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-ENSG00000214160 Constructing ScanVcfParam object. VCF contains: 18,925 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: 18,922 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: - 18,922 rows - 18,922 unique variants - 213 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 27 seconds. Loading SNPlocs data. Loading reference genome data. Preprocessing RSIDs. Validating RSIDs of 10,000 SNPs using BSgenome::snpsById... BSgenome::snpsById done in 46 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 18,922 SNPs using BSgenome::snpsById... BSgenome::snpsById done in 12 seconds. 399 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-ENSG00000214160/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 18,525 SNPs using BSgenome::snpsById... BSgenome::snpsById done in 14 seconds. Checking for correct direction of A1 (reference) and A2 (alternative allele). There are 1 SNPs where A1 doesn't match the reference genome. These will be flipped with their effect columns. 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. 597 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-ENSG00000214160/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. 3,630 SNPs (20.2%) 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-ENSG00000214160/eqtl-a-ENSG00000214160.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: - 17,928 rows (94.7% of original 18,922 rows) - 17,928 unique variants - 211 genome-wide significant variants (P<5e-8) - 22 chromosomes Done munging in 1.818 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 0.01628080 0.0138348 2: rs4648739 1 1894284 T C 1894284 PASS 0.228823 0.00314394 0.0141683 3: rs425277 1 2069172 C T 2069172 PASS 0.282999 0.00193830 0.0132127 4: rs78265569 1 2146165 C A 2146165 PASS 0.073182 0.03219090 0.0228515 5: rs11576356 1 2233961 G A 2233961 PASS 0.146087 -0.00256139 0.0168512 LP N P Z 1: 0.6212470 18440 0.2391955 1.1770000 2: 0.0838254 14882 0.8244695 0.2218001 3: 0.0538191 27015 0.8834478 0.1465999 4: 0.7987300 31155 0.1589535 1.4086000 5: 0.0559967 23874 0.8790292 -0.1522000