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-ENSG00000064545 Constructing ScanVcfParam object. VCF contains: 6,880 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: 6,878 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: - 6,878 rows - 6,878 unique variants - 34 genome-wide significant variants (P<5e-8) - 1 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 6,878 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 18 seconds. Loading SNPlocs data. Loading reference genome data. Preprocessing RSIDs. Validating RSIDs of 6,878 SNPs using BSgenome::snpsById... BSgenome::snpsById done in 20 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 6,878 SNPs using BSgenome::snpsById... BSgenome::snpsById done in 7 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. 227 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-ENSG00000064545/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. 804 SNPs (12.1%) 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-ENSG00000064545/eqtl-a-ENSG00000064545.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: - 6,651 rows (96.7% of original 6,878 rows) - 6,651 unique variants - 32 genome-wide significant variants (P<5e-8) - 1 chromosomes Done munging in 0.852 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 END FILTER FRQ BETA 1: rs117951771 19 18239971 C T 18239971 PASS 0.0179157 0.0414763 2: rs273493 19 18240127 T C 18240127 PASS 0.9403400 -0.0483302 3: rs12609740 19 18240298 G A 18240298 PASS 0.1367210 -0.0012664 4: rs148235907 19 18240355 G A 18240355 PASS 0.0180908 0.0419396 5: rs10406361 19 18241708 G A 18241708 PASS 0.5351780 -0.0122679 SE LP N P Z 1: 0.0448684 0.4493040 21848 0.35538247 0.92419948 2: 0.0251249 1.2641600 31240 0.05443021 -1.92339702 3: 0.0173241 0.0261119 31567 0.94164694 -0.07320003 4: 0.0446546 0.4588850 21962 0.34762820 0.93919974 5: 0.0119326 0.5171980 31569 0.30394990 -1.02799985