 1 duplicate column(s). Checking for empty columns. Unlisting 4 columns. VCF data.table contains: 18,018 rows x 12 columns. Renaming ID as SNP. VCF file has -log10 P-values; these will be converted to unadjusted p-values in the 'P' column. No INFO (SI) column detected. Standardising column headers. First line of summary statistics file: SNP chr BP end REF ALT FILTER AF ES SE LP SS P Summary statistics report: - 18,018 rows - 18,018 unique variants - 1,156 genome-wide significant variants (P<5e-8) - 22 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Inferring genome build. Loading SNPlocs data. Loading reference genome data. Preprocessing RSIDs. Validating RSIDs of 10,000 SNPs using BSgenome::snpsById... Loading required package: BiocGenerics Attaching package: ‘BiocGenerics’ The following objects are masked from ‘package:stats’: IQR, mad, sd, var, xtabs The following objects are masked from ‘package:base’: anyDuplicated, aperm, append, as.data.frame, basename, cbind, colnames, dirname, do.call, duplicated, eval, evalq, Filter, Find, get, grep, grepl, intersect, is.unsorted, lapply, Map, mapply, match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, Position, rank, rbind, Reduce, rownames, sapply, setdiff, sort, table, tapply, union, unique, unsplit, which.max, which.min Loading required package: S4Vectors Loading required package: stats4 Attaching package: ‘S4Vectors’ The following objects are masked from ‘package:base’: expand.grid, I, unname BSgenome::snpsById done in 29 seconds. Loading SNPlocs data. Loading reference genome data. Preprocessing RSIDs. Validating RSIDs of 10,000 SNPs using BSgenome::snpsById... BSgenome::snpsById done in 54 seconds. Inferred genome build: GRCH37 Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Ensuring all SNPs are on the reference genome. Loading SNPlocs data. Loading reference genome data. Preprocessing RSIDs. Validating RSIDs of 18,018 SNPs using BSgenome::snpsById... BSgenome::snpsById done in 28 seconds. 398 SNPs are not on the reference genome. These will be corrected from the reference genome. Loading SNPlocs data. Sorting coordinates with 'data.table'. Writing in tabular format ==> /rds/general/project/neurogenomics-lab/ephemeral/MAGMA_Files_Public/data/GWAS_munged/eqtl-a-ENSG00000064989/logs/snp_not_found_from_chr_bp.tsv Writing uncompressed instead of gzipped to enable tabix indexing. Converting full summary stats file to tabix format for fast querying... Reading header. Ensuring file is bgzipped. Tabix-indexing file. Removing temporary .tsv file. Loading SNPlocs data. Loading reference genome data. Preprocessing RSIDs. Validating RSIDs of 17,622 SNPs using BSgenome::snpsById... BSgenome::snpsById done in 14 seconds. Checking for correct direction of A1 (reference) and A2 (alternative allele). Reordering so first three column headers are SNP, CHR and BP in this order. Reordering so the fourth and fifth columns are A1 and A2. Checking for missing data. Checking for duplicate columns. Ensuring that the N column is all integers. The sumstats N column is not all integers, this could effect downstream analysis. These will be converted to integers. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Checking for bi-allelic SNPs. 528 SNPs are non-biallelic. These will be removed. Sorting coordinates with 'data.table'. Writing in tabular format ==> /rds/general/project/neurogenomics-lab/ephemeral/MAGMA_Files_Public/data/GWAS_munged/eqtl-a-ENSG00000064989/logs/snp_bi_allelic.tsv Writing uncompressed instead of gzipped to enable tabix indexing. Converting full summary stats file to tabix format for fast querying... Reading header. Ensuring file is bgzipped. Tabix-indexing file. Removing temporary .tsv file. Computing Z-score from P using formula: `sign(BETA)*sqrt(stats::qchisq(P,1,lower=FALSE)` N already exists within sumstats_dt. 4,021 SNPs (23.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, AF1, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.A1.1000G.EUR, FREQ.A1.ESP.EUR, FREQ.ALLELE1.HAPMAPCEU, FREQ.B, FREQ1, FREQ1.HAPMAP, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_A1, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, AF_EFF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Sorting coordinates with 'data.table'. Writing in tabular format ==> /rds/general/project/neurogenomics-lab/ephemeral/MAGMA_Files_Public/data/GWAS_munged/eqtl-a-ENSG00000064989/eqtl-a-ENSG00000064989.tsv Writing uncompressed instead of gzipped to enable tabix indexing. Converting full summary stats file to tabix format for fast querying... Reading header. Ensuring file is bgzipped. Tabix-indexing file. Removing temporary .tsv file. Summary statistics report: - 17,094 rows (94.9% of original 18,018 rows) - 17,094 unique variants - 1,122 genome-wide significant variants (P<5e-8) - 22 chromosomes Done munging in 2.234 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 END FILTER FRQ BETA SE 1: rs12103 1 1247494 T C 1247494 PASS 0.754845 0.01245300 0.0138351 2: rs4648739 1 1894284 T C 1894284 PASS 0.228823 0.00560920 0.0141682 3: rs425277 1 2069172 C T 2069172 PASS 0.282999 0.01220950 0.0132123 4: rs78265569 1 2146165 C A 2146165 PASS 0.073182 -0.00622289 0.0228531 5: rs11576356 1 2233961 G A 2233961 PASS 0.146087 0.01595090 0.0168507 LP N P Z 1: 0.434136 18440 0.3680137 0.9002002 2: 0.159735 14882 0.6922532 0.3957991 3: 0.449177 27015 0.3554864 0.9239998 4: 0.104956 31155 0.7853152 -0.2723991 5: 0.463511 23874 0.3439450 0.9463992