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-ENSG00000189339
Constructing ScanVcfParam object.
VCF contains: 17,955 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: 17,954 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:
   - 17,954 rows
   - 17,954 unique variants
   - 182 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 32 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 17,954 SNPs using BSgenome::snpsById...
BSgenome::snpsById done in 12 seconds.
406 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-ENSG00000189339/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 17,559 SNPs using BSgenome::snpsById...
BSgenome::snpsById done in 12 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.
719 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-ENSG00000189339/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.
3,901 SNPs (23.2%) 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-ENSG00000189339/eqtl-a-ENSG00000189339.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:
   - 16,840 rows (93.8% of original 17,954 rows)
   - 16,840 unique variants
   - 174 genome-wide significant variants (P<5e-8)
   - 22 chromosomes
Done munging in 2.002 minutes.
Successfully finished preparing sumstats file, preview:
Reading header.
           SNP CHR     BP A1 A2    END FILTER       FRQ        BETA        SE
1:   rs4108074   1 618463  G  A 618463   PASS 0.0779817 -0.01424530 0.0221959
2: rs151190501   1 662613  G  A 662613   PASS 0.0108268  0.06080510 0.0575098
3:  rs61769339   1 662622  G  A 662622   PASS 0.0764669  0.00549835 0.0223965
4: rs150820983   1 676127  C  T 676127   PASS 0.0216049 -0.04102510 0.0409351
5:  rs12238997   1 693731  A  G 693731   PASS 0.1073070 -0.01236090 0.0192297
          LP    N         P          Z
1: 0.2831600   84 0.5210027 -0.6418005
2: 0.5369730  508 0.2904203  1.0572000
3: 0.0935859 1427 0.8061467  0.2454000
4: 0.4999740   85 0.3162467 -1.0022006
5: 0.2838100 4050 0.5202235 -0.6430009