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-ENSG00000228727
Constructing ScanVcfParam object.
VCF contains: 36,329 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: 36,329 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:
   - 36,329 rows
   - 36,329 unique variants
   - 6 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 37 seconds.
Loading SNPlocs data.
Loading reference genome data.
Preprocessing RSIDs.
Validating RSIDs of 10,000 SNPs using BSgenome::snpsById...
BSgenome::snpsById done in 60 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 36,329 SNPs using BSgenome::snpsById...
BSgenome::snpsById done in 39 seconds.
22,157 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-ENSG00000228727/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 14,192 SNPs using BSgenome::snpsById...
BSgenome::snpsById done in 18 seconds.
Checking for correct direction of A1 (reference) and A2 (alternative allele).
There are 1 SNPs where neither A1 nor A2 match the reference genome. 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-ENSG00000228727/logs/alleles_dont_match_ref_gen.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.
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.
847 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-ENSG00000228727/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.
3,401 SNPs (25.5%) 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-ENSG00000228727/eqtl-a-ENSG00000228727.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:
   - 13,344 rows (36.7% of original 36,329 rows)
   - 13,344 unique variants
   - 0 genome-wide significant variants (P<5e-8)
   - 22 chromosomes
Done munging in 2.887 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 -0.00461689 0.0138355
2:  rs4648739   1 1894284  T  C 1894284   PASS 0.228823 -0.00665763 0.0141682
3:   rs425277   1 2069172  C  T 2069172   PASS 0.282999  0.01449510 0.0132122
4: rs78265569   1 2146165  C  A 2146165   PASS 0.073182  0.01276330 0.0228529
5: rs11576356   1 2233961  G  A 2233961   PASS 0.146087 -0.02308130 0.0168501
         LP    N         P          Z
1: 0.131543 4254 0.7386811 -0.3336004
2: 0.194938 4026 0.6383546 -0.4700006
3: 0.564408 8269 0.2726415  1.0969997
4: 0.239147 8184 0.5765713  0.5584000
5: 0.767800 8267 0.1706868 -1.3700002